diff options
Diffstat (limited to 'wqflask')
33 files changed, 1553 insertions, 2419 deletions
diff --git a/wqflask/base/trait.py b/wqflask/base/trait.py index 0f8f937c..ec8c40a0 100644 --- a/wqflask/base/trait.py +++ b/wqflask/base/trait.py @@ -516,7 +516,7 @@ def retrieve_trait_info(trait, dataset, get_qtl_info=False): # If the dataset is confidential and the user has access to confidential # phenotype traits, then display the pre-publication description instead # of the post-publication description - if trait.confidential: + if not trait.pubmed_id: trait.abbreviation = trait.pre_publication_abbreviation trait.description_display = trait.pre_publication_description else: diff --git a/wqflask/tests/unit/wqflask/marker_regression/test_gemma_mapping.py b/wqflask/tests/unit/wqflask/marker_regression/test_gemma_mapping.py new file mode 100644 index 00000000..5b621264 --- /dev/null +++ b/wqflask/tests/unit/wqflask/marker_regression/test_gemma_mapping.py @@ -0,0 +1,205 @@ +# test for wqflask/marker_regression/gemma_mapping.py +import unittest +import random +from unittest import mock +from wqflask.marker_regression.gemma_mapping import run_gemma +from wqflask.marker_regression.gemma_mapping import gen_pheno_txt_file +from wqflask.marker_regression.gemma_mapping import gen_covariates_file +from wqflask.marker_regression.gemma_mapping import parse_gemma_output +from wqflask.marker_regression.gemma_mapping import parse_loco_output + + +class AttributeSetter: + def __init__(self, obj): + for key, val in obj.items(): + setattr(self, key, val) + + +class MockGroup(AttributeSetter): + def get_samplelist(self): + return None + + +class TestGemmaMapping(unittest.TestCase): + + @mock.patch("wqflask.marker_regression.gemma_mapping.parse_loco_output") + def test_run_gemma_firstrun_set_false(self, mock_parse_loco): + """add tests for gemma function where first run is set to false""" + dataset = AttributeSetter( + {"group": AttributeSetter({"genofile": "genofile.geno"})}) + + output_file = "file1" + mock_parse_loco.return_value = [] + this_trait = AttributeSetter({"name": "t1"}) + + result = run_gemma(this_trait=this_trait, this_dataset=dataset, samples=[], vals=[ + ], covariates="", use_loco=True, first_run=False, output_files=output_file) + + expected_results = ([], "file1") + self.assertEqual(expected_results, result) + + @mock.patch("wqflask.marker_regression.gemma_mapping.webqtlConfig.GENERATED_IMAGE_DIR", "/home/user/img") + @mock.patch("wqflask.marker_regression.gemma_mapping.GEMMAOPTS", "-debug") + @mock.patch("wqflask.marker_regression.gemma_mapping.GEMMA_WRAPPER_COMMAND", "ghc") + @mock.patch("wqflask.marker_regression.gemma_mapping.TEMPDIR", "/home/user/data/") + @mock.patch("wqflask.marker_regression.gemma_mapping.parse_loco_output") + @mock.patch("wqflask.marker_regression.gemma_mapping.logger") + @mock.patch("wqflask.marker_regression.gemma_mapping.flat_files") + @mock.patch("wqflask.marker_regression.gemma_mapping.gen_covariates_file") + @mock.patch("wqflask.marker_regression.run_mapping.random.choice") + @mock.patch("wqflask.marker_regression.gemma_mapping.os") + @mock.patch("wqflask.marker_regression.gemma_mapping.gen_pheno_txt_file") + def test_run_gemma_firstrun_set_true(self, mock_gen_pheno_txt, mock_os, mock_choice, mock_gen_covar, mock_flat_files, mock_logger, mock_parse_loco): + """add tests for run_gemma where first run is set to true""" + chromosomes = [] + for i in range(1, 5): + chromosomes.append(AttributeSetter({"name": f"CH{i}"})) + chromo = AttributeSetter({"chromosomes": chromosomes}) + dataset_group = MockGroup( + {"name": "GP1", "genofile": "file_geno"}) + dataset = AttributeSetter({"group": dataset_group, "name": "dataset1_name", + "species": AttributeSetter({"chromosomes": chromo})}) + trait = AttributeSetter({"name": "trait1"}) + samples = [] + mock_gen_pheno_txt.return_value = None + mock_os.path.isfile.return_value = True + mock_gen_covar.return_value = None + mock_choice.return_value = "R" + mock_flat_files.return_value = "/home/genotype/bimbam" + mock_parse_loco.return_value = [] + results = run_gemma(this_trait=trait, this_dataset=dataset, samples=[ + ], vals=[], covariates="", use_loco=True) + system_calls = [mock.call('ghc --json -- -debug -g /home/genotype/bimbam/file_geno.txt -p /home/user/data//gn2/trait1_dataset1_name_pheno.txt -a /home/genotype/bimbam/file_snps.txt -gk > /home/user/data//gn2/GP1_K_RRRRRR.json'), + mock.call('ghc --json --input /home/user/data//gn2/GP1_K_RRRRRR.json -- -debug -a /home/genotype/bimbam/file_snps.txt -lmm 2 -g /home/genotype/bimbam/file_geno.txt -p /home/user/data//gn2/trait1_dataset1_name_pheno.txt > /home/user/data//gn2/GP1_GWA_RRRRRR.json')] + mock_os.system.assert_has_calls(system_calls) + mock_gen_pheno_txt.assert_called_once() + mock_parse_loco.assert_called_once_with(dataset, "GP1_GWA_RRRRRR") + mock_os.path.isfile.assert_called_once_with( + ('/home/user/imgfile_output.assoc.txt')) + self.assertEqual(mock_logger.debug.call_count, 2) + self.assertEqual(mock_flat_files.call_count, 4) + self.assertEqual(results, ([], "GP1_GWA_RRRRRR")) + + @mock.patch("wqflask.marker_regression.gemma_mapping.TEMPDIR", "/home/user/data") + def test_gen_pheno_txt_file(self): + """add tests for generating pheno txt file""" + with mock.patch("builtins.open", mock.mock_open())as mock_open: + gen_pheno_txt_file(this_dataset={}, genofile_name="", vals=[ + "x", "w", "q", "we", "R"], trait_filename="fitr.re") + mock_open.assert_called_once_with( + '/home/user/data/gn2/fitr.re.txt', 'w') + filehandler = mock_open() + values = ["x", "w", "q", "we", "R"] + write_calls = [mock.call('NA\n'), mock.call('w\n'), mock.call( + 'q\n'), mock.call('we\n'), mock.call('R\n')] + + filehandler.write.assert_has_calls(write_calls) + + @mock.patch("wqflask.marker_regression.gemma_mapping.flat_files") + @mock.patch("wqflask.marker_regression.gemma_mapping.create_trait") + @mock.patch("wqflask.marker_regression.gemma_mapping.create_dataset") + def test_gen_covariates_file(self, create_dataset, create_trait, flat_files): + """add tests for generating covariates files""" + covariates = "X1:X2,Y1:Y2,M1:M3,V1:V2" + samplelist = ["X1", "X2", "X3", "X4"] + create_dataset_side_effect = [] + create_trait_side_effect = [] + + for i in range(4): + create_dataset_side_effect.append(AttributeSetter({"name": f'name_{i}'})) + create_trait_side_effect.append( + AttributeSetter({"data": [f'data_{i}']})) + + create_dataset.side_effect = create_trait_side_effect + create_trait.side_effect = create_trait_side_effect + + group = MockGroup({"name": "group_X", "samplelist": samplelist}) + this_dataset = AttributeSetter({"group": group}) + flat_files.return_value = "Home/Genenetwork" + + with mock.patch("builtins.open", mock.mock_open())as mock_open: + gen_covariates_file(this_dataset=this_dataset, covariates=covariates, + samples=["x1", "x2", "X3"]) + + create_dataset.assert_has_calls( + [mock.call('X2'), mock.call('Y2'), mock.call('M3'), mock.call('V2')]) + mock_calls = [] + trait_names = ["X1", "Y1", "M1", "V1"] + + for i, trait in enumerate(create_trait_side_effect): + mock_calls.append( + mock.call(dataset=trait, name=trait_names[i], cellid=None)) + + create_trait.assert_has_calls(mock_calls) + + flat_files.assert_called_once_with('mapping') + mock_open.assert_called_once_with( + 'Home/Genenetwork/group_X_covariates.txt', 'w') + filehandler = mock_open() + filehandler.write.assert_has_calls([mock.call( + '-9\t'), mock.call('-9\t'), mock.call('-9\t'), mock.call('-9\t'), mock.call('\n')]) + + @mock.patch("wqflask.marker_regression.gemma_mapping.webqtlConfig.GENERATED_IMAGE_DIR", "/home/user/img/") + def test_parse_gemma_output(self): + """add test for generating gemma output with obj returned""" + file = """X/Y\t gn2\t21\tQ\tE\tA\tP\tMMB\tCDE\t0.5 +X/Y\tgn2\t21322\tQ\tE\tA\tP\tMMB\tCDE\t0.5 +chr\tgn1\t12312\tQ\tE\tA\tP\tMMB\tCDE\t0.7 +X\tgn7\t2324424\tQ\tE\tA\tP\tMMB\tCDE\t0.4 +125\tgn9\t433575\tQ\tE\tA\tP\tMMB\tCDE\t0.67 +""" + with mock.patch("builtins.open", mock.mock_open(read_data=file)) as mock_open: + results = parse_gemma_output(genofile_name="gema_file") + expected = [{'name': ' gn2', 'chr': 'X/Y', 'Mb': 2.1e-05, 'p_value': 0.5, 'lod_score': 0.3010299956639812}, {'name': 'gn2', 'chr': 'X/Y', 'Mb': 0.021322, 'p_value': 0.5, 'lod_score': 0.3010299956639812}, + {'name': 'gn7', 'chr': 'X', 'Mb': 2.324424, 'p_value': 0.4, 'lod_score': 0.3979400086720376}, {'name': 'gn9', 'chr': 125, 'Mb': 0.433575, 'p_value': 0.67, 'lod_score': 0.17392519729917352}] + mock_open.assert_called_once_with( + "/home/user/img/gema_file_output.assoc.txt") + self.assertEqual(results, expected) + + @mock.patch("wqflask.marker_regression.gemma_mapping.webqtlConfig.GENERATED_IMAGE_DIR", "/home/user/img") + def test_parse_gemma_output_with_empty_return(self): + """add tests for parse gemma output where nothing returned""" + output_file_results = """chr\t today""" + with mock.patch("builtins.open", mock.mock_open(read_data=output_file_results)) as mock_open: + results = parse_gemma_output(genofile_name="gema_file") + self.assertEqual(results, []) + + @mock.patch("wqflask.marker_regression.gemma_mapping.TEMPDIR", "/home/tmp") + @mock.patch("wqflask.marker_regression.gemma_mapping.os") + @mock.patch("wqflask.marker_regression.gemma_mapping.json") + def test_parse_loco_outputfile_found(self, mock_json, mock_os): + """add tests for parse loco output file found""" + mock_json.load.return_value = { + "files": [["file_name", "user", "~/file1"], + ["file_name", "user", "~/file2"]] + } + return_file_1 = """X/Y\t L1\t21\tQ\tE\tA\tP\tMMB\tCDE\t0.5 +X/Y\tL2\t21322\tQ\tE\tA\tP\tMMB\tCDE\t0.5 +chr\tL3\t12312\tQ\tE\tA\tP\tMMB\tCDE\t0.7""" + return_file_2 = """chr\tother\t21322\tQ\tE\tA\tP\tMMB\tCDE\t0.5""" + mock_os.path.isfile.return_value = True + file_to_write = """{"files":["file_1","file_2"]}""" + with mock.patch("builtins.open") as mock_open: + + handles = (mock.mock_open(read_data="gwas").return_value, mock.mock_open( + read_data=return_file_1).return_value, mock.mock_open(read_data=return_file_2).return_value) + mock_open.side_effect = handles + results = parse_loco_output( + this_dataset={}, gwa_output_filename=".xw/") + expected_results = [{'name': ' L1', 'chr': 'X/Y', 'Mb': 2.1e-05, 'p_value': 0.5, 'lod_score': 0.3010299956639812}, { + 'name': 'L2', 'chr': 'X/Y', 'Mb': 0.021322, 'p_value': 0.5, 'lod_score': 0.3010299956639812}] + + self.assertEqual(expected_results, results) + + @mock.patch("wqflask.marker_regression.gemma_mapping.TEMPDIR", "/home/tmp") + @mock.patch("wqflask.marker_regression.gemma_mapping.os") + def test_parse_loco_outputfile_not_found(self, mock_os): + """add tests for parse loco output where output file not found""" + + mock_os.path.isfile.return_value = False + file_to_write = """{"files":["file_1","file_2"]}""" + + with mock.patch("builtins.open", mock.mock_open(read_data=file_to_write)) as mock_open: + results = parse_loco_output( + this_dataset={}, gwa_output_filename=".xw/") + self.assertEqual(results, []) diff --git a/wqflask/tests/unit/wqflask/marker_regression/test_plink_mapping.py b/wqflask/tests/unit/wqflask/marker_regression/test_plink_mapping.py new file mode 100644 index 00000000..5eec93f1 --- /dev/null +++ b/wqflask/tests/unit/wqflask/marker_regression/test_plink_mapping.py @@ -0,0 +1,85 @@ +# test for wqflask/marker_regression/plink_mapping.py +import unittest +from unittest import mock +from wqflask.marker_regression.plink_mapping import build_line_list +from wqflask.marker_regression.plink_mapping import get_samples_from_ped_file +from wqflask.marker_regression.plink_mapping import flat_files +from wqflask.marker_regression.plink_mapping import gen_pheno_txt_file_plink +from wqflask.marker_regression.plink_mapping import parse_plink_output + + +class AttributeSetter: + def __init__(self, obj): + for key, val in obj.items(): + setattr(self, key, val) +class TestPlinkMapping(unittest.TestCase): + + + def test_build_line_list(self): + """test for building line list""" + line_1 = "this is line one test" + irregular_line = " this is an, irregular line " + exp_line1 = ["this", "is", "line", "one", "test"] + + results = build_line_list(irregular_line) + self.assertEqual(exp_line1, build_line_list(line_1)) + self.assertEqual([], build_line_list()) + self.assertEqual(["this", "is", "an,", "irregular", "line"], results) + + @mock.patch("wqflask.marker_regression.plink_mapping.flat_files") + def test_get_samples_from_ped_file(self, mock_flat_files): + """test for getting samples from ped file""" + dataset = AttributeSetter({"group": AttributeSetter({"name": "n_1"})}) + file_sample = """Expected_1\tline test +Expected_2\there + Expected_3\tthree""" + mock_flat_files.return_value = "/home/user/" + with mock.patch("builtins.open", mock.mock_open(read_data=file_sample)) as mock_open: + results = get_samples_from_ped_file(dataset) + mock_flat_files.assert_called_once_with("mapping") + mock_open.assert_called_once_with("/home/user/n_1.ped", "r") + self.assertEqual( + ["Expected_1", "Expected_2", "Expected_3"], results) + + @mock.patch("wqflask.marker_regression.plink_mapping.TMPDIR", "/home/user/data/") + @mock.patch("wqflask.marker_regression.plink_mapping.get_samples_from_ped_file") + def test_gen_pheno_txt_file_plink(self, mock_samples): + """test for getting gen_pheno txt file""" + mock_samples.return_value = ["Expected_1", "Expected_2", "Expected_3"] + + trait = AttributeSetter({"name": "TX"}) + dataset = AttributeSetter({"group": AttributeSetter({"name": "n_1"})}) + vals = ["value=K1", "value=K2", "value=K3"] + with mock.patch("builtins.open", mock.mock_open()) as mock_open: + results = gen_pheno_txt_file_plink(this_trait=trait, dataset=dataset, + vals=vals, pheno_filename="ph_file") + mock_open.assert_called_once_with( + "/home/user/data/ph_file.txt", "wb") + filehandler = mock_open() + calls_expected = [mock.call('FID\tIID\tTX\n'), + mock.call('Expected_1\tExpected_1\tK1\nExpected_2\tExpected_2\tK2\nExpected_3\tExpected_3\tK3\n')] + + filehandler.write.assert_has_calls(calls_expected) + + filehandler.close.assert_called_once() + + @mock.patch("wqflask.marker_regression.plink_mapping.TMPDIR", "/home/user/data/") + @mock.patch("wqflask.marker_regression.plink_mapping.build_line_list") + def test_parse_plink_output(self, mock_line_list): + """test for parsing plink output""" + chromosomes = [0, 34, 110, 89, 123, 23, 2] + species = AttributeSetter( + {"name": "S1", "chromosomes": AttributeSetter({"chromosomes": chromosomes})}) + + fake_file = """0 AACCAT T98.6 0.89\n2 AATA B45 0.3\n121 ACG B56.4 NA""" + + mock_line_list.side_effect = [["0", "AACCAT", "T98.6", "0.89"], [ + "2", "AATA", "B45", "0.3"], ["121", "ACG", "B56.4", "NA"]] + with mock.patch("builtins.open", mock.mock_open(read_data=fake_file)) as mock_open: + parse_results = parse_plink_output( + output_filename="P1_file", species=species) + mock_open.assert_called_once_with( + "/home/user/data/P1_file.qassoc", "rb") + expected = (2, {'AACCAT': 0.89, 'AATA': 0.3}) + + self.assertEqual(parse_results, expected) diff --git a/wqflask/tests/unit/wqflask/marker_regression/test_qtlreaper_mapping.py b/wqflask/tests/unit/wqflask/marker_regression/test_qtlreaper_mapping.py new file mode 100644 index 00000000..b47f877a --- /dev/null +++ b/wqflask/tests/unit/wqflask/marker_regression/test_qtlreaper_mapping.py @@ -0,0 +1,21 @@ +import unittest +from unittest import mock +from wqflask.marker_regression.qtlreaper_mapping import gen_pheno_txt_file + +#issues some methods in genofile object are not defined +#modify samples should equal to vals +class TestQtlReaperMapping(unittest.TestCase): + @mock.patch("wqflask.marker_regression.qtlreaper_mapping.TEMPDIR", "/home/user/data") + def test_gen_pheno_txt_file(self): + vals=["V1","x","V4","V3","x"] + samples=["S1","S2","S3","S4","S5"] + trait_filename="trait_file" + with mock.patch("builtins.open", mock.mock_open())as mock_open: + gen_pheno_txt_file(samples=samples,vals=vals,trait_filename=trait_filename) + mock_open.assert_called_once_with("/home/user/data/gn2/trait_file.txt","w") + filehandler=mock_open() + write_calls= [mock.call('Trait\t'),mock.call('S1\tS3\tS4\n'),mock.call('T1\t'),mock.call('V1\tV4\tV3')] + + filehandler.write.assert_has_calls(write_calls) + + diff --git a/wqflask/tests/unit/wqflask/marker_regression/test_rqtl_mapping.py b/wqflask/tests/unit/wqflask/marker_regression/test_rqtl_mapping.py new file mode 100644 index 00000000..c585f1df --- /dev/null +++ b/wqflask/tests/unit/wqflask/marker_regression/test_rqtl_mapping.py @@ -0,0 +1,48 @@ +import unittest +from unittest import mock +from wqflask import app +from wqflask.marker_regression.rqtl_mapping import get_trait_data_type +from wqflask.marker_regression.rqtl_mapping import sanitize_rqtl_phenotype +from wqflask.marker_regression.rqtl_mapping import sanitize_rqtl_names + +class TestRqtlMapping(unittest.TestCase): + + def setUp(self): + self.app_context=app.app_context() + self.app_context.push() + + def tearDown(self): + self.app_context.pop() + + + @mock.patch("wqflask.marker_regression.rqtl_mapping.g") + @mock.patch("wqflask.marker_regression.rqtl_mapping.logger") + def test_get_trait_data(self,mock_logger,mock_db): + """test for getting trait data_type return True""" + query_value="""SELECT value FROM TraitMetadata WHERE type='trait_data_type'""" + mock_db.db.execute.return_value.fetchone.return_value=["""{"type":"trait_data_type","name":"T1","traid_id":"fer434f"}"""] + results=get_trait_data_type("traid_id") + mock_db.db.execute.assert_called_with(query_value) + self.assertEqual(results,"fer434f") + + def test_sanitize_rqtl_phenotype(self): + """test for sanitizing rqtl phenotype""" + vals=['f',"x","r","x","x"] + results=sanitize_rqtl_phenotype(vals) + expected_phenotype_string='c(f,NA,r,NA,NA)' + + self.assertEqual(results,expected_phenotype_string) + + def test_sanitize_rqtl_names(self): + """test for sanitzing rqtl names""" + vals=['f',"x","r","x","x"] + expected_sanitized_name="c('f',NA,'r',NA,NA)" + results=sanitize_rqtl_names(vals) + self.assertEqual(expected_sanitized_name,results) + + + + + + + diff --git a/wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py b/wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py new file mode 100644 index 00000000..4129cc0c --- /dev/null +++ b/wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py @@ -0,0 +1,284 @@ +import unittest +import datetime +from unittest import mock + +from wqflask.marker_regression.run_mapping import get_genofile_samplelist +from wqflask.marker_regression.run_mapping import geno_db_exists +from wqflask.marker_regression.run_mapping import write_input_for_browser +from wqflask.marker_regression.run_mapping import export_mapping_results +from wqflask.marker_regression.run_mapping import trim_markers_for_figure +from wqflask.marker_regression.run_mapping import get_perm_strata +from wqflask.marker_regression.run_mapping import get_chr_lengths + + +class AttributeSetter: + def __init__(self, obj): + for k, v in obj.items(): + setattr(self, k, v) + + +class MockGroup(AttributeSetter): + + def get_genofiles(self): + return [{"location": "~/genofiles/g1_file", "sample_list": ["S1", "S2", "S3", "S4"]}] + + +class TestRunMapping(unittest.TestCase): + def setUp(self): + + self.group = MockGroup( + {"genofile": "~/genofiles/g1_file", "name": "GP1_", "species": "Human"}) + chromosomes = { + "3": AttributeSetter({ + "name": "C1", + "length": "0.04" + }), + "4": AttributeSetter({ + "name": "C2", + "length": "0.03" + }), + "5": AttributeSetter({ + "name": "C4", + "length": "0.01" + }) + } + self.dataset = AttributeSetter( + {"fullname": "dataser_1", "group": self.group, "type": "ProbeSet"}) + + self.chromosomes = AttributeSetter({"chromosomes": chromosomes}) + self.trait = AttributeSetter( + {"symbol": "IGFI", "chr": "X1", "mb": 123313}) + + def tearDown(self): + self.dataset = AttributeSetter( + {"group": {"location": "~/genofiles/g1_file"}}) + + def test_get_genofile_samplelist(self): + + results_1 = get_genofile_samplelist(self.dataset) + self.assertEqual(results_1, ["S1", "S2", "S3", "S4"]) + self.group.genofile = "~/genofiles/g2_file" + result_2 = get_genofile_samplelist(self.dataset) + self.assertEqual(result_2, []) + + @mock.patch("wqflask.marker_regression.run_mapping.data_set") + def test_if_geno_db_exists(self, mock_data_set): + mock_data_set.create_dataset.side_effect = [ + AttributeSetter({}), Exception()] + results_no_error = geno_db_exists(self.dataset) + results_with_error = geno_db_exists(self.dataset) + + self.assertEqual(mock_data_set.create_dataset.call_count, 2) + self.assertEqual(results_with_error, "False") + self.assertEqual(results_no_error, "True") + + def test_trim_markers_for_figure(self): + + markers = [{ + "name": "MK1", + "chr": "C1", + "cM": "1", + "Mb": "12000", + "genotypes": [], + "dominance":"TT", + "additive":"VA", + "lod_score":0.5 + }, + { + "name": "MK2", + "chr": "C2", + "cM": "15", + "Mb": "10000", + "genotypes": [], + "lod_score":0.7 + }, + { + "name": "MK1", + "chr": "C3", + "cM": "45", + "Mb": "1", + "genotypes": [], + "dominance":"Tt", + "additive":"VE", + "lod_score":1 + }] + + marker_2 = [{ + "name": "MK1", + "chr": "C1", + "cM": "1", + "Mb": "12000", + "genotypes": [], + "dominance":"TT", + "additive":"VA", + "p_wald":4.6 + }] + results = trim_markers_for_figure(markers) + result_2 = trim_markers_for_figure(marker_2) + expected = [ + { + "name": "MK1", + "chr": "C1", + "cM": "1", + "Mb": "12000", + "genotypes": [], + "dominance":"TT", + "additive":"VA", + "lod_score":0.5 + }, + { + "name": "MK1", + "chr": "C3", + "cM": "45", + "Mb": "1", + "genotypes": [], + "dominance":"Tt", + "additive":"VE", + "lod_score":1 + } + + ] + self.assertEqual(results, expected) + self.assertEqual(result_2, marker_2) + + def test_export_mapping_results(self): + """test for exporting mapping results""" + datetime_mock = mock.Mock(wraps=datetime.datetime) + datetime_mock.now.return_value = datetime.datetime( + 2019, 9, 1, 10, 12, 12) + + markers = [{ + "name": "MK1", + "chr": "C1", + "cM": "1", + "Mb": "12000", + "genotypes": [], + "dominance":"TT", + "additive":"VA", + "lod_score":3 + }, + { + "name": "MK2", + "chr": "C2", + "cM": "15", + "Mb": "10000", + "genotypes": [], + "lod_score":7 + }, + { + "name": "MK1", + "chr": "C3", + "cM": "45", + "Mb": "1", + "genotypes": [], + "dominance":"Tt", + "additive":"VE", + "lod_score":7 + }] + + with mock.patch("builtins.open", mock.mock_open()) as mock_open: + + with mock.patch("wqflask.marker_regression.run_mapping.datetime.datetime", new=datetime_mock): + export_mapping_results(dataset=self.dataset, trait=self.trait, markers=markers, + results_path="~/results", mapping_scale="physic", score_type="-log(p)") + + write_calls = [ + mock.call('Time/Date: 09/01/19 / 10:12:12\n'), + mock.call('Population: Human GP1_\n'), mock.call( + 'Data Set: dataser_1\n'), + mock.call('Gene Symbol: IGFI\n'), mock.call( + 'Location: X1 @ 123313 Mb\n'), + mock.call('\n'), mock.call('Name,Chr,'), + mock.call('Mb,-log(p)'), mock.call('Cm,-log(p)'), + mock.call(',Additive'), mock.call(',Dominance'), + mock.call('\n'), mock.call('MK1,C1,'), + mock.call('12000,'), mock.call('1,'), + mock.call('3'), mock.call(',VA'), + mock.call(',TT'), mock.call('\n'), + mock.call('MK2,C2,'), mock.call('10000,'), + mock.call('15,'), mock.call('7'), + mock.call('\n'), mock.call('MK1,C3,'), + mock.call('1,'), mock.call('45,'), + mock.call('7'), mock.call(',VE'), + mock.call(',Tt') + + ] + mock_open.assert_called_once_with("~/results", "w+") + filehandler = mock_open() + filehandler.write.assert_has_calls(write_calls) + + @mock.patch("wqflask.marker_regression.run_mapping.random.choice") + def test_write_input_for_browser(self, mock_choice): + """test for writing input for browser""" + mock_choice.side_effect = ["F", "i", "l", "e", "s", "x"] + with mock.patch("builtins.open", mock.mock_open()) as mock_open: + expected = ['GP1__Filesx_GWAS', 'GP1__Filesx_ANNOT'] + + results = write_input_for_browser( + this_dataset=self.dataset, gwas_results={}, annotations={}) + self.assertEqual(results, expected) + + def test_get_perm_strata(self): + categorical_vars = ["C1", "C2", "W1"] + used_samples = ["S1", "S2"] + sample_list = AttributeSetter({"sample_attribute_values": { + "S1": { + "C1": "c1_value", + "C2": "c2_value", + "W1": "w1_value" + + }, + "S2": { + "W1": "w2_value", + "W2": "w2_value" + + }, + "S3": { + + "C1": "c1_value", + "C2": "c2_value" + + }, + + }}) + + results = get_perm_strata(this_trait={}, sample_list=sample_list, + categorical_vars=categorical_vars, used_samples=used_samples) + self.assertEqual(results, [2, 1]) + + def test_get_chr_length(self): + """test for getting chromosome length""" + chromosomes = AttributeSetter({"chromosomes": self.chromosomes}) + dataset = AttributeSetter({"species": chromosomes}) + results = get_chr_lengths( + mapping_scale="physic", mapping_method="reaper", dataset=dataset, qtl_results=[]) + chr_lengths = [] + for key, chromo in self.chromosomes.chromosomes.items(): + chr_lengths.append({"chr": chromo.name, "size": chromo.length}) + + self.assertEqual(chr_lengths, results) + + qtl_results = [{ + "chr": "16", + "cM": "0.2" + }, + { + "chr": "12", + "cM": "0.5" + }, + { + "chr": "18", + "cM": "0.1" + }, + { + "chr": "22", + "cM": "0.4" + }, + ] + + result_with_other_mapping_scale = get_chr_lengths( + mapping_scale="other", mapping_method="reaper", dataset=dataset, qtl_results=qtl_results) + expected_value = [{'chr': '1', 'size': '0'}, { + 'chr': '16', 'size': '500000.0'}, {'chr': '18', 'size': '400000.0'}] + + self.assertEqual(result_with_other_mapping_scale, expected_value) diff --git a/wqflask/wqflask/__init__.py b/wqflask/wqflask/__init__.py index 874cde17..0564cfa7 100644 --- a/wqflask/wqflask/__init__.py +++ b/wqflask/wqflask/__init__.py @@ -7,6 +7,11 @@ from flask import g from flask import Flask from utility import formatting from wqflask.markdown_routes import glossary_blueprint +from wqflask.markdown_routes import references_blueprint +from wqflask.markdown_routes import links_blueprint +from wqflask.markdown_routes import policies_blueprint +from wqflask.markdown_routes import environments_blueprint +from wqflask.markdown_routes import facilities_blueprint app = Flask(__name__) @@ -19,6 +24,11 @@ app.jinja_env.globals.update( # Registering blueprints app.register_blueprint(glossary_blueprint, url_prefix="/glossary") +app.register_blueprint(references_blueprint, url_prefix="/references") +app.register_blueprint(links_blueprint, url_prefix="/links") +app.register_blueprint(policies_blueprint, url_prefix="/policies") +app.register_blueprint(environments_blueprint, url_prefix="/environments") +app.register_blueprint(facilities_blueprint, url_prefix="/facilities") @app.before_request def before_request(): @@ -39,4 +49,4 @@ from wqflask import db_info from wqflask import user_login from wqflask import user_session -import wqflask.views +import wqflask.views diff --git a/wqflask/wqflask/correlation/show_corr_results.py b/wqflask/wqflask/correlation/show_corr_results.py index 4c2b64ba..1b801b1d 100644 --- a/wqflask/wqflask/correlation/show_corr_results.py +++ b/wqflask/wqflask/correlation/show_corr_results.py @@ -484,75 +484,78 @@ def generate_corr_json(corr_results, this_trait, dataset, target_dataset, for_ap if trait.view == False: continue results_dict = {} - if not for_api: - results_dict['checkbox'] = "<INPUT TYPE='checkbox' NAME='searchResult' class='checkbox trait_checkbox' style='padding-right: 0px;' VALUE='" + hmac.hmac_creation('{}:{}'.format(trait.name, trait.dataset.name)) + "'>" - results_dict['index'] = i + 1 - results_dict['trait_id'] = "<a href='/show_trait?trait_id="+str(trait.name)+"&dataset="+str(dataset.name)+"'>"+str(trait.name)+"</a>" - else: - results_dict['trait_id'] = trait.name + results_dict['index'] = i + 1 + results_dict['trait_id'] = trait.name + results_dict['dataset'] = trait.dataset.name if target_dataset.type == "ProbeSet": results_dict['symbol'] = trait.symbol - results_dict['description'] = trait.description_display + results_dict['description'] = "N/A" results_dict['location'] = trait.location_repr - results_dict['mean'] = float(trait.mean) + results_dict['mean'] = "N/A" + results_dict['lrs_score'] = "N/A" + results_dict['additive'] = "N/A" + if bool(trait.description_display): + results_dict['description'] = trait.description_display + if bool(trait.mean): + results_dict['mean'] = float(trait.mean) if trait.LRS_score_repr != "N/A": - results_dict['lrs_score'] = "%.1f" % float(trait.LRS_score_repr) - else: - results_dict['lrs_score'] = "N/A" + results_dict['lrs_score'] = f"{float(trait.LRS_score_repr):.1f}" results_dict['lrs_location'] = trait.LRS_location_repr - if trait.additive != "": - results_dict['additive'] = "%0.3f" % float(trait.additive) - else: - results_dict['additive'] = "N/A" - if for_api: - results_dict['sample_r'] = "%0.3f" % float(trait.sample_r) - else: - results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>" + if bool(trait.additive): + results_dict['additive'] = f"{float(trait.additive):.3f}" + results_dict['sample_r'] = f"{float(trait.sample_r):.3f}" results_dict['num_overlap'] = trait.num_overlap - results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) - if trait.lit_corr == "" or trait.lit_corr == 0: - results_dict['lit_corr'] = "--" - else: - results_dict['lit_corr'] = "%0.3f" % float(trait.lit_corr) - if trait.tissue_corr == "" or trait.tissue_corr == 0: - results_dict['tissue_corr'] = "--" - else: - results_dict['tissue_corr'] = "%0.3f" % float(trait.tissue_corr) + results_dict['sample_p'] = f"{float(trait.sample_p):.3e}" + results_dict['lit_corr'] = "--" + results_dict['tissue_corr'] = "--" + results_dict['tissue_pvalue'] = "--" + if bool(trait.lit_corr): + results_dict['lit_corr'] = f"{float(trait.lit_corr):.3f}" + if bool(trait.tissue_corr): + results_dict['tissue_corr'] = f"{float(trait.tissue_corr):.3f}" + results_dict['tissue_pvalue'] = f"{float(trait.tissue_pvalue):.3e}" elif target_dataset.type == "Publish": - results_dict['description'] = trait.description_display - results_dict['authors'] = trait.authors - if trait.pubmed_id: + results_dict['abbreviation_display'] = "N/A" + results_dict['description'] = "N/A" + results_dict['authors_display'] = "N/A" + results_dict['additive'] = "N/A" + if for_api: + results_dict['pubmed_id'] = "N/A" + results_dict['year'] = "N/A" + else: + results_dict['pubmed_link'] = "N/A" + results_dict['pubmed_text'] = "N/A" + + if bool(trait.abbreviation): + results_dict['abbreviation_display'] = trait.abbreviation + if bool(trait.description_display): + results_dict['description'] = trait.description_display + if bool(trait.authors): + authors_list = trait.authors.split(',') + if len(authors_list) > 6: + results_dict['authors_display'] = ", ".join(authors_list[:6]) + ", et al." + else: + results_dict['authors_display'] = trait.authors + if bool(trait.pubmed_id): if for_api: results_dict['pubmed_id'] = trait.pubmed_id results_dict['year'] = trait.pubmed_text else: - results_dict['pubmed'] = "<a href='" + trait.pubmed_link + "'> " + trait.pubmed_text + "</a>" - else: - if for_api: - results_dict['pubmed_id'] = "N/A" - results_dict['year'] = "N/A" - else: - results_dict['pubmed'] = "N/A" + results_dict['pubmed_link'] = trait.pubmed_link + results_dict['pubmed_text'] = trait.pubmed_text + results_dict['lrs_score'] = trait.LRS_score_repr results_dict['lrs_location'] = trait.LRS_location_repr - if trait.additive != "": - results_dict['additive'] = "%0.3f" % float(trait.additive) - else: - results_dict['additive'] = "N/A" - if for_api: - results_dict['sample_r'] = "%0.3f" % trait.sample_r - else: - results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % trait.sample_r + "</a>" + if bool(trait.additive): + results_dict['additive'] = f"{float(trait.additive):.3f}" + results_dict['sample_r'] = f"{float(trait.sample_r):.3f}" results_dict['num_overlap'] = trait.num_overlap - results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) + results_dict['sample_p'] = f"{float(trait.sample_p):.3e}" else: - results_dict['lrs_location'] = trait.LRS_location_repr - if for_api: - results_dict['sample_r'] = "%0.3f" % trait.sample_r - else: - results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>" + results_dict['location'] = trait.location_repr + results_dict['sample_r'] = f"{float(trait.sample_r):.3f}" results_dict['num_overlap'] = trait.num_overlap - results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) + results_dict['sample_p'] = f"{float(trait.sample_p):.3e}" results_list.append(results_dict) diff --git a/wqflask/wqflask/markdown_routes.py b/wqflask/wqflask/markdown_routes.py index 7a9fac41..601845d7 100644 --- a/wqflask/wqflask/markdown_routes.py +++ b/wqflask/wqflask/markdown_routes.py @@ -9,21 +9,24 @@ from flask import Blueprint from flask import render_template glossary_blueprint = Blueprint('glossary_blueprint', __name__) +references_blueprint = Blueprint("references_blueprint", __name__) +environments_blueprint = Blueprint("environments_blueprint", __name__) +links_blueprint = Blueprint("links_blueprint", __name__) +policies_blueprint = Blueprint("policies_blueprint", __name__) +facilities_blueprint = Blueprint("facilities_blueprint", __name__) def render_markdown(file_name): """Try to fetch the file name from Github and if that fails, try to -look for it inside the file system - - """ +look for it inside the file system """ github_url = ("https://raw.githubusercontent.com/" "genenetwork/gn-docs/master/") + md_content = requests.get(f"{github_url}{file_name}") if md_content.status_code == 200: - return markdown.Markdown().convert(md_content.content.decode("utf-8")) + return markdown.markdown(md_content.content.decode("utf-8"), extensions=['tables']) # TODO: Add fallback on our git server by checking the mirror. - # Content not available return (f"\nContent for {file_name} not available. " "Please check " @@ -37,3 +40,34 @@ def glossary(): return render_template( "glossary.html", rendered_markdown=render_markdown("general/glossary/glossary.md")), 200 + + +@references_blueprint.route('/') +def references(): + return render_template( + "references.html", + rendered_markdown=render_markdown("general/references/references.md")), 200 + + +@environments_blueprint.route("/") +def environments(): + return render_template("environment.html", rendered_markdown=render_markdown("general/environments/environments.md")), 200 + + +@links_blueprint.route("/") +def links(): + return render_template( + "links.html", + rendered_markdown=render_markdown("general/links/links.md")), 200 + + +@policies_blueprint.route("/") +def policies(): + return render_template( + "links.html", + rendered_markdown=render_markdown("general/policies/policies.md")), 200 + + +@facilities_blueprint.route("/") +def facilities(): + return render_template("facilities.html", rendered_markdown=render_markdown("general/help/facilities.md")), 200 diff --git a/wqflask/wqflask/marker_regression/display_mapping_results.py b/wqflask/wqflask/marker_regression/display_mapping_results.py index 3f6de2b2..08c2d750 100644 --- a/wqflask/wqflask/marker_regression/display_mapping_results.py +++ b/wqflask/wqflask/marker_regression/display_mapping_results.py @@ -74,6 +74,14 @@ DARKVIOLET = ImageColor.getrgb("darkviolet") MEDIUMPURPLE = ImageColor.getrgb("mediumpurple") # ---- END: Define common colours ---- # +# ZS: List of distinct colors for manhattan plot if user selects "varied" +COLOR_CODES = ["#FF0000", "#00FF00", "#0000FF", "#FFFF00", "#FF00FF", "#00FFFF", + "#000000", "#800000", "#008000", "#000080", "#808000", "#800080", + "#008080", "#808080", "#C00000", "#00C000", "#0000C0", "#C0C000", + "#C000C0", "#00C0C0", "#C0C0C0", "#400000", "#004000", "#000040"] + +DISTINCT_COLOR_LIST = [ImageColor.getrgb(color) for color in COLOR_CODES] + # ---- FONT FILES ---- # VERDANA_FILE = "./wqflask/static/fonts/verdana.ttf" VERDANA_BOLD_FILE = "./wqflask/static/fonts/verdanab.ttf" @@ -293,6 +301,12 @@ class DisplayMappingResults(object): self.plotScale = "physic" self.manhattan_plot = start_vars['manhattan_plot'] + if self.manhattan_plot: + self.color_scheme = "alternating" + if 'color_scheme' in start_vars: + self.color_scheme = start_vars['color_scheme'] + if self.color_scheme == "single": + self.manhattan_single_color = ImageColor.getrgb("#" + start_vars['manhattan_single_color']) if 'permCheck' in list(start_vars.keys()): self.permChecked = start_vars['permCheck'] @@ -2424,10 +2438,16 @@ class DisplayMappingResults(object): Yc = yZero - qtlresult['lod_score']*LRSHeightThresh/LRS_LOD_Max if self.manhattan_plot == True: - if self.selectedChr == -1 and (previous_chr_as_int % 2 == 1): - point_color = RED + if self.color_scheme == "single": + point_color = self.manhattan_single_color + elif self.color_scheme == "varied": + point_color = DISTINCT_COLOR_LIST[previous_chr_as_int] else: - point_color = BLUE + if self.selectedChr == -1 and (previous_chr_as_int % 2 == 1): + point_color = RED + else: + point_color = BLUE + im_drawer.text( text="5", xy=( diff --git a/wqflask/wqflask/marker_regression/gemma_mapping.py b/wqflask/wqflask/marker_regression/gemma_mapping.py index 68a8d5ba..02f91a32 100644 --- a/wqflask/wqflask/marker_regression/gemma_mapping.py +++ b/wqflask/wqflask/marker_regression/gemma_mapping.py @@ -31,16 +31,11 @@ def run_gemma(this_trait, this_dataset, samples, vals, covariates, use_loco, maf gwa_output_filename = this_dataset.group.name + "_GWA_" + ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(6)) this_chromosomes = this_dataset.species.chromosomes.chromosomes - chr_list_string = "" - for i in range(len(this_chromosomes)): - if i < (len(this_chromosomes) - 1): - chr_list_string += this_chromosomes[i+1].name + "," - else: - chr_list_string += this_chromosomes[i+1].name + this_chromosomes_name=[chromosome.name for chromosome in this_chromosomes] + chr_list_string=",".join(this_chromosomes_name) if covariates != "": gen_covariates_file(this_dataset, covariates, samples) - if use_loco == "True": generate_k_command = GEMMA_WRAPPER_COMMAND + ' --json --loco ' + chr_list_string + ' -- ' + GEMMAOPTS + ' -g %s/%s_geno.txt -p %s/gn2/%s.txt -a %s/%s_snps.txt -gk > %s/gn2/%s.json' % (flat_files('genotype/bimbam'), genofile_name, diff --git a/wqflask/wqflask/marker_regression/plink_mapping.py b/wqflask/wqflask/marker_regression/plink_mapping.py index fd91b6ca..5d675c38 100644 --- a/wqflask/wqflask/marker_regression/plink_mapping.py +++ b/wqflask/wqflask/marker_regression/plink_mapping.py @@ -9,11 +9,11 @@ import utility.logger logger = utility.logger.getLogger(__name__ ) def run_plink(this_trait, dataset, species, vals, maf): - plink_output_filename = webqtlUtil.genRandStr("%s_%s_"%(dataset.group.name, this_trait.name)) + plink_output_filename = webqtlUtil.genRandStr(f"{dataset.group.name}_{this_trait.name}_") gen_pheno_txt_file(dataset, vals) - plink_command = PLINK_COMMAND + ' --noweb --bfile %s/%s --no-pheno --no-fid --no-parents --no-sex --maf %s --out %s%s --assoc ' % ( - flat_files('mapping'), dataset.group.name, maf, TMPDIR, plink_output_filename) + + plink_command = f"{PLINK_COMMAND} --noweb --bfile {flat_files('mapping')}/{dataset.group.name} --no-pheno --no-fid --no-parents --no-sex --maf {maf} --out { TMPDIR}{plink_output_filename} --assoc " logger.debug("plink_command:", plink_command) os.system(plink_command) @@ -29,12 +29,12 @@ def gen_pheno_txt_file(this_dataset, vals): """Generates phenotype file for GEMMA/PLINK""" current_file_data = [] - with open("{}/{}.fam".format(flat_files('mapping'), this_dataset.group.name), "r") as outfile: + with open(f"{flat_files('mapping')}/{this_dataset.group.name}.fam", "r") as outfile: for i, line in enumerate(outfile): split_line = line.split() current_file_data.append(split_line) - with open("{}/{}.fam".format(flat_files('mapping'), this_dataset.group.name), "w") as outfile: + with open(f"{flat_files('mapping')}/{this_dataset.group.name}.fam","w") as outfile: for i, line in enumerate(current_file_data): if vals[i] == "x": this_val = -9 @@ -44,8 +44,8 @@ def gen_pheno_txt_file(this_dataset, vals): def gen_pheno_txt_file_plink(this_trait, dataset, vals, pheno_filename = ''): ped_sample_list = get_samples_from_ped_file(dataset) - output_file = open("%s%s.txt" % (TMPDIR, pheno_filename), "wb") - header = 'FID\tIID\t%s\n' % this_trait.name + output_file = open(f"{TMPDIR}{pheno_filename}.txt", "wb") + header = f"FID\tIID\t{this_trait.name}\n" output_file.write(header) new_value_list = [] @@ -65,7 +65,7 @@ def gen_pheno_txt_file_plink(this_trait, dataset, vals, pheno_filename = ''): for i, sample in enumerate(ped_sample_list): j = i+1 value = new_value_list[i] - new_line += '%s\t%s\t%s\n'%(sample, sample, value) + new_line += f"{sample}\t{sample}\t{value}\n" if j%1000 == 0: output_file.write(newLine) @@ -78,7 +78,7 @@ def gen_pheno_txt_file_plink(this_trait, dataset, vals, pheno_filename = ''): # get strain name from ped file in order def get_samples_from_ped_file(dataset): - ped_file= open("{}{}.ped".format(flat_files('mapping'), dataset.group.name), "r") + ped_file= open(f"{flat_files('mapping')}{dataset.group.name}.ped","r") line = ped_file.readline() sample_list=[] @@ -98,7 +98,7 @@ def parse_plink_output(output_filename, species): threshold_p_value = 1 - result_fp = open("%s%s.qassoc"% (TMPDIR, output_filename), "rb") + result_fp = open(f"{TMPDIR}{output_filename}.qassoc","rb") line = result_fp.readline() @@ -154,7 +154,7 @@ def parse_plink_output(output_filename, species): # function: convert line from str to list; # output: lineList list ####################################################### -def build_line_list(line=None): +def build_line_list(line=""): line_list = line.strip().split(' ')# irregular number of whitespaces between columns line_list = [item for item in line_list if item !=''] line_list = [item.strip() for item in line_list] diff --git a/wqflask/wqflask/marker_regression/qtlreaper_mapping.py b/wqflask/wqflask/marker_regression/qtlreaper_mapping.py index 78b1f7b0..505ae295 100644 --- a/wqflask/wqflask/marker_regression/qtlreaper_mapping.py +++ b/wqflask/wqflask/marker_regression/qtlreaper_mapping.py @@ -17,22 +17,29 @@ def run_reaper(this_trait, this_dataset, samples, vals, json_data, num_perm, boo else: genofile_name = this_dataset.group.name - trait_filename = str(this_trait.name) + "_" + str(this_dataset.name) + "_pheno" + trait_filename =f"{str(this_trait.name)}_{str(this_dataset.name)}_pheno" gen_pheno_txt_file(samples, vals, trait_filename) - output_filename = this_dataset.group.name + "_GWA_" + ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(6)) + output_filename = (f"{this_dataset.group.name}_GWA_"+ + ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(6)) + ) bootstrap_filename = None permu_filename = None opt_list = [] if boot_check and num_bootstrap > 0: - bootstrap_filename = this_dataset.group.name + "_BOOTSTRAP_" + ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(6)) + bootstrap_filename = (f"{this_dataset.group.name}_BOOTSTRAP_" + + ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(6)) + ) opt_list.append("-b") - opt_list.append("--n_bootstrap " + str(num_bootstrap)) - opt_list.append("--bootstrap_output " + webqtlConfig.GENERATED_IMAGE_DIR + bootstrap_filename + ".txt") + opt_list.append(f"--n_bootstrap{str(num_bootstrap)}") + opt_list.append(f"--bootstrap_output{webqtlConfig.GENERATED_IMAGE_DIR}{bootstrap_filename}.txt") if num_perm > 0: - permu_filename = this_dataset.group.name + "_PERM_" + ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(6)) + permu_filename =("{this_dataset.group.name}_PERM_" + + ''.join(random.choice(string.ascii_uppercase + + string.digits) for _ in range(6)) + ) opt_list.append("-n " + str(num_perm)) opt_list.append("--permu_output " + webqtlConfig.GENERATED_IMAGE_DIR + permu_filename + ".txt") if control_marker != "" and do_control == "true": @@ -40,13 +47,15 @@ def run_reaper(this_trait, this_dataset, samples, vals, json_data, num_perm, boo if manhattan_plot != True: opt_list.append("--interval 1") - reaper_command = REAPER_COMMAND + ' --geno {0}/{1}.geno --traits {2}/gn2/{3}.txt {4} -o {5}{6}.txt'.format(flat_files('genotype'), - genofile_name, - TEMPDIR, - trait_filename, - " ".join(opt_list), - webqtlConfig.GENERATED_IMAGE_DIR, - output_filename) + reaper_command = (REAPER_COMMAND + + ' --geno {0}/{1}.geno --traits {2}/gn2/{3}.txt {4} -o {5}{6}.txt'.format(flat_files('genotype'), + + genofile_name, + TEMPDIR, + trait_filename, + " ".join(opt_list), + webqtlConfig.GENERATED_IMAGE_DIR, + output_filename)) logger.debug("reaper_command:" + reaper_command) os.system(reaper_command) @@ -61,12 +70,13 @@ def run_reaper(this_trait, this_dataset, samples, vals, json_data, num_perm, boo suggestive = permu_vals[int(num_perm*0.37-1)] significant = permu_vals[int(num_perm*0.95-1)] - return marker_obs, permu_vals, suggestive, significant, bootstrap_vals, [output_filename, permu_filename, bootstrap_filename] + return (marker_obs, permu_vals, suggestive, significant, bootstrap_vals, + [output_filename, permu_filename, bootstrap_filename]) def gen_pheno_txt_file(samples, vals, trait_filename): """Generates phenotype file for GEMMA""" - with open("{}/gn2/{}.txt".format(TEMPDIR, trait_filename), "w") as outfile: + with open(f"{TEMPDIR}/gn2/{trait_filename}.txt","w") as outfile: outfile.write("Trait\t") filtered_sample_list = [] @@ -90,7 +100,7 @@ def parse_reaper_output(gwa_filename, permu_filename, bootstrap_filename): only_cm = False only_mb = False - with open("{}{}.txt".format(webqtlConfig.GENERATED_IMAGE_DIR, gwa_filename)) as output_file: + with open(f"{webqtlConfig.GENERATED_IMAGE_DIR}{gwa_filename}.txt") as output_file: for line in output_file: if line.startswith("ID\t"): if len(line.split("\t")) < 8: @@ -137,13 +147,13 @@ def parse_reaper_output(gwa_filename, permu_filename, bootstrap_filename): permu_vals = [] if permu_filename: - with open("{}{}.txt".format(webqtlConfig.GENERATED_IMAGE_DIR, permu_filename)) as permu_file: + with open(f"{webqtlConfig.GENERATED_IMAGE_DIR}{permu_filename}.txt") as permu_file: for line in permu_file: permu_vals.append(float(line)) bootstrap_vals = [] if bootstrap_filename: - with open("{}{}.txt".format(webqtlConfig.GENERATED_IMAGE_DIR, bootstrap_filename)) as bootstrap_file: + with open(f"{webqtlConfig.GENERATED_IMAGE_DIR}{bootstrap_filename}.txt") as bootstrap_file: for line in bootstrap_file: bootstrap_vals.append(int(line)) diff --git a/wqflask/wqflask/marker_regression/run_mapping.py b/wqflask/wqflask/marker_regression/run_mapping.py index 31d6a67c..c474e0e0 100644 --- a/wqflask/wqflask/marker_regression/run_mapping.py +++ b/wqflask/wqflask/marker_regression/run_mapping.py @@ -138,7 +138,12 @@ class RunMapping(object): mapping_results_filename = self.dataset.group.name + "_" + ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(6)) self.mapping_results_path = "{}{}.csv".format(webqtlConfig.GENERATED_IMAGE_DIR, mapping_results_filename) - if start_vars['manhattan_plot'] == "true": + if start_vars['manhattan_plot']: + self.color_scheme = "alternating" + if "color_scheme" in start_vars: + self.color_scheme = start_vars['color_scheme'] + if self.color_scheme == "single": + self.manhattan_single_color = start_vars['manhattan_single_color'] self.manhattan_plot = True else: self.manhattan_plot = False diff --git a/wqflask/wqflask/static/images/edit.png b/wqflask/wqflask/static/images/edit.png Binary files differnew file mode 100644 index 00000000..571b08cd --- /dev/null +++ b/wqflask/wqflask/static/images/edit.png diff --git a/wqflask/wqflask/static/new/css/markdown.css b/wqflask/wqflask/static/new/css/markdown.css index 91167908..dca3e31d 100644 --- a/wqflask/wqflask/static/new/css/markdown.css +++ b/wqflask/wqflask/static/new/css/markdown.css @@ -2,7 +2,10 @@ padding: 20px; } -#markdown h2, #markdown h3, #markdown h4, #markdown h5 { +#markdown h2, +#markdown h3, +#markdown h4, +#markdown h5 { font-weight: bold; } @@ -11,3 +14,51 @@ margin-right: auto; margin-left: auto; } + +.github-btn-container { + margin: 20px 10px; + display: flex; + width: 90vw; + justify-content: flex-end; +} + +.github-btn { + display: flex; + justify-content: center; + border: 3px solid #357ebd; + background: lightgrey; + padding: 3px 4px; + width: 200px; + border-radius: 16px; +} + +.github-btn a { + align-self: center; + font-weight: bold; + color: #357ebd; +} + +.github-btn a img { + height: 40px; + width: 40px; + padding-left:5px; +} + + +.container { + width: 80vw; + margin: auto; + max-width: 80vw; + +} + +.container p { + font-size: 17px; + word-spacing: 0.2em; +} + +@media(max-width:650px) { + .container { + width: 100vw; + } +}
\ No newline at end of file diff --git a/wqflask/wqflask/static/new/css/show_trait.css b/wqflask/wqflask/static/new/css/show_trait.css index 5e1a279b..39c6ba53 100644 --- a/wqflask/wqflask/static/new/css/show_trait.css +++ b/wqflask/wqflask/static/new/css/show_trait.css @@ -145,11 +145,11 @@ input.corr-location { display: inline; } -div.block-by-index-div { +div.block-div { margin-bottom: 10px; } -div.block-by-attribute-div { +div.block-div-2 { margin-top:10px; margin-bottom:10px; } diff --git a/wqflask/wqflask/static/new/css/trait_list.css b/wqflask/wqflask/static/new/css/trait_list.css index 691dcb12..b83655da 100644 --- a/wqflask/wqflask/static/new/css/trait_list.css +++ b/wqflask/wqflask/static/new/css/trait_list.css @@ -1,12 +1,20 @@ -div.tool-button-container {
- min-width: 950px;
-}
-
-div.collection-table-options {
- min-width: 1100px;
-}
-
-div.show-hide-container {
- margin-bottom: 5px;
- margin-top: 10px;
-}
\ No newline at end of file +div.tool-button-container { + min-width: 950px; +} + +div.collection-table-options { + min-width: 1100px; +} + +div.show-hide-container { + margin-bottom: 5px; + margin-top: 10px; +} + +button.active { + background: #e5e5e5; + -webkit-box-shadow: inset 0px 0px 5px #c1c1c1; + -moz-box-shadow: inset 0px 0px 5px #c1c1c1; + box-shadow: inset 0px 0px 5px #c1c1c1; + outline: none; + }
\ No newline at end of file diff --git a/wqflask/wqflask/static/new/javascript/show_trait.js b/wqflask/wqflask/static/new/javascript/show_trait.js index a34811f8..87c35984 100644 --- a/wqflask/wqflask/static/new/javascript/show_trait.js +++ b/wqflask/wqflask/static/new/javascript/show_trait.js @@ -568,14 +568,29 @@ create_value_dropdown = function(value) { populate_sample_attributes_values_dropdown = function() { var attribute_info, key, sample_attributes, selected_attribute, value, _i, _len, _ref, _ref1, _results; $('#attribute_values').empty(); - sample_attributes = {}; - attr_keys = Object.keys(js_data.attributes).sort(); - for (i=0; i < attr_keys.length; i++) { - attribute_info = js_data.attributes[attr_keys[i]]; - sample_attributes[attribute_info.name] = attribute_info.distinct_values; - } - selected_attribute = $('#exclude_menu').val().replace("_", " "); - _ref1 = sample_attributes[selected_attribute]; + sample_attributes = []; + + var attributes_as_list = Object.keys(js_data.attributes).map(function(key) { + return [key, js_data.attributes[key].name]; + }); + + attributes_as_list.sort(function(first, second) { + if (second[1] > first[1]){ + return -1 + } + if (first[1] > second[1]){ + return 1 + } + return 0 + }); + + for (i=0; i < attributes_as_list.length; i++) { + attribute_info = js_data.attributes[attributes_as_list[i][0]] + sample_attributes.push(attribute_info.distinct_values); + } + + selected_attribute = $('#exclude_column').val() + _ref1 = sample_attributes[selected_attribute - 1]; _results = []; for (_i = 0, _len = _ref1.length; _i < _len; _i++) { value = _ref1[_i]; @@ -590,25 +605,37 @@ if (Object.keys(js_data.attributes).length){ populate_sample_attributes_values_dropdown(); } -$('#exclude_menu').change(populate_sample_attributes_values_dropdown); +$('#exclude_column').change(populate_sample_attributes_values_dropdown); block_by_attribute_value = function() { var attribute_name, cell_class, exclude_by_value; - attribute_name = $('#exclude_menu').val(); + + let exclude_group = $('#exclude_by_attr_group').val(); + let exclude_column = $('#exclude_column').val(); + + if (exclude_group === "other") { + var table_api = $('#samples_other').DataTable(); + } else { + var table_api = $('#samples_primary').DataTable(); + } + exclude_by_value = $('#attribute_values').val(); - cell_class = ".column_name-" + attribute_name; - return $(cell_class).each((function(_this) { - return function(index, element) { - var row; - if ($.trim($(element).text()) === exclude_by_value) { - row = $(element).parent('tr'); - return $(row).find(".trait-value-input").val("x"); - } - }; - })(this)); + + let val_nodes = table_api.column(3).nodes().to$(); + let exclude_val_nodes = table_api.column(attribute_start_pos + parseInt(exclude_column)).nodes().to$(); + + for (i = 0; i < exclude_val_nodes.length; i++) { + let this_col_value = exclude_val_nodes[i].childNodes[0].data; + let this_val_node = val_nodes[i].childNodes[0]; + + if (this_col_value == exclude_by_value){ + this_val_node.value = "x"; + } + } }; -$('#exclude_group').click(block_by_attribute_value); +$('#exclude_by_attr').click(block_by_attribute_value); + block_by_index = function() { - var end_index, error, index, index_list, index_set, index_string, start_index, _i, _j, _k, _len, _len1, _ref, _results; + var end_index, error, index, index_list, index_set, index_string, start_index, _i, _j, _k, _len, _len1, _ref; index_string = $('#remove_samples_field').val(); index_list = []; _ref = index_string.split(","); @@ -630,7 +657,7 @@ block_by_index = function() { index_list.push(index); } } - _results = []; + let block_group = $('#block_group').val(); if (block_group === "other") { table_api = $('#samples_other').DataTable(); @@ -645,6 +672,65 @@ block_by_index = function() { } }; +filter_by_value = function() { + let filter_logic = $('#filter_logic').val(); + let filter_column = $('#filter_column').val(); + let filter_value = $('#filter_value').val(); + let block_group = $('#filter_group').val(); + + if (block_group === "other") { + var table_api = $('#samples_other').DataTable(); + } else { + var table_api = $('#samples_primary').DataTable(); + } + + let val_nodes = table_api.column(3).nodes().to$(); + if (filter_column == "value"){ + var filter_val_nodes = table_api.column(3).nodes().to$(); + } + else if (filter_column == "stderr"){ + var filter_val_nodes = table_api.column(5).nodes().to$(); + } + else if (!isNaN(filter_column)){ + var filter_val_nodes = table_api.column(attribute_start_pos + parseInt(filter_column)).nodes().to$(); + } + else { + return false + } + + for (i = 0; i < filter_val_nodes.length; i++) { + if (filter_column == "value" || filter_column == "stderr"){ + var this_col_value = filter_val_nodes[i].childNodes[0].value; + } else { + var this_col_value = filter_val_nodes[i].childNodes[0].data; + } + let this_val_node = val_nodes[i].childNodes[0]; + + if(!isNaN(this_col_value) && !isNaN(filter_value)) { + if (filter_logic == "greater_than"){ + if (parseFloat(this_col_value) <= parseFloat(filter_value)){ + this_val_node.value = "x"; + } + } + else if (filter_logic == "less_than"){ + if (parseFloat(this_col_value) >= parseFloat(filter_value)){ + this_val_node.value = "x"; + } + } + else if (filter_logic == "greater_or_equal"){ + if (parseFloat(this_col_value) < parseFloat(filter_value)){ + this_val_node.value = "x"; + } + } + else if (filter_logic == "less_or_equal"){ + if (parseFloat(this_col_value) > parseFloat(filter_value)){ + this_val_node.value = "x"; + } + } + } + } +}; + hide_no_value = function() { return $('.value_se').each((function(_this) { return function(_index, element) { @@ -1528,6 +1614,12 @@ $('#block_by_index').click(function(){ block_by_index(); edit_data_change(); }); + +$('#filter_by_value').click(function(){ + filter_by_value(); + edit_data_change(); +}) + $('#exclude_group').click(edit_data_change); $('#block_outliers').click(edit_data_change); $('#reset').click(edit_data_change); diff --git a/wqflask/wqflask/templates/base.html b/wqflask/wqflask/templates/base.html index 0e572fcf..faa59deb 100644 --- a/wqflask/wqflask/templates/base.html +++ b/wqflask/wqflask/templates/base.html @@ -64,13 +64,14 @@ <li class=""> <a href="/help" class="dropdow-toggle" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">Help <span class="caret"></a> <ul class="dropdown-menu"> - <li><a href="/references">References</a></li> + <li><a href="{{ url_for('references_blueprint.references') }}">References</a></li> <li><a href="/tutorials">Tutorials/Primers</a></li> <li><a href="{{ url_for('glossary_blueprint.glossary') }}">Glossary of Term</a></li> <li><a href="http://gn1.genenetwork.org/faq.html">FAQ</a></li> - <li><a href="/policies">Policies</a></li> - <li><a href="/links">Links</a></li> - <li><a href="/environments">Environments</a></li> + <li><a href="{{ url_for('policies_blueprint.policies') }}">Policies</a></li> + <li><a href="{{ url_for('links_blueprint.links') }}">Links</a></li> + <li><a href="{{ url_for('facilities_blueprint.facilities') }}">Facilities</a></li> + <li><a href="{{ url_for('environments_blueprint.environments') }}">Environments</a></li> <li><a href="/news">GN1 News</a></li> </ul> </li> diff --git a/wqflask/wqflask/templates/correlation_page.html b/wqflask/wqflask/templates/correlation_page.html index bc0b592c..6419b185 100644 --- a/wqflask/wqflask/templates/correlation_page.html +++ b/wqflask/wqflask/templates/correlation_page.html @@ -2,9 +2,11 @@ {% block title %}Correlation Results{% endblock %} {% block css %} <link rel="stylesheet" type="text/css" href="{{ url_for('css', filename='DataTables/css/jquery.dataTables.css') }}" /> - <link rel="stylesheet" type="text/css" href="/static/new/css/show_trait.css" /> <link rel="stylesheet" type="text/css" href="{{ url_for('js', filename='DataTablesExtensions/buttonsBootstrap/css/buttons.bootstrap.css') }}" /> <link rel="stylesheet" type="text/css" href="{{ url_for('js', filename='DataTablesExtensions/buttonStyles/css/buttons.dataTables.min.css') }}"> + <link rel="stylesheet" type="text/css" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.1/css/all.min.css"> + <link rel="stylesheet" type="text/css" href="/static/new/css/trait_list.css" /> + <link rel="stylesheet" type="text/css" href="/static/new/css/show_trait.css" /> {% endblock %} {% block content %} <div class="container" style="min-width: 1250px;"> @@ -112,10 +114,38 @@ </div> {% endif %} </div> - <div style="margin-bottom: 5px;"> - <b>Show/Hide Columns:</b> + <div class="show-hide-container"> + <b>Show/Hide Columns:</b> + <br> + <button class="toggle-vis" data-column="1">Index</button> + <button class="toggle-vis" data-column="2">Record</button> + {% if target_dataset.type == 'ProbeSet' %} + <button class="toggle-vis" data-column="3">Symbol</button> + <button class="toggle-vis" data-column="4">Description</button> + <button class="toggle-vis" data-column="5">Location</button> + <button class="toggle-vis" data-column="6">Mean</button> + <button class="toggle-vis" data-column="7">High P</button> + <button class="toggle-vis" data-column="8">Peak Location</button> + <button class="toggle-vis" data-column="9">Effect Size</button> + {% elif target_dataset.type == 'Publish' %} + <button class="toggle-vis" data-column="3">Abbreviation</button> + <button class="toggle-vis" data-column="4">Description</button> + <button class="toggle-vis" data-column="5">Authors</button> + <button class="toggle-vis" data-column="6">Year</button> + <button class="toggle-vis" data-column="7">Sample {% if corr_method == 'pearson' %}r{% else %}rho{% endif %}</button> + <button class="toggle-vis" data-column="8">N</button> + <button class="toggle-vis" data-column="9">Sample p({% if corr_method == 'pearson' %}r{% else %}rho{% endif %})</button> + <button class="toggle-vis" data-column="10">High P</button> + <button class="toggle-vis" data-column="11">Peak Location</button> + <button class="toggle-vis" data-column="12">Effect Size</button> + {% else %} + <button class="toggle-vis" data-column="3">Location</button> + <button class="toggle-vis" data-column="4">Sample {% if corr_method == 'pearson' %}r{% else %}rho{% endif %}</button> + <button class="toggle-vis" data-column="5">N</button> + <button class="toggle-vis" data-column="6">Sample p({% if corr_method == 'pearson' %}r{% else %}rho{% endif %})</button> + {% endif %} </div> - <div style="width: 100%; min-width: {% if target_dataset.type == "ProbeSet" %}1700px{% elif target_dataset.type == "Publish" %}1600px{% else %}600px{% endif %};"> + <div style="width: 100%; {% if target_dataset.type == "ProbeSet" %}min-width: 1700px;{% elif target_dataset.type == "Publish" %}min-width: 1600px;{% else %}width: 650px;{% endif %}"> <table id="trait_table" class="table-hover table-striped cell-border" style="float: left;"> <thead> <tr> @@ -127,77 +157,7 @@ </thead> <tbody> - {% for trait in correlation_results %} - <tr> - <td><INPUT TYPE="checkbox" NAME="searchResult" class="checkbox trait_checkbox" style="padding-right: 0px;" VALUE="{{ data_hmac('{}:{}'.format(trait.name, trait.dataset.name)) }}"></td> - <td data-export="{{ loop.index }}" style="padding-left: 8px; padding-right: 0px; padding-top: 4px; align: right;">{{ loop.index }}</td> - <td data-export="{{ trait.name }}"> - <a href="{{ url_for('show_trait_page', - trait_id = trait.name, - dataset = trait.dataset.name - )}}"> - {{ trait.name }} - </a> - </td> - {% if target_dataset.type == 'ProbeSet' %} - <td data-export="{{ trait.symbol }}">{{ trait.symbol }}</td> - <td data-export="{{ trait.description_display }}">{{ trait.description_display }}</TD> - <td data-export="{{ trait.location_repr }}" style="white-space: nowrap;">{{ trait.location_repr }}</td> - <td data-export="{{ '%0.3f' % trait.mean|float }}" align="right">{{ '%0.3f' % trait.mean|float }}</td> - <td data-export="{{ '%0.3f'|format(trait.sample_r) }}"" align="right"><a target="_blank" href="corr_scatter_plot?dataset_1={% if dataset.name == 'Temp' %}Temp_{{ dataset.group.name }}{% else %}{{ dataset.name }}{% endif %}&dataset_2={% if trait.dataset.name == 'Temp' %}Temp_{{ trait.dataset.group.name }}{% else %}{{ trait.dataset.name }}{% endif %}&trait_1={{ this_trait.name }}&trait_2={{ trait.name }}">{{ '%0.3f'|format(trait.sample_r) }}</a></td> - <td data-export="{{ trait.num_overlap }}" align="right">{{ trait.num_overlap }}</td> - <td data-export="{{ '%0.3e'|format(trait.sample_p) }}" align="right">{{ '%0.3e'|format(trait.sample_p) }}</td> - {% if trait.lit_corr == "" or trait.lit_corr == 0.000 %} - <td data-export="--" align="right">--</td> - {% else %} - <td data-export="{{ '%0.3f'|format(trait.lit_corr) }}" align="right">{{ '%0.3f'|format(trait.lit_corr) }}</td> - {% endif %} - {% if trait.tissue_corr == "" or trait.tissue_corr == 0.000 %} - <td data-export="--" align="right">--</td> - <td data-export="--" align="right">--</td> - {% else %} - <td data-export="{{ '%0.3f'|format(trait.tissue_corr) }}" align="right">{{ '%0.3f'|format(trait.tissue_corr) }}</td> - <td data-export="{{ '%0.3e'|format(trait.tissue_pvalue) }}" align="right">{{ '%0.3e'|format(trait.tissue_pvalue) }}</td> - {% endif %} - <td data-export={% if trait.LRS_score_repr != "N/A" %}"{{ '%0.1f' % trait.LRS_score_repr|float }}"{% else %}"N/A"{% endif %} align="right">{% if trait.LRS_score_repr != "N/A" %}{{ '%0.1f' % trait.LRS_score_repr|float }}{% else %}N/A{% endif %}</td> - <td data-export="{{ trait.LRS_location_repr }}" align="right">{{ trait.LRS_location_repr }}</td> - <td data-export={% if trait.additive != "" %}"{{ '%0.3f' % trait.additive|float }}"{% else %}"N/A"{% endif %} align="right">{% if trait.additive != "" %}{{ '%0.3f' % trait.additive|float }}{% else %}N/A{% endif %}</td> - {% elif target_dataset.type == "Publish" %} - {% if trait.abbreviation %} - <td title="{{ trait.abbreviation }}" data-export="{{ trait.abbreviation }}">{% if trait.abbreviation|length > 20 %}{{ trait.abbreviation[:20] }}...{% else %}{{ trait.abbreviation }}{% endif %}</td> - {% else %} - <td data-export="N/A">N/A</td> - {% endif %} - <td data-export="{{ trait.description_display }}">{% if trait.description_display|length > 70 %}{{ trait.description_display[:70] }}...{% else %}{{ trait.description_display }}{% endif %}</td> - {% if trait.authors %} - {% set authors_list = trait.authors.split(',') %} - <td data-export="{{ trait.authors }}">{% if authors_list|length > 6 %}{{ authors_list[:6]|join(', ') }}, et al.{% else %}{{ trait.authors }}{% endif %}</td> - {% else %} - <td data-export="N/A">N/A</td> - {% endif %} - <td data-export="{{ trait.pubmed_text }}"> - {% if trait.pubmed_text != "N/A" %} - <a href="{{ trait.pubmed_link }}"> - {{ trait.pubmed_text }} - </a> - {% else %} - {{ trait.pubmed_text }} - {% endif %} - </td> - <td data-export="{{ '%0.3f'|format(trait.sample_r) }}"" align="right"><a target="_blank" href="corr_scatter_plot?dataset_1={% if dataset.name == 'Temp' %}Temp_{{ dataset.group.name }}{% else %}{{ dataset.name }}{% endif %}&dataset_2={{ trait.dataset.name }}&trait_1={{ this_trait.name }}&trait_2={{ trait.name }}">{{ '%0.3f'|format(trait.sample_r) }}</a></td> - <td data-export="{{ trait.num_overlap }}" align="right">{{ trait.num_overlap }}</td> - <td data-export="{{ '%0.3e'|format(trait.sample_p) }}" align="right">{{ '%0.3e'|format(trait.sample_p) }}</td> - <td data-export="{{ trait.LRS_score_repr }}" align="right">{{ trait.LRS_score_repr }}</td> - <td data-export="{{ trait.LRS_location_repr }}" align="right">{{ trait.LRS_location_repr }}</td> - <td data-export={% if trait.additive != "" %}"{{ '%0.3f' % trait.additive|float }}"{% else %}"N/A"{% endif %} align="right">{% if trait.additive != "" %}{{ '%0.3f' % trait.additive|float }}{% else %}N/A{% endif %}</td> - {% elif target_dataset.type == "Geno" %} - <td data-export="{{ trait.location_repr }}" align="right">{{ trait.location_repr }}</TD> - <td data-export="{{ '%0.3f'|format(trait.sample_r) }}"" align="right"><a target="_blank" href="corr_scatter_plot?dataset_1={% if dataset.name == 'Temp' %}Temp_{{ dataset.group.name }}{% else %}{{ dataset.name }}{% endif %}&dataset_2={{ trait.dataset.name }}&trait_1={{ this_trait.name }}&trait_2={{ trait.name }}">{{ '%0.3f'|format(trait.sample_r) }}</a></td> - <td data-export="{{ trait.num_overlap }}" align="right">{{ trait.num_overlap }}</td> - <td data-export="{{ '%0.3e'|format(trait.sample_p) }}" align="right">{{ '%0.3e'|format(trait.sample_p) }}</td> - {% endif %} - </tr> - {% endfor %} + <td colspan="100%" align="center"><br><b><font size="15">Loading...</font></b><br></td> </tbody> </table> </div> @@ -215,6 +175,8 @@ <script language="javascript" type="text/javascript" src="{{ url_for('js', filename='DataTablesExtensions/buttons/js/dataTables.buttons.min.js') }}"></script> <script language="javascript" type="text/javascript" src="{{ url_for('js', filename='DataTablesExtensions/buttons/js/buttons.colVis.min.js') }}"></script> <script language="javascript" type="text/javascript" src="{{ url_for('js', filename='DataTablesExtensions/plugins/sorting/natural.js') }}"></script> + <script language="javascript" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.1/js/all.min.js"></script> + <script language="javascript" type="text/javascript" src="https://cdn.datatables.net/scroller/2.0.2/js/dataTables.scroller.min.js"></script> <script type="text/javascript" charset="utf-8"> var table_json = {{ json_results | safe }} @@ -329,16 +291,7 @@ console.time("Creating table"); - {% if target_dataset.type == "ProbeSet" %} table_conf = { - "drawCallback": function( settings ) { - $('#trait_table tr').click(function(event) { - if (event.target.type !== 'checkbox') { - $(':checkbox', this).trigger('click'); - } - }); - $('.trait_checkbox:checkbox').on("change", change_buttons); - }, buttons: [ { extend: 'columnsToggle', @@ -352,136 +305,295 @@ postfixButtons: [ 'colvisRestore' ] } ], + "data": table_json, + "columns": [ + { + 'data': null, + 'width': "25px", + 'orderDataType': "dom-checkbox", + 'orderSequence': [ "desc", "asc"], + 'render': function(data, type, row, meta) { + return '<input type="checkbox" name="searchResult" class="checkbox trait_checkbox" value="' + data.hmac + '">' + } + }, + { + 'title': "Index", + 'type': "natural", + 'width': "30px", + 'data': "index" + }, + { + 'title': "Record", + 'type': "natural-minus-na", + 'data': null, + 'width': "60px", + 'render': function(data, type, row, meta) { + return '<a target="_blank" href="/show_trait?trait_id=' + data.trait_id + '&dataset=' + data.dataset + '">' + data.trait_id + '</a>' + } + }{% if target_dataset.type == 'ProbeSet' %}, + { + 'title': "Symbol", + 'type': "natural", + 'width': "120px", + 'data': "symbol" + }, + { + 'title': "Description", + 'type': "natural", + 'data': null, + 'render': function(data, type, row, meta) { + try { + return decodeURIComponent(escape(data.description)) + } catch(err){ + return escape(data.description) + } + } + }, + { + 'title': "Location", + 'type': "natural-minus-na", + 'width': "125px", + 'data': "location" + }, + { + 'title': "Mean", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "mean", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Sample {% if corr_method == 'pearson' %}r{% else %}rho{% endif %}", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "sample_r", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "N", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "num_overlap", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Sample p({% if corr_method == 'pearson' %}r{% else %}rho{% endif %})", + 'type': "natural-minus-na", + 'width': "65px", + 'data': "sample_p", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Lit {% if corr_method == 'pearson' %}r{% else %}rho{% endif %}", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "lit_corr", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Tissue {% if corr_method == 'pearson' %}r{% else %}rho{% endif %}", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "tissue_corr", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Tissue p({% if corr_method == 'pearson' %}r{% else %}rho{% endif %})", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "tissue_pvalue", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "High P<a href=\"http://gn1.genenetwork.org/glossary.html#LRS\" target=\"_blank\" style=\"color: white;\"> <i class=\"fa fa-info-circle\" aria-hidden=\"true\"></i></a>", + 'type': "natural-minus-na", + 'data': "lrs_score", + 'width': "60px", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Peak Location", + 'type': "natural-minus-na", + 'width': "125px", + 'data': "lrs_location" + }, + { + 'title': "Effect Size<a href=\"http://gn1.genenetwork.org/glossary.html#A\" target=\"_blank\" style=\"color: white;\"> <i class=\"fa fa-info-circle\" aria-hidden=\"true\"></i></a>", + 'type': "natural-minus-na", + 'data': "additive", + 'width': "85px", + 'orderSequence': [ "desc", "asc"] + }{% elif target_dataset.type == 'Publish' %}, + { + 'title': "Abbreviation", + 'type': "natural", + 'width': "200px", + 'data': null, + 'render': function(data, type, row, meta) { + try { + return decodeURIComponent(escape(data.abbreviation_display)) + } catch(err){ + return data.abbreviation_display + } + } + }, + { + 'title': "Description", + 'type': "natural", + 'data': null, + 'render': function(data, type, row, meta) { + try { + return decodeURIComponent(escape(data.description)) + } catch(err){ + return data.description + } + } + }, + { + 'title': "Authors", + 'type': "natural", + 'width': "400px", + 'data': null, + 'render': function(data, type, row, meta) { + try { + return decodeURIComponent(escape(data.authors_display)) + } catch(err){ + return data.authors_display + } + } + }, + { + 'title': "Year", + 'type': "natural-minus-na", + 'data': null, + 'width': "80px", + 'render': function(data, type, row, meta) { + if (data.pubmed_id != "N/A"){ + return '<a href="' + data.pubmed_link + '">' + data.pubmed_text + '</a>' + } else { + return data.pubmed_text + } + }, + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Sample {% if corr_method == 'pearson' %}r{% else %}rho{% endif %}", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "sample_r", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "N", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "num_overlap", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Sample p({% if corr_method == 'pearson' %}r{% else %}rho{% endif %})", + 'type': "natural-minus-na", + 'width': "65px", + 'data': "sample_p", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "High P<a href=\"http://gn1.genenetwork.org/glossary.html#LRS\" target=\"_blank\" style=\"color: white;\"> <i class=\"fa fa-info-circle\" aria-hidden=\"true\"></i></a>", + 'type': "natural-minus-na", + 'data': "lrs_score", + 'width': "60px", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Peak Location", + 'type': "natural-minus-na", + 'width': "125px", + 'data': "lrs_location" + }, + { + 'title': "Effect Size<a href=\"http://gn1.genenetwork.org/glossary.html#A\" target=\"_blank\" style=\"color: white;\"> <i class=\"fa fa-info-circle\" aria-hidden=\"true\"></i></a>", + 'type': "natural-minus-na", + 'data': "additive", + 'width': "85px", + 'orderSequence': [ "desc", "asc"] + }{% elif target_dataset.type == 'Geno' %}, + { + 'title': "Location", + 'type': "natural-minus-na", + 'width': "120px", + 'data': "location" + }, + { + 'title': "Sample {% if corr_method == 'pearson' %}r{% else %}rho{% endif %}", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "sample_r", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "N", + 'type': "natural-minus-na", + 'width': "40px", + 'data': "num_overlap", + 'orderSequence': [ "desc", "asc"] + }, + { + 'title': "Sample p({% if corr_method == 'pearson' %}r{% else %}rho{% endif %})", + 'type': "natural-minus-na", + 'width': "65px", + 'data': "sample_p", + 'orderSequence': [ "desc", "asc"] + }{% endif %} + ], "columnDefs": [ { "targets": 0, "orderable": false } ], - "columns": [ - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural", "width": "15%" }, - { "type": "natural" }, - { "type": "natural" }, - { "orderDataType": "dom-innertext", 'orderSequence': [ "desc", "asc"] }, - { "type": "natural" }, - { "type": "scientific" }, - { "type": "natural-minus-na", 'orderSequence': [ "desc", "asc"] }, - { "type": "natural-minus-na", 'orderSequence': [ "desc", "asc"] }, - { "type": "scientific" }, - { "type": "natural-minus-na" }, - { "type": "natural-minus-na" }, - { "type": "natural-minus-na" } - ], - "createdRow": function ( row, data, index ) { - $('td', row).eq(4).attr('title', $('td', row).eq(4).text()); - if ($('td', row).eq(4).text().length > 40) { - $('td', row).eq(4).text($('td', row).eq(4).text().substring(0, 40)); - $('td', row).eq(4).text($('td', row).eq(4).text() + '...') - } - }, + {% if target_dataset.type == 'Geno' %} + "order": [[6, "asc" ]], + {% else %} "order": [[9, "asc" ]], - "sDom": "Btir", - "iDisplayLength": -1, - "autoWidth": false, - "deferRender": true, + {% endif %} + "sDom": "itir", + "autoWidth": true, "bSortClasses": false, - "paging": false, - "orderClasses": true + "scrollY": "50vh", + "scroller": true, + "scrollCollapse": true } - {% elif target_dataset.type == "Publish" %} - table_conf = { - "drawCallback": function( settings ) { - $('#trait_table tr').click(function(event) { - if (event.target.type !== 'checkbox') { - $(':checkbox', this).trigger('click'); - } - }); - $('.trait_checkbox:checkbox').on("change", change_buttons); - }, - "buttons": [ - { - extend: 'columnsToggle', - columns: function( idx, data, node ) { - if (idx != 0) { - return true; - } else { - return false; - } - }, - postfixButtons: [ 'colvisRestore' ] - } - ], - "columnDefs": [ - { "targets": 0, "orderable": false } - ], - "columns": [ - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural", "width": "20%" }, - { "type": "natural", "width": "12%" }, - { "type": "natural-minus-na" }, - { "orderDataType": "dom-innertext", 'orderSequence': [ "desc", "asc"] }, - { "type": "natural" }, - { "type": "scientific" }, - { "type": "natural-minus-na" }, - { "type": "natural-minus-na" }, - { "type": "natural-minus-na" } - ], - "order": [[9, "asc" ]], - "sDom": "Btir", - "iDisplayLength": -1, - "autoWidth": false, - "deferRender": true, - "bSortClasses": false, - "paging": false, - "orderClasses": true, - } - {% elif target_dataset.type == "Geno" %} - table_conf = { - "paging": false, - buttons: [ - { - extend: 'columnsToggle', - columns: function( idx, data, node ) { - if (idx != 0) { - return true; - } else { - return false; - } - }, - postfixButtons: [ 'colvisRestore' ] - } - ], - "columnDefs": [ - { "targets": 0, "orderable": false } - ], - "columns": [ - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural" }, - { "type": "natural" }, - { "orderDataType": "dom-innertext", 'orderSequence': [ "desc", "asc"] }, - { "type": "natural-minus-na" }, - { "type": "scientific" } - ], - "order": [[6, "asc" ]], - "sDom": "Btir", - "autoWidth": false, - "bDeferRender": true, - "scrollY": "800px", - "scrollCollapse": false - } - {% endif %} + trait_table = $('#trait_table').DataTable(table_conf); - the_table = $('#trait_table').DataTable(table_conf); + trait_table.on( 'order.dt search.dt draw.dt', function () { + trait_table.column(1, {search:'applied', order:'applied'}).nodes().each( function (cell, i) { + cell.innerHTML = i+1; + } ); + } ).draw(); console.timeEnd("Creating table"); + $('.toggle-vis').on('click', function (e) { + e.preventDefault(); + + // Get the column API object + var column = trait_table.column( $(this).attr('data-column') ); + + // Toggle the visibility + column.visible( ! column.visible() ); + + if (column.visible()){ + $(this).removeClass("active"); + } else { + $(this).addClass("active"); + } + } ); + + $('#redraw').on('click', function (e) { + e.preventDefault(); + trait_table.columns().visible( true ); + $('.toggle-vis.active').removeClass('active'); + }); + submit_special = function(url) { $("#correlation_form").attr("action", url); return $("#correlation_form").submit(); @@ -498,7 +610,7 @@ $("#select_traits").click(function() { console.log("redrawing") - the_table.draw(); + trait_table.draw(); }); }); </script> diff --git a/wqflask/wqflask/templates/environment.html b/wqflask/wqflask/templates/environment.html new file mode 100644 index 00000000..94b31464 --- /dev/null +++ b/wqflask/wqflask/templates/environment.html @@ -0,0 +1,40 @@ +{% extends "base.html" %} + +{% block title %}Glossary{% endblock %} + +{% block css %} +<link rel="stylesheet" type="text/css" href="/static/new/css/markdown.css" /> +{% endblock %} + +{% block content %} + + <div class="github-btn-container"> + <div class="github-btn "> + <a href="https://github.com/genenetwork/gn-docs"> + Edit Text + <img src="/static/images/edit.png"> + </a> + </div> +</div> +<div id="markdown" class="container"> + + <div class="cls-table-style">{{ rendered_markdown|safe }} </div> +</div> + +<style type="text/css"> +table { + width: 100%; +} +table, th, td { + border: 1px solid black; + +} + +td,th{ + padding-top:8px; + padding-bottom: 8px; + text-align: center; +} + +</style> +{% endblock %} diff --git a/wqflask/wqflask/templates/environments.html b/wqflask/wqflask/templates/environments.html deleted file mode 100644 index 5ef91a95..00000000 --- a/wqflask/wqflask/templates/environments.html +++ /dev/null @@ -1,83 +0,0 @@ -{% extends "base.html" %} - -{% block title %}Environments{% endblock %} - -{% block content %} -<div class="container"> - <h3>System Properties</h3> - <table class="table table-bordered table-striped table-hover" style="width: 800px;"> - <tbody> - <tr><td colspan="4">Operating System</td></tr> - <tr> - <td style="text-align: right;">Ubuntu</td> - <td>12.04.5 LTS 64-bit</td> - <td><a target="_blank" href="http://www.ubuntu.com/">http://www.ubuntu.com/</a></td> - <td>Free software licenses (mainly GPL)</td> - </tr> - <tr><td colspan="4">Database</td></tr> - <tr> - <td style="text-align: right;">MySQL</td> - <td>5.5.40</td> - <td><a target="_blank" href="http://www.mysql.com/">http://www.mysql.com/</a></td> - <td>GPL (version 2) or proprietary</td> - </tr> - <tr><td colspan="4">Python</td></tr> - <tr> - <td style="text-align: right;">Python</td> - <td>2.7.3</td> - <td><a target="_blank" href="http://www.python.org/">http://www.python.org/</a></td> - <td>Python Software Foundation License</td> - </tr> - <tr> - <td style="text-align: right;">Flask</td> - <td>0.9</td> - <td><a target="_blank" href="http://flask.pocoo.org/">http://flask.pocoo.org/</a></td> - <td>BSD</td> - </tr> - <tr> - <td style="text-align: right;">Jinja2</td> - <td>2.6</td> - <td><a target="_blank" href="http://jinja.pocoo.org/">http://jinja.pocoo.org/</a></td> - <td>BSD</td> - </tr> - <tr> - <td style="text-align: right;">NumPy</td> - <td>1.7.0</td> - <td><a target="_blank" href="http://www.numpy.org/">http://www.numpy.org/</a></td> - <td>BSD-new</td> - </tr> - <tr> - <td style="text-align: right;">SciPy</td> - <td>0.11.0</td> - <td><a target="_blank" href="http://www.scipy.org/">http://www.scipy.org/</a></td> - <td>BSD-new</td> - </tr> - <tr><td colspan="4">JavaScript / CSS</td></tr> - <tr> - <td style="text-align: right;">jQuery</td> - <td>1.10.2</td> - <td><a target="_blank" href="http://jquery.com/">http://jquery.com/</a></td> - <td>MIT</td> - </tr> - <tr> - <td style="text-align: right;">Bootstrap</td> - <td>2.3.1</td> - <td><a target="_blank" href="http://getbootstrap.com/">http://getbootstrap.com/</a></td> - <td>MIT License (Apache License 2.0 prior to 3.1.0)</td> - </tr> - <tr> - <td style="text-align: right;">DataTables</td> - <td>1.9.4</td> - <td><a target="_blank" href="http://www.datatables.net/">http://www.datatables.net/</a></td> - <td>MIT</td> - </tr> - <tr> - <td style="text-align: right;">CKEditor</td> - <td>4.4.5</td> - <td><a target="_blank" href="http://ckeditor.com/">http://ckeditor.com/</a></td> - <td>GPL, LGPL and MPL</td> - </tr> - </tbody> - </table> -</div> -{% endblock %} diff --git a/wqflask/wqflask/templates/facilities.html b/wqflask/wqflask/templates/facilities.html new file mode 100644 index 00000000..a022b657 --- /dev/null +++ b/wqflask/wqflask/templates/facilities.html @@ -0,0 +1,24 @@ +{% extends "base.html" %} + +{% block title %}Facilities{% endblock %} + +{% block css %} +<link rel="stylesheet" type="text/css" href="/static/new/css/markdown.css" /> +{% endblock %} + +{% block content %} + + <div class="github-btn-container"> + <div class="github-btn"> + <a href="https://github.com/genenetwork/gn-docs"> + Edit Text + <img src="/static/images/edit.png"> + </a> + </div> +</div> +<div id="markdown" class="container"> + {{ rendered_markdown|safe }} + +</div> + +{% endblock %}
\ No newline at end of file diff --git a/wqflask/wqflask/templates/glossary.html b/wqflask/wqflask/templates/glossary.html index 146c7e86..752c4b12 100644 --- a/wqflask/wqflask/templates/glossary.html +++ b/wqflask/wqflask/templates/glossary.html @@ -8,9 +8,16 @@ {% block content %} +<div class="github-btn-container"> + <div class="github-btn"> + <a href="https://github.com/genenetwork/gn-docs"> + Edit Text + <img src="/static/images/edit.png"> + </a> + </div> +</div> <div id="markdown" class="container"> - <small> - <a href="https://raw.githubusercontent.com/genenetwork/genenetwork2/wqflask/wqflask/static/glossary.md" target="_">[Edit on Github]</a></small> + {{ rendered_markdown|safe }} </div> {% endblock %} diff --git a/wqflask/wqflask/templates/links.html b/wqflask/wqflask/templates/links.html index 6ff7fc6c..072e8429 100644 --- a/wqflask/wqflask/templates/links.html +++ b/wqflask/wqflask/templates/links.html @@ -1,451 +1,24 @@ {% extends "base.html" %} -{% block title %}Links{% endblock %} -{% block content %} - -<Table width= "100%" cellSpacing=0 cellPadding=5><TR> - <!-- Body Start from Here --> - <TD vAlign=top width="100%" height=200> - - -<P class="title">Links for Exploring Networks of Genes and Phenotypes </P> - - -<Blockquote class="subtitle">GeneNetwork and WebQTL have integrated links to the following resources</Blockquote> -<Blockquote> -<Blockquote>GN PARTNERS, DEVELOPMENT SITES, AND MIRRORS</Blockquote> -<UL> -<LI><a href="http://genenetwork.helmholtz-hzi.de">German Helmholtz Foundation GeneNetwork</a> at the <A HREF="http://www.helmholtz-hzi.de/en/" target="_empty">Helmholtz Centre for Infection Research (HZI)</A>, Braunschweig Germany, in the <a href="hzi.de/en/research/research_groups/experimental_mouse_genetics/experimental_mouse_genetics/team/" target="_empty">research group</A> of Dr. Klaus Schughart. - -<LI><a href="http://genenetwork.epfl.ch" target="_empty">Swiss GeneNetwork</A> in the Laboratory of Integrative Systems Physiology lead by Dr. Johan Auwerx at the EPFL in Lausanne (initiated Nov 9, 2009) - -<LI><a href="http://www.genenetwork.waimr.uwa.edu.au">Australian GeneNetwork</a> mirror and development sites, Centre for Diabetes Research, University of Western Australia, in the research group of Dr. Grant Morahan <!--was http://130.95.9.19/--> (initiated May 2007) - -<LI><a href="http://webqtl.bic.nus.edu.sg/">Singapore GeneNetwork</a> mirror site at the National University of Singapore, Bioinformatics Center, Dr. Mark De Silva (initiated Oct 2009) - -<LI><a href="http://gn.genetics.ucla.edu" target="_empty">California GeneNetwork</A> mirror site in the Department of Genetics, University of California at Los Angeles, in the research group of Dr. A. Jake Lusis (initiated Aug 2008) - -<LI><a href="http://gnat.versailles.inra.fr/" target="_empty">INRA IJPB, Versailles</A> mirror site in the VAST lab of Dr. Olivier Loudet, Plant Breeding and Genetics Unit (initiated Dec 2008) - - -<LI><a href="http://xzhou3.memphis.edu/" target="_empty">University of Memphis</A> mirror sites in the Bioinformatics Program and research group of Drs. Ramin Homayouni and Mohammed Yazin (initiated June 2009) - -<LI><a href="http://www.computablegenomix.com/">Computable Genomix </a> and the <A HREF="https://grits.eecs.utk.edu/sgo/sgo.html" target="_empty">Semantic Gene Organizer</A> systems are the source of GeneNetwork literature correlation data sets. - -<BR><BR><BR> -<LI><a href="http://genenetwork.org/share/annotations/">Custom Microarray Annotation Files</a> used by GeneNetwork -</UL> -</Blockquote> - -<BR> - -<Blockquote class="subtitle">KEY RESOURCES CONNECTED WITH GENENETWORK</Blockquote> -<Blockquote> -<UL> -<LI><a href="http://mus.well.ox.ac.uk/mouse/HS/" target="_empty">Wellcome Trust Oxford Mouse Resource Portal</a> -<LI><a href="http://www.sanger.ac.uk/mouseportal/" target="_empty">WTSI Mouse Resource Portal</a> - -<LI><a href="http://www.sanger.ac.uk/cgi-bin/modelorgs/mousegenomes/lookseq/index.pl?show=1:10000000-10000000,paired_pileup&win=100&lane=129S1.bam&width=700" target="_empty">Sanger Mouse Sequencing Portal</a> (David Adams and colleagues) - -<LI><a href="http://www.grissom.gr/stranger/StRAnGER.php" target="_empty">StRAnGER</a> Gene Ontology and KEGG pathway analyzer - -<LI><a href="http://phenogen.ucdenver.edu/PhenoGen/index.jsp" target="_empty">PhenoGen Informatics</a> -<LI><a href="http://www.brain-map.org/welcome.do" target="_empty">The Allen Mouse Brain Atlas</a> -<LI><a href="http://amigo.geneontology.org/cgi-bin/amigo/go.cgi" target="_empty">AmiGO</a> -<LI><a href="http://syndb.cbi.pku.edu.cn/" target="_empty">Synapse DB</a> -<LI><a href="https://www.pantherdb.org" target="_empty">ABI Panther</a> -<LI><a href="http://biogps.gnf.org" target="_empty">BioGPS</A> <font>and its predecessor </font> <a href="http://symatlas.gnf.org/SymAtlas/" target="_empty">SymAtlas</A> -<LI><a href="http://mouse.perlegen.com/mouse/download.html -" target="_empty">Perlegen/NIEHS Mouse Sequence Data</A> -<LI><a href="http://www.ontologicaldiscovery.org/" target="_empty">Ontological Discovery Environment</a> -<LI><a href="https://shad.eecs.utk.edu/sgo/sgo.html" target="_empty">Semantic Gene Organizer</a> -<LI><a href="http://genome.ucsc.edu/" target="_empty">UCSC Genome Browser</A> and <a href="http://genome.brc.mcw.edu/" target="_empty">mirror</A> -<LI><a href="http://www.ensembl.org/Mus_musculus/index.html" target="_empty">Ensembl</A> -<LI><a href="http://www.ncbi.nlm.nih.gov/gquery/gquery.fcgi?itool=toolbar" target="_empty">NCBI</A> -<LI><a href="http://phenome.jax.org/pub-cgi/phenome/mpdcgi?rtn=docs/home" target="_empty">Mouse Phenome Database</A> and the <a href="http://phenome.jax.org/pub-cgi/phenome/mpdcgi?rtn=snps/list_pre" target="_empty">MPP SNP Browser</A> -<LI><a href="http://bioinfo.vanderbilt.edu/webgestalt/" target="_empty">WebGestalt</A> -<LI><a href="http://grappa.eecs.utk.edu" target="_empty">GrAPPA</A> Clique-based clustering tool -</UL> -</Blockquote> - -<BR> -<Blockquote class="subtitle">Resources for Analysis of Single Genes, SNPs, mRNAs, and Proteins</Blockquote> -<Blockquote> -<Blockquote> -<a href="http://harvester.fzk.de/harvester/" target="_empty">Harvester</a> retrieves summary data on any one of 57,000 proteins from several bioinformatic resources. -<SMALL>[Added Dec 22, 2004; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> - -<Blockquote> -<a href="http://mus.well.ox.ac.uk/cgi/gscan/wwwqtl.cgi" target="_empty">GSCAN</a>: the Oxford Wellcome Trust Genome Viewer retrieves mapping data for many mouse experimental mapping populations including the Heterogenous Stock, the Pre-Collaborative Cross mice, and Mouse Diversity Panel. -<SMALL>[Added Oct 13, 2010; last site review Oct 13, 2010 by RWW.]</SMALL> -</Blockquote> - - - - -<Blockquote> -<a href="http://nif-apps-stage.neuinfo.org/nif/nifgwt.html" target="_empty">NIF</a>: The Neuroscience Information Framework retrieves summary from a wide variety of neuroscience and bioinformatic resources. -<SMALL>[Added Dec 3, 2009; last site review Dec 3, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://genomics.senescence.info/" target="_empty">Genomics of aging resources</a>. A collection of databases and tools designed to help researchers understand the genetics of human ageing through a combination of functional genomics and evolutionary biology. -<SMALL>[Added Feb 28, 2010; last site review Feb 28, 2010 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.hgmd.cf.ac.uk/ac/index.php" target="_empty">Human Disease Gene Database</a> from Cardiff (requires log in) -<SMALL>[Added Nov 5, 2009; last site review Nov 5, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.snp-nexus.org/" target="_empty">SNPnexus</a> database of human SNPs is designed to simplify and assist in the selection of functionally relevant SNPs for large-scale genotyping studies of multifactorial disorders.<SMALL>[Added Jan 15, 2010; last site review Jan 15, 2010 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.snpedia.com/index.php/SNPedia" target="_empty">SNPedia</a> is a wiki investigating human genetics. We share information about the effects of variations in DNA, citing peer-reviewed scientific publications. It is used by Promethease to analyze and help explain your DNA.<SMALL>[Added Jan 15, 2010; last site review Jan 15, 2010 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="https://www.genoglyphix.com/ggx_browser/search/ -" target="_empty">Genoglyphix Browser</a> includes extensive data on human copy number variants as well as maps of low copy number repeat regions. -<SMALL>[Added Nov 5, 2009; last site review Nov 5, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.hprd.org/query" target="_empty">Human Protein Reference DB</a>: a manually curated resource with data on 20,000 proteins. Very effective interface and rich data. -<SMALL>[Added Oct 30, 2005; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://xmap.picr.man.ac.uk" target="_empty">x:map</a> is a terrific visual display tool for exploring Affymetrix Exon array data sets for mouse and human transcriptomes. -<SMALL>[Added April 18, 2008; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.pdg.cnb.uam.es/UniPub/iHOP/" target="_empty">iHOP</a> retrieves PubMed sentences that report interactions between a reference gene and associate genes and proteins. It allows the assembly of complex graphs that plot the literature interactions of genes. Effective interface for humans and machines. -<SMALL>[Added Dec 25, 2004; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.proteinatlas.org/" target="_empty">Human Protein Atlas</a> displays expression and localization of proteins in a large variety of normal human tissues and cancer cells as high resolution images of immunohistochemically stained tissues and cell lines. -<SMALL>[Added Sept 22, 2007; last site review Sept 22, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.gopubmed.com/" target="_empty">GoPubMed</a> is a simple tool that searches PubMed and sorts the results by GO and MeSH terms. -<SMALL>[Added July 5, 2007 by RWW; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.ncbi.nih.gov/IEB/Research/Acembly/index.html?human" target="_empty">AceView</a> and the <a href="http://www.ebi.ac.uk/astd/main.html" target="_empty">Alternative Splicing and Transcript Diversity database</A> provide excellent resources for systematic information about the many alternative transcripts produced from single genes. -<SMALL>[Added Jan 1, 2005; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> - -<Blockquote> -<a href="http://www.informatics.jax.org/menus/allsearch_menu.shtml" target="_empty">MGI</a> and <a href="http://rgd.mcw.edu/tool-entry.shtml" target="_empty">RGD</a> are reference sites for mouse and rat genetics, respectively. -<SMALL>[Added Dec 22, 2004; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> - - -<Blockquote> -<a href="http://www.dsi.univ-paris5.fr/genatlas/" target="_empty">GenAtlas</a> provides summary data for approximately 19300 human genes and has a useful link that will fetch 10 Kb of upstream sequence for promoter analysis. -[Added Jan 9, 2005; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://polly.wustl.edu/promolign/main.html" target="_empty">PromoLign</a> aligns homologous regions of mouse and human promoters and highlights SNPs and transcription factor binding sites. Check the quick tutorial to see how to extract key data. This site requires an SVG plugin that may not be supported by some browsers and operating systems. -[Added May 10, 2005; FAILED: last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://gai.nci.nih.gov/cgi-bin/GeneViewer.cgi?" target="_empty">CGAP SNP Viewer</a> allows users to view SNPs in the context of transcripts, ORFs and protein motifs for either human or mouse genes. Try the <I>Ahr</I> gene in mouse as an example. -<SMALL>[Added April 10, 2006; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://syndb.cbi.pku.edu.cn/" target="_empty">Synapse Database</a> (SynDB) is a comprehensive database of genes and proteins associated with the neuronal or neuromuscular synapse. Many <B>Trait Data and Analysis</B> pages provide links to SynDB. -<SMALL>[Added May 29, 2005; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://crb118.med.upenn.edu/syn/dev/syndb/main.php" target="_empty">Synapse Database</a> at University of Pennsylvania is a comprehensive database of roughly 200 genes and proteins associated with the synapse. -<SMALL>[Added Nov 26, 2006; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://biosingapore.org/index.php/Databases_and_tools" target="_empty">Singapore</a> Bio Databases and Tool. -<SMALL>[Added Dec 22, 2004; Dragon Genome Explorer site FAILED last site review, changed link; Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> - <a href="http://mutdb.org/AnnoSNP/" target="_empty" >MutDB</a> and <a href="http://www.snps3d.org/modules.php?name=Search&op=advanced%20search" target="_empty">SNPs3D</a> provide great data on functional SNPs in human genes. To analyze the functional impact of non-synonymous SNPs you will also find <a href="http://snpanalyzer.uthsc.edu/" target="_empty" >SNP Analyzer</a> useful because it evaluates SNP impact in terms of the whole protein structural context. -<SMALL>[Added Dec 22, 2004; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://moult.umbi.umd.edu/mouse2004/modules.php?name=Targets" target="_empty" >Alternative Splicing</a> Project provides great summaries and output graphs on splice variants in human, mouse, and Drosophila. -<SMALL>[Added Nov 8, 2005; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -</Blockquote> - -<BR> - -<Blockquote class="subtitle">Resources on Imprinting and Parental Origin Effects</Blockquote> -<Blockquote> -<Blockquote> -<a href="http://www.geneimprint.org/site/genes-by-species" target="_empty">Geneimprint</a> is a portal into the burgeoning field of genomic imprinting, collecting relevant articles and reviews, press reports, video and audio lectures, and genetic information -<SMALL>[Added June 23, 2010 by RWW; last site review June 23, 2010 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://igc.otago.ac.nz/Search.html" target="_empty">Catalogue of Parent of Origin Effects</a> provides a list of imprinted and putatively imprinted genes with commentary by Ian Morison (University of Otago, New Zealand). Database was last updated in 2008. -<SMALL>[Added June 23, 2010 by RWW; last site review June 23, 2010 by RWW.]</SMALL> -</Blockquote> -</Blockquote> - -<BR> - -<Blockquote class="subtitle">Resources for the Spatial Analysis of Gene and Protein Expression</Blockquote> -<Blockquote> -<Blockquote> -<a href="http://bioinformatics.ubc.ca/resources/links_directory/?subcategory_id=101 -" target="_empty">UBC Bioinformatic and Gene Expression Links</a> is a very extensive and well curated collection of on-line resources for the analysis of biological data sets. -<SMALL>[Added May 24, 2007 by RWW; last site review Sept 19, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -The <a href="http://mamep.molgen.mpg.de/mamep/search.php?searchtype=simple" target="_empty">mamep GeneExpression Links</a> image database of whole-mounted in situ hybridization of mid-gestation mouse embryos. Try entering the symbol <I>Ptch1</I>. -<SMALL>[Added May 28, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -The <a href="http://www.genes2cognition.org/genetics.html" target="_empty">Genes to Cognition</a> databases have a focus on proteins expressed in several key cellular compartments related to synpase function. -<SMALL>[Added Aug 9, 2007 by RWW.]</SMALL> -</Blockquote> - -<Blockquote> -<a href="http://www.cdtdb.brain.riken.jp/CDT/CDTSearch.jsp" target="_empty">Cerebellar Development Transcriptome Database</a>. Expression data for the mouse cerebellum, both microarray and in situ. -<SMALL>[Added Sept 1, 2010; last site review Sept 1, 2010 by RWW.]</SMALL> -</Blockquote> - - -<Blockquote> -Several excellent resources can be used to explore patterns of gene expression primarily in C57BL/6J mice. This strain is one of the parents of the BXD, AXB/BXA, BXH, and CXB genetic reference populations that are key resources in the Gene Network and its companion site, the <a href="http://www.mbl.org" target="_empty" >Mouse Brain Library</A>. -<UL> -<LI><a href="http://www.stjudebgem.org/web/search/keyword/searchByKeyWordForm.php" target="_empty">BGEM</a> and <a href="http://www.ncbi.nlm.nih.gov/projects/gensat/" target="_empty">GENSAT</a> provide images of gene expression in brains of embryos, neonates, and adult mice (roughly 2008 genes as of July 2005). -<BR> -<BR> -<LI><a href="http://www.genepaint.org/Frameset.html" target="_empty">GenePaint</a> and <a href="http://www.geneatlas.org/gene/search/searchgene.jsp" target="_empty">GeneAtlas</a> are companion sites that also provide expression data in embryos, neonates, and adults at high spatial resolution. GeneAtlas has excellent but slow image searching and matching capabilities. -<BR> -<BR> -<LI><a href="http://www.brain-map.org/index.jsp" target="_empty">Allen Brain Atlas</a> has expression data for ~12000 transcripts (adult males in the sagittal plane). -<BR> -<BR> -<LI><a href="http://genex.hgu.mrc.ac.uk/Emage/database/emageIntro.html" target="_empty">EMAP</a> (Edinburgh Mouse Atlas Project) provides data on expression of ~800 genes during development (in situ, immunohistochemistry, and reporter knock-in expression patterns). Most data are from wholemounts between Theiler stages 11 and 20 (embryonic days E7 to E13). EMAP can be used as a Java WebStart application. -<BR> -<BR> -<LI><a href="http://www.mouseatlas.org/data/mouse/project_tissue_view" target="_empty">Mouse Atlas of Gene Expression</a> is a massive SAGE library. The Atlas has quantified the normal state for many tissues by determining the number and identity of genes expressed throughout development. The scope of the project encompasses multiple stages of development of C57BL/6J mouse, from the single cell zygote to the adult, and includes an extensive initial collection of 200 tissues. DiscoverySpace is a WebStart application for use with The Mouse Atlas of Gene Expression. -<BR> -<BR> -<LI><a href="http://mahoney.chip.org/mahoney/database.html" target="_empty">Mahoney</a> Center maintains a rich image collection for ~1000 transcription factors expressed in brain (developmental stages, coronal plane). -<SMALL>[Added Dec 22, 2004; sites reviewed last on Sept 26, 2005 by RWW.]</SMALL> -<BR> -<BR> -</UL> -</Blockquote> -</Blockquote> - -<BR> - -<Blockquote class="subtitle">Resources for the Analysis of Sets and Networks of Transcripts, Genes, Proteins, and SNPs</Blockquote> -<Blockquote> -<Blockquote> -<a href="http://www.genemania.org/full.jsf" target="_empty">GeneMANIA</a> helps you predict the function of your favourite genes and gene sets. Powerful and fast computational methods and a great use of Cytoscape Web. (<A HREF="http://nar.oxfordjournals.org/cgi/content/full/38/suppl_2/W214" target="_empty">2010 PDF</A>). -<SMALL>[Added July 1, 2010; last site review Aug 8, 2010 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://toppgene.cchmc.org/" target="_empty">ToppGene Suite</a> A one-stop portal for gene list enrichment analysis and candidate gene prioritization based on functional annotations and protein interactions network -<SMALL>[Added Jan 16, 2010; last site review Jan 16, 2010 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.wikipathways.org/index.php/WikiPathways" target="_empty">WikiPathways</a> (WGCNA) is an open, public platform dedicated to the curation of biological pathways by and for the scientific community. -<SMALL>[Added Nov 12, 2009; last site review Nov 12, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.pathwaycommons.org/pc/" target="_empty">Pathway Commons</a> (WGCNA) is a search tool to find and visualize public biological pathway information. This site collates from several major sites. -<SMALL>[Added Nov 12, 2009; last site review Nov 12, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.sanger.ac.uk/cgi-bin/modelorgs/mousegenomes/snps.pl" target="_empty">Sanger Mouse Genome Project SNP Finder</a> provides access to SNP and indels generated by sequencing 17 strains of mice (plus C57BL/6J). Marvelous. -<SMALL>[Added Nov 18, 2009; last site review Nov 18, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/" target="_empty">Weighted Gene Coexpression Network Analysis</a> (WGCNA) is a collection of R functions to perform weighted correlation network analysis that includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. See the recent paper on <A HREF="http://www.biomedcentral.com/1471-2105/9/559">WGCNA</A>. -<SMALL>[Added Aug 21, 2009; last site review Aug 21, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.genome.jp/" target="_empty">GenomeNet</a> is a terrific site for the analysis of molecular networks. Download the very effective <a href="http://www.genome.jp/download/" target="_empty">KegArray</A> 0.2.6beta package (May 2005) for exploratory data analysis of microarray data set. This package is as good as most commerical software and includes with built-in linkage to the KEGG databases. Versions are available for Mac OS X and Windows. -<SMALL>[Added Jan 3, 2005; last site review Aug 5, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.bioinf.ebc.ee/EP/EP/" target="_empty">Expression Profiler at http://ep.ebi.ac.uk/</a> is a set of tools for clustering, analysis and visualization of gene expression and other genomic data. Tools in the Expression Profiler allow you to perform cluster analysis, pattern discovery, pattern visualization, study and search Gene Ontology categories, generate sequence logos, extract regulatory sequences, study protein interactions, as well as to link analysis results to external tools and databases. -<SMALL>[Added May 20, 2008; last site review May 20, 2008 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.thebiogrid.org/" target="_empty">BioGRID</a>: the Biological General Repository for Interaction Datasets is a freely accessible database of protein and genetic interactions from Mt. Sinai, Toronto. -<SMALL>[Added July 28, 2007; last site review July 28, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://cismols.cchmc.org/" target="_empty">CisMols Analyzer</a> at Cincinnati Children's Hospital (Aronow and colleagues) is a server and database for the analysis of cis element co-occurences in the promoters of a list of genes. The <a href="http://polydoms.cchmc.org/polydoms/" target="_empty">PolyDoms Analyzer</a> is a tool for scanning through gene lists for those members of a pathway, ontolog, or disease that contain potentially harmful protein-coding SNPs. <a href="http://genometrafac.cchmc.org/" target="_empty">GenomeTraFaC</a> is a comparative genomics-based resource for initial characterization of gene models and the identification of putative cis-regulatory regions of RefSeq Gene Orthologs. -<SMALL>[Added Sept 23, 2006; last site review Sept 23, 2006 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://compbio.uthsc.edu/miRSNP/" target="_empty">PolymiRTS</a> database that searches for microRNA (miRNA) targets in transcripts that overlap SNPs. This database will also search for genes with associated phenotype variants that may have variants in miRNA target sequence (Yan Cui, Lei Bao and colleagues). - <SMALL>[Added Sept 23, 2006; last site review Sept 23, 2006 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.broad.mit.edu/gsea/msigdb/msigdb_index.html" target="_empty">MSigDB</a>: The Molecular Signature Database is part of the Broad Institute Gene Set Enrichment Analysis suite. MSigDB contains large numbers of static and partly annotated sets of genes/transcripts. Registration is not actually required to download data sets. - <SMALL>[Added Jan 18, 2007; last site review Jan 18, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://inia.uchsc.edu/INIA/index.jsp" target="_empty">C-INIA</a> MAGIC-B microarray knowledgebase from the Department of Pharmacology, University of Colorado, Denver, part of the NIAAA INIA project. Extensive public and privated brain array data sets in a powerful analytic web environment. - <SMALL>[Added May 31, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.genmapp.org/introduction.asp" target="_empty">GenMAPP 2.0</a> (2004), the Gene Map Annotation and Pathway Prolifer, is a free Windows application (simple registration required) with which you can visualize expression and other genomic data sets on maps of biological pathways. Very flexible suite of programs that you can also use to make custom gene annotation maps (and more). -<SMALL>[Added Aug 5, 2005; last site review Aug 5, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://bind.ca/" target="_empty">BIND</a> and <a href="http://string.embl.de/" target="_empty">STRING</a> and <a href="http://www.ebi.ac.uk/intact/index.jsp" target="_empty">IntAct</a> are great sites that provide access to well curated data on protein-protein interactions. BIND and IntAct focus on experimentally verified interactions whereas STRING and preBIND incorporate inferred interaction based on other data types, including gene expression. Links to BIND and STRING have been added to the Trait Data and Analysis forms on the GeneNetwork BETA site. -<SMALL>[Added Aug 21, 2005; last site reviews Aug 27, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://ai.stanford.edu/~erans/cancer/index.html" target="_empty">Microarray Module Maps</a> is a great site that databases a large number of coexpression modules defined using many cancer array studies. -<SMALL>[Added Aug 26, 2005; last site review Aug 26, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.geneontology.org/GO.tools.microarray.shtml" target="_empty">The Gene Ontology Consortium</a> maintains a well annotated list of open resources for the analysis of large expression data sets and gene ontologies. Note that there are several different lists, each with valuable links. -<SMALL>[Added July 15, 2005; last site review July 15, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.prioritizer.nl/" target="_empty">Prioritizer</a>: Prioritizer is a stand-alone Java program that uses a functional human gene network, available at <a href="http://www.genenetwork.nl" target="_empty">www.genenetwork.nl</a>, to prioritize positional candidate genes that reside within susceptibility loci, by assuming that real disease genes, residing within different loci are functionally closely related within the gene network.</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.bioinformatics.ic.ac.uk/eqtl/" target="_empty">eQTL Explorer</a> is a Java WebStart application that has also been designed for the calculation and display of QTL maps for large rat data sets, particuarly those generated using the HXB strains. Locations of QTLs for both mRNA traits and conventional physiological traits are displayed on chromosome ideograms. High precision QTL maps can also be generated. A password is required to gain access to the primary data files. -<SMALL>[Added January 7, 2006; last site review Jan 7, 2006 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://cliquego.uthsc.edu/" target="_empty">Clique-GO Analysis</a> is a novel tool for extracting cliques of coregulated transcripts. The current data requires Affymetrix U74Av2 probe set IDs as input. Try "103370_at" (the gene <I>Lin7c</I>) as an example. -<SMALL>[Added Jan 4, 2005; last site review Jan 4, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.bioinformatics.ubc.ca/pavlidis/lab/software.html" target="_empty">Gemma and ErmineJ</a> are powerful resources for analysis and metaanalysis of gene expression data sets at UBC. Pavlidis and colleagues also provide updated <A HREF="http://bioinformatics.ubc.ca/microannots/ -">GO data</A> for common microarray platforms. -<SMALL>[Added Jan 4, 2005; last site review June 7, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.cytoscape.org/index.php" target="_empty">Cytoscape</a> is one of several <a href="http://sbml.org/index.psp" target="_empty">SBML</a>-compatible open source programs for visualizing molecular interaction networks and overlaying these networks with gene expression profiles and other data sets to generate and test specific hypotheses. -<SMALL>[Added Jan 5, 2005; last site review Jan 5, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://cgap.nci.nih.gov/Pathways/Pathway_Searcher" target="_empty">Pathway Searcher</a> provides fast access to gene/protein interaction pathways. An intuitive interface. -<SMALL>[Added Dec 30, 2004; last site review Dec 30, 2004 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://genome.ucsc.edu/cgi-bin/hgNear" target="_empty">Gene Sorter</a> is a tool for generating and sorting sets of genes using a wide variety of information integrated into UCSC's Genome Brower. -<SMALL>[Added Dec 31, 2004; last site review Dec 31, 2004 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.cisreg.ca/cgi-bin/oPOSSUM/opossum" target="_empty">oPPOSUM</a> is a tool for finding over-represented transcription factor binding sites in lists of mouse and human genes. It handles about 100 out of greater than 600 TFBSs. -<SMALL>[Added Jan 27, 2005; last site review Nov 21, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://motif.genome.jp/" target="_empty">MOTIF</a> and <a href="http://www.dbi.tju.edu/dbi/tools/paint/index.php?op=FnetBuilder" target="_empty">PAINT</a> search for motifs in submitted sequences or lists of genes. Paint makes use of the TRANSFAC Pro database. -<SMALL>[Added Dec 22, 2004; last site review Dec 25, 2004 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://arrowsmith.psych.uic.edu/arrowsmith_uic/index.html" target="_empty">Arrowsmith</a> provides a fast way to evaluate known interactions or common mechanisms between two genes or proteins. It carries out a sophisticated comparison of the current PubMed database. -<SMALL>[Added Dec 22, 2004; last site review June 7, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.chilibot.net/" target="_empty">Chilibot</a> applies natural-language processing to the PubMed database to hunt for directed relationships among pairs or sets of genes, proteins, and keywords. <SMALL>[Added Dec 30, 2004; last site review Aug 13, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -Mouse Imprinting Resources: -<a href="http://www.mgu.har.mrc.ac.uk/research/imprinting" target="_empty">The Harwell Mouse Imprinting Resource</a>, -<a href="http://www.geneimprint.com/" target="_empty">Duke University - Jirtle's Laboratory</a>, -<a href="http://fantom2.gsc.riken.go.jp/imprinting/" target="_empty">RIKEN Candidate Imprinted Transcript Maps</a>, and -<a href="http://igc.otago.ac.nz/home.html">Imprinted Gene Catalogue - University of Otago</a>. -<SMALL>[Added Oct 20, 2006; last site review Oct 20, 2006 by RWW.]</SMALL> -</Blockquote> -</Blockquote> - -<BR> - -<Blockquote class="subtitle">Resources for the Analysis of Phenotypes in Genetic Reference Populations</Blockquote> -<Blockquote> -<Blockquote> -<a href="http://www.mbl.org/NewMBL_MySQL/tmbl.php" target="_empty">MBL</a> is a extensive image database of brain sections from genetic reference populations of mice, including the BXD, AXB, CXB, BXH strains included in WebQTL. The MBL is a companion database of WebQTL. -<SMALL>[Added Dec 22, 2004; last site review Aug 6, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://snp.ucsd.edu/mouse/" target="_empty">MPAD</a> Mouse Phenome Association Database v 1.0, by Eleazar Eskin and Hyun Min Kang. This resource performs genome-wide association mapping. Phenotype data sets are derived from the Mouse Phenome Project set of standard mouse strains. The permutation procedures account for the genetic relations among these strains and provide much more appropriate genome-wide significance thresholds than previous mouse association mapping methods. -<SMALL>[Added Nov 19, 2006; last site review Nov 19, 2006 by RWW. Link broken June 2007 probably due to move from UCSD to UCLA; check with EE.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://gscan.well.ox.ac.uk/gs/wwwqtl.cgi#" target="_empty">GScan</a> at the Wellcome Trust, Oxford, is a sophisticated viewer and analysis tool with which to explore the genetic control of diverse phenotypes (including array data) generated using heterogeneous stock mice (Flint, Mott, and colleagues). -<SMALL>[Added May 28, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://phenome.jax.org/pub-cgi/phenome/mpdcgi?rtn=docs/home" target="_empty">Phenome Project</a> provides access to a wide variety of phenotype data many common and wild inbred strains of mice. -<SMALL>[Added Dec 22, 2004; last site review Dec 25, 2004 by RWW.]</SMALL> -</Blockquote> -</Blockquote> - -<BR> - -<Blockquote class="subtitle">QTL Mapping Resources</Blockquote> -<Blockquote> -<Blockquote> -<a href="http://compbio.uthsc.edu/QSB/" target="_empty">QSB</a>: QSB is a stand-alone JAVA program with a sophisticated GUI developed for genetical genomics or systems genetics, an emerging field that combines quantitative genetics and genomics. QSB stands for QTL mapping, Sequence polymorphism analysis (or SNP analysis) and Bayesian network analysis. QSB takes marker and array data from a segregating population as input and identifies significant QTLs and then evaluated networks of candidate genes associated with these QTLs. -<SMALL>[Added July 29, 2005; last site review Jan 7, 2006 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://omicspace.riken.jp/PosMed" target="_empty">Positional Medline (PosMed)</A> is a knowledge-based ranking system of candidate genes within QTL intervals for human, mouse, rat, Arabidopsis, and rice. -<SMALL>[Added Nov 4, 2009; last site review Nov 4, 2009 by RWW.]</SMALL> -</Blockquote> -<Blockquote><a href="http://omicspace.riken.jp" target="_empty">Genome - Phenome Superbrain Project</a> integrates various databases to build a comprehensive computerized encyclopedia of omic sciences in several species, including mouse, rat, human, and arabidopsis, etc. The goal is to evolve this intelligent system into a form of artificial intelligence that can solve a researcher's problems by exploiting a vast amount of information accumulated in documents and published data ranging from genomes to phenomes. <SMALL>[Added Sept 13, 2007; last site review Sept12, 2007 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://qtlreaper.sourceforge.net/" target="_empty">QTL Reaper</a> is software, written in C and compiled as a Python module, for rapidly scanning microarray expression data for QTLs. It is essentially the batch-oriented version of WebQTL. It requires, as input, expression data from members of a set of recombinant inbred lines and genotype information for the same lines. It searches for an association between each expression trait and all genotypes and evaluates that association by a permutation test. For the permutation test, it performs only as many permutations as are necessary to define the empirical P-value to a reasonable precision. It also performs bootstrap resampling to estimate the confidence region for the location of a putative QTL. -<SMALL>[Added Jan 27, 2005; last site review Jan 27, 2005 by KFM.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://ibi.zju.edu.cn/software/qtlnetwork/" target="_empty">QTLNetwork 2.0</a> is a software package ofr mapping QTLs with epistatic and GXE interaction effects in experimental populations including double-haploid, recombinant inbred, backcross, F2, IF2 and BxFy populations. The program provides graphical presentations of QTL mapping results. The software is programmed by C++ programming language under Microsoft Visual C++ 6.0 environment. It works with Microsoft Windows operating systems, including Windows 95/98, NT, 2000, XP, 2003server. A new version of QTLNetwork is under developing, and its functions will be extended to include linkage group construction and marker-assisted virtual breeding.<SMALL>[Added June 21, 2007.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.broad.mit.edu/personal/claire/MouseHapMap/Inbred.htm" target="_empty">MouseHapMap</a> project genotypes from Mark Daly and colleagues. Approximately 140,000 SNPs across 49 strains. Updated Feb 2006.used to explore the Oxford Wellcome Heterogeneous stock QTL mapping project population. It currently includes mapping data for 100+ phenotypes typed across 2000 animals and 13,000 SNPs. -<SMALL>[Added May 10, 2006; last site review May 10, 2006 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -A valuable list of <a href="http://www.stat.wisc.edu/%7Eyandell/qtl/software/" target="_empty">Software for QTL Data Analysis</a> and <B>Gene Expression Microarray Software</B> is managed by Brian Yandell at University of Wisconsin. -<SMALL>[Added May 16, 2006; last site review May 16, 2006 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://gscan.well.ox.ac.uk/gs/wwwqtl.cgi" target="_empty">GSCAN DB</a> is a browser used to explore the Oxford Wellcome Heterogeneous stock QTL mapping project population. It currently includes mapping data for 100+ phenotypes typed across 2000 animals and 13,000 SNPs. -<SMALL>[Added May 10, 2006; last site review May 10, 2006 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://www.well.ox.ac.uk/mouse/INBREDS/" target="_empty">The Wellcome Trust-CTC SNP Data Set</a> consists of high density SNP data for approximately 490 strains of mice at 13,377 SNPs. These data fiels were processed slightly to generate many of the mouse mapping files used in WebQTL. -<SMALL>[Added Sept 27, 2005; last site review Sept 27, 2005 by RWW.]</SMALL> -</Blockquote> -<Blockquote> -<a href="http://mouse.perlegen.com/mouse/summary_reports.html" target="_empty">The NIEHS-Perlegen Mouse Strain Resequencing Project</a> provides links to SNP data for up to 15 strains of mice. Very high density data for many chromosomes. These data are integrated to some extent in the GeneNetwork. -<SMALL>[Added Sept 25, 2005; last site review Sept 25, 2005 by RWW.]</SMALL> -</Blockquote> -</Blockquote> +{% block title %}Links{% endblock %} -<BR> +{% block css %} +<link rel="stylesheet" type="text/css" href="/static/new/css/markdown.css" /> +{% endblock %} -<Blockquote class="subtitle">Affymetrix Array Annotation Resources</Blockquote> -<Blockquote> -<Blockquote> -<a href="http://research.stowers-institute.org/efg/ScientificSoftware/Applications/Affy/Annotations/" target="_empty">Affy MOE430A and MOE430B Annotation</a> files are explained more clearly that Affymetrix has ever done by Earl F Glynn at the Stowers Institute. (efg@stowers-insitute.org). -<SMALL>[Added July 17, 2006; last site review June 7, 2007 by RWW. This Oct 7, 2005 file caused Grace Wheeler's Mac internet connection to break.]</SMALL> -</Blockquote> -</Blockquote> +{% block content %} -<BR> +<div class="github-btn-container"> + <div class="github-btn "> + <a href="https://github.com/genenetwork/gn-docs"> + Edit Text + <img src="/static/images/edit.png"> + </a> + </div> +</div> -<Blockquote class="subtitle">Information about this HTML page: </Blockquote> -<Blockquote> -<Blockquote><P><P>This text originally generated by RWW, Dec 21, 2004. Updated by EJC, Feb 27, 2005; by RWW, July 15, Sept 25. -<P>Management of GeneNetwork access and trait <A HREF="http://www.genenetwork.org/manager.html">pages</A>. -</Blockquote> -</Blockquote> - - </TD> - </TR></TABLE> +<div id="markdown" class="container"> + {{ rendered_markdown|safe }} -{% endblock %} +</div> +{% endblock %}
\ No newline at end of file diff --git a/wqflask/wqflask/templates/mapping_results.html b/wqflask/wqflask/templates/mapping_results.html index 28d93542..9542c29d 100644 --- a/wqflask/wqflask/templates/mapping_results.html +++ b/wqflask/wqflask/templates/mapping_results.html @@ -40,6 +40,9 @@ <input type="hidden" name="use_loco" value="{{ use_loco }}"> <input type="hidden" name="selected_chr" value="{{ selectedChr }}"> <input type="hidden" name="manhattan_plot" value="{{ manhattan_plot }}"> + {% if manhattan_plot == True %} + <input type="hidden" name="color_scheme" value="alternating"> + {% endif %} <input type="hidden" name="num_perm" value="{{ nperm }}"> <input type="hidden" name="perm_info" value=""> <input type="hidden" name="perm_strata" value="{{ perm_strata }}"> @@ -55,7 +58,7 @@ <input type="hidden" name="wanted_inputs" value=""> <input type="hidden" name="form_url" value="/run_mapping"> - <div class="container"> + <div class="container" style="min-width: 1400px;"> <div class="col-xs-5"> <h2>Map Viewer: Whole Genome</h2><br> <b>Population:</b> {{ dataset.group.species|capitalize }} {{ dataset.group.name }}<br> @@ -77,7 +80,7 @@ <table> <tr> <td><b>Chr: </b></td> - <td> + <td style="padding: 5px;"> <select name="chromosomes" size="1"> {% for chr in ChrList %} <option value="{{ chr[1] }}" {% if (chr[1] + 1) == selectedChr %}selected{% endif %}>{{ chr[0] }}</option> @@ -87,7 +90,7 @@ </td> </tr> <tr> - <td><b>View: </b></td> + <td ><b>View: </b></td> <td style="padding: 5px;"> <input type="text" name="startMb" size="7" value="{% if startMb != -1 %}{{ startMb }}{% endif %}"> to <input type="text" name="endMb" size="7" value="{% if endMb != -1 %}{{ endMb }}{% endif %}"> </td> @@ -114,11 +117,31 @@ </tr> <tr> <td><b>Width: </b></td> - <td> + <td style="padding: 5px;"> <input type="text" name="graphWidth" value="{% if graphWidth is defined %}{{ graphWidth }}{% else %}1600{% endif %}" size="5"><span style="font-size: 12px;"> pixels (minimum=900)</span> </td> </tr> </table> + {% if manhattan_plot == True and selectedChr == -1 %} + <table style="margin-top: 10px;"> + <tr> + <td> + <b>Manhattan Plot Color Scheme: </b> + </td> + <td> + <select id="color_scheme"> + <option value="alternating" {% if color_scheme == "alternating" %}selected{% endif %}>Alternating</option> + <option value="varied" {% if color_scheme == "varied" %}selected{% endif %}>Varied by Chr</option> + <option value="single" {% if color_scheme == "single" %}selected{% endif %}>Single Color</option> + </select> + </td> + <td> + <input name="manhattan_single_color" type="hidden" id="point_color" value={% if manhattan_single_color %}{{ manhattan_single_color }}{% else %}"#D9D9D9"{% endif %}> + <button style="display: none; margin-left: 5px;" id="point_color_picker" class="jscolor {valueElement: 'point_color'}">Choose Color</button> + </td> + </tr> + </table> + {% endif %} </div> <div class="col-xs-4" style="padding: 0px;"> {% if (mapping_method == "reaper" or mapping_method == "rqtl_geno") and nperm > 0 %} @@ -328,6 +351,9 @@ <script type="text/javascript" src="{{ url_for('js', filename='underscore-string/underscore.string.min.js') }}"></script> <script type="text/javascript" src="{{ url_for('js', filename='d3-tip/d3-tip.js') }}"></script> <script type="text/javascript" src="/static/new/js_external/plotly-latest.min.js"></script> + {% if manhattan_plot == True and selectedChr == -1 %} + <script type="text/javascript" src="/static/new/js_external/jscolor.js"></script> + {% endif %} <script language="javascript" type="text/javascript" src="{{ url_for('js', filename='DataTables/js/jquery.dataTables.min.js') }}"></script> <script language="javascript" type="text/javascript" src="https://cdn.datatables.net/buttons/1.0.0/js/dataTables.buttons.min.js"></script> @@ -423,7 +449,7 @@ var mapping_input_list = ['temp_uuid', 'trait_id', 'dataset', 'tool_used', 'form_url', 'method', 'transform', 'trimmed_markers', 'selected_chr', 'chromosomes', 'mapping_scale', 'score_type', 'suggestive', 'significant', 'num_perm', 'permCheck', 'perm_output', 'perm_strata', 'categorical_vars', 'num_bootstrap', 'bootCheck', 'bootstrap_results', - 'LRSCheck', 'covariates', 'maf', 'use_loco', 'manhattan_plot', 'control_marker', 'control_marker_db', 'do_control', 'genofile', + 'LRSCheck', 'covariates', 'maf', 'use_loco', 'manhattan_plot', 'color_scheme', 'manhattan_single_color', 'control_marker', 'control_marker_db', 'do_control', 'genofile', 'pair_scan', 'startMb', 'endMb', 'graphWidth', 'lrsMax', 'additiveCheck', 'showSNP', 'showGenes', 'viewLegend', 'haplotypeAnalystCheck', 'mapmethod_rqtl_geno', 'mapmodel_rqtl_geno', 'temp_trait', 'group', 'species', 'reaper_version', 'primary_samples', 'n_samples'] @@ -449,10 +475,21 @@ remap = function() { $('input[name=selected_chr]').val($('select[name=chromosomes]').val()); + $('input[name=color_scheme]').val($('select#color_scheme').val()); $('#marker_regression_form').attr('action', '/loading'); return $('#marker_regression_form').submit(); }; + {% if manhattan_plot == True and selectedChr == -1 %} + $('#color_scheme').change(function(){ + if ($(this).val() == "single"){ + $('#point_color_picker').show(); + } else { + $('#point_color_picker').hide(); + } + }); + {% endif %} + {% if mapping_method != "gemma" and mapping_method != "plink" %} $('#download_perm').click(function(){ perm_info_dict = { diff --git a/wqflask/wqflask/templates/policies.html b/wqflask/wqflask/templates/policies.html index 83b6b3c0..4e0985d3 100644 --- a/wqflask/wqflask/templates/policies.html +++ b/wqflask/wqflask/templates/policies.html @@ -1,18 +1,23 @@ {% extends "base.html" %} -{% block title %}Policies{% endblock %} + +{% block title %}Links{% endblock %} + +{% block css %} +<link rel="stylesheet" type="text/css" href="/static/new/css/markdown.css" /> +{% endblock %} + {% block content %} -<Table width= "100%" cellSpacing=0 cellPadding=5><TR> -<!-- Body Start from Here --> -<TD valign="top" height="200" width="100%"> - <P class="title">WebQTL Conditions of Use</P> - <UL> - <LI><A HREF="conditionsofUse.html">WebQTL Usage Conditions and Limitations</A><P></P> - <LI><A HREF="dataSharing.html">WebQTL Data Sharing Policy</A><P></P> - <LI><A HREF="statusandContact.html">Status and investigators to contact on data use and publication</A><P></P> - </UL> - <P></P> -</TD> -</TR></TABLE> + <div class="github-btn-container"> + <div class="github-btn "> + <a href="https://github.com/genenetwork/gn-docs"> + Edit Text + <img src="/static/images/edit.png"> + </a> + </div> +</div> +<div id="markdown" class="container"> + {{ rendered_markdown|safe }} +</div> {% endblock %}
\ No newline at end of file diff --git a/wqflask/wqflask/templates/reference.html b/wqflask/wqflask/templates/reference.html deleted file mode 100644 index d95d22e3..00000000 --- a/wqflask/wqflask/templates/reference.html +++ /dev/null @@ -1,1497 +0,0 @@ -{% extends "base.html" %} -{% block title %}References{% endblock %} -{% block content %} - -<h2> Papers and References to GeneNetwork</A></h2> - -<BLOCKQUOTE> - -<left> -<a href="#New">Highlighted References</a> | -<a href="#Key">Key References</a> | -<a href="#Background">Background References</a> | -</left> - -<BR> <BR> -<left> -<a href="#2020">2020</a> | -<a href="#2019">2019</a> | -<a href="#2018">2018</a> | -<a href="#2017">2017</a> | -<a href="#2016">2016</a> | -<a href="#2015">2015</a> | -<a href="#2014">2014</a> | -<a href="#2013">2013</a> | -<a href="#2012">2012</a> | -<a href="#2011">2011</a> | -<a href="#2010">2010</a> | -<a href="#2009">2009</a> | -<a href="#2008">2008</a> | -<a href="#2007">2007</a> | -<a href="#2006">2006</a> | -<a href="#2005">2005</a> | -<a href="#2004">2004</a> | -<a href="#2003">2003</a> | -</left> -</BLOCKQUOTE> - -<DIR> - <A HREF="https://scholar.google.com/scholar?as_q=&as_epq=&as_oq=webqtl+%22genenetwork%22&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&btnG=&hl=en&as_sdt=0%2C5"target="_blank" class="fwn">Google Scholar</A> search for <I> "genenetwork" OR "webqtl" </I> generated: -<OL> -<LI>1430 hits on 2016/09/08 -<LI>1730 hits on 2017/10/17 -<LI>2020 hits on 2019/05/13) -</OL> - -<A HREF="https://scholar.google.com/scholar?as_q=&as_epq=&as_oq=genenetwork.org&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&btnG=&hl=en&as_sdt=0%2C5"target="_blank" class="fwn">Google Scholar</A> search for <I> "genenetwork.org" </I> generated: - -<OL> -<LI>1030 hits on 2019/05/13 -<LI> 105 hits from 2018/01/01 to 2019/05/13 -</OL> - -</DIR> - - -<BLOCKQUOTE> - <A NAME="New" class="subtitle">Highlighted References</A> -<BLOCKQUOTE style="font-size: 14px;"> - -<B><I>Please send us citations to articles that we may have missed.</I></B> - -<OL> - -<LI> Mulligan MK, Mozhui K, Prins P, Williams RW (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27933521" target="_blank" class="fwn">2017</A>) GeneNetwork: A Toolbox for Systems Genetics. In <I>Systems Genetics</I>, Methods in Molecular Biology 1488:75-120 -[An updated primer in using GeneNetwork for molecular analysis of mouse and human cohorts.] -<SMALL><A HREF="/images/upload/Mulligan_How_To_Use_GeneNetwork_2017_v1.pdf" target="_blank" class="fwn">PDF version</A> -</SMALL> -<BR> -<BR> - -<LI> Williams RW, Williams EG (<A HREF="/images/upload/Williams_ResourcesSystemsGenetics_MethodsMolBio_2016.pdf" target="_blank" class="fwn"" target="_blank" class="fwn">2017</A>) Resources for Systems Genetics. In <I>Systems Genetics</I>, Methods in Molecular Biology 1488:3-29. -[This review is intended to help you when making the hard choices about types of resources to use in system genetic studies. The short answer: embrace diversity in your resources. The computational barriers to joint analysis are now minimal.] -<SMALL><A HREF="/images/upload/Williams_ResourcesSystemsGenetics_MethodsMolBio_2016.pdf" target="_blank" class="fwn">PDF version</A> -</SMALL> -<BR> -<BR> - -<LI> Williams RW (<A HREF="http://journal.frontiersin.org/article/10.3389/neuro.01.016.2009/full" target="_blank" class="fwn">2009</A>) Herding cats: the sociology of data integration. Frontier in Neuroscience 3(2):154-6. -[An short but amusing commentary on predictive (someday perhaps even precision) medicine and how to get there using genetic reference populations such as the BXD and Collaborative Cross families.] -<SMALL><A HREF="http://journal.frontiersin.org/article/10.3389/neuro.01.016.2009/full" target="_blank" class="fwn">PDF version</A> -</SMALL> -<BR> -<BR> - - -<LI> -Pinelli M, Carissimo A, Cutillo L, Lai CH, Mutarelli M, Moretti MN, Singh MV, Karali M, Carrella D, Pizzo M, Russo F, Ferrari S, Ponzin D, Angelini C, Banfi S, di Bernardo D (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27235414" target="_blank" class="fwn">2016</A>) An atlas of gene expression and gene co-regulation in the human retina.Nucleic Acids Res. 2016 Jul 8;44(12):5773-84 -<SMALL><A HREF="http://retina.tigem.it" target="_blank" class="fwn">RETINA database</A>, and see the <A HREF="/images/upload/Pinelli_diBerardo_2016_AtlasHumanRetina.pdf" target="_blank" class="fwn">PDF</A>. These data are now in GeneNetwork (Species = Human, Group = Retina). -</SMALL> - -<BR> -<BR> - - -<LI> -Williams EG, Wu Y, Pooja J, Dubuis S, Blattmann P, Argmann CA, Houten SM, Amariuta T, Wolski W, Zamboni N, Aebersold R, Auwerx J (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27284200" target="_blank" class="fwn">2016</A>) Systems proteomics and trans-omic integration illuminate new mechanisms in mitochondrial function. Science 352(6291):aad0189 -<SMALL><A HREF="http://science.sciencemag.org/content/352/6291/aad0189.full" target="_blank" class="fwn">HTML version</A>, <A HREF="/images/upload/WilliamsEG_Auwerx_Systems_Science-2016.pdf " target="_blank" class="fwn">PDF</A> -</SMALL> -<BR> -<BR> - - - -<LI> -Sloan Z, Arends D, Broman KW, Centeno A, Furlotte N, Nijveen H, Yan L, Zhou X, Williams RW, Prins P (2016) GenetNetwork: framework for web-based genetics. The Journal of Open Source Software http://joss.theoj.org/papers/10.21105/joss.00025 (http://dx.doi.org/10.21105/joss.00025) -<SMALL><A HREF="http://joss.theoj.org/papers/10.21105/joss.00025" target="_blank" class="fwn">HTML version</A> -</SMALL> -<BR> -<BR> - -<LI>Alam G, Miller DB, O'Callaghan JP, Lu L, Williams RW, Jones BC (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27182044" target="_blank" class="fwn">2016</A>) MPTP neurotoxicity is highly concordant between the sexes among BXD recombinant inbred mouse strains. Neurotoxicology in press -<SMALL><A HREF="/images/upload/Alam_Jones_MPTP_Neurotox_2016.pdf" target="_blank" class="fwn">PDF version</A> -</SMALL> -<BR> -<BR> - - -<LI>Merkwirth C, Jovaisaite V, Durieux J, Matilainen O, Jordan SD, Quiros PM, Steffen KK, Williams EG, Mouchiroud L, Tronnes SU, Murillo V, Wolff SC, Shaw RJ, Auwerx J, Dillin A (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27133168" target="_blank" class="fwn">2016</A>) Two conserved histone demethylases regulate mitochondrial stress-induced longevity. Cell 165:1209-1223 -<BR> -<BR> - - -<LI> Wang X, Pandey AK, Mulligan MK, Williams EG, Mozhui K, Li Z, Jovaisaite V, Quarles LD, Xiao Z, Huang J, Capra JA, Chen Z, Taylor WL, Bastarache L, Niu X, Pollard KS, Ciobanu DC, Reznik AO, Tishkov AV, Zhulin IB, Peng J, Nelson SF, Denny JC, Auwerx J, Lu L, Williams RW (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26833085" target="_blank" class="fwn">2016</A>). Joint mouse-human phenome-wide association to test gene function and disease risk. Nature Communications 7:10464 -[Best reference on the BXD family of strains and the wide range of phenotypes that have been generated over the past 40 years.] - -<SMALL><A HREF="/images/upload/Wang_PheWas_NatComm_2016.pdf" target="_blank" class="fwn">PDF version</A> and the - -<A HREF="/images/upload/Wang_SupplementalTables_NatComm_2016.xlsx" target="_blank" class="fwn">Supplementary Tables in one Excel file</A> -</SMALL> - -<BR> -<BR> - - -<LI> Xue Y, Li J, Yan L, Lu L, Liao FF (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26092713" target="_blank" class="fwn">2015</A>) Genetic variability to diet-induced hippocampal dysfunction in BXD recombinant inbred (RI) mouse strains. Behav Brain Res 292:83-94 -<BR> -<BR> - -<LI>Chaum E, Winborn CS, Bhattacharya S (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25963977" target="_blank" class="fwn">2015</A>) Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population. Mamm Genome 26:210-221 -<BR> -<BR> - -<LI>Cheng Q, Seltzer Z, Sima C, Lakschevitz FS, Glogauer M. (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25942439" target="_blank" class="fwn">2015</A>) Quantitative Trait Loci and Candidate Genes for Neutrophil Recruitment in Sterile Inflammation Mapped in AXB-BXA Recombinant Inbred Mice. PLoS One 10:e0124117 -<BR> -<BR> - -<LI>Scott RE, Ghule PN, Stein JL, Stein GS (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25215496" target="_blank" class="fwn">2015</A>) Cell cycle gene expression networks discovered using systems biology: Significance in carcinogenesis. J Cell Physiol 230:2533-42 -<BR> -<BR> - -<LI> Williams EG, Auwerx J (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26140590" target="_blank" class="fwn">2015</A>) The convergence of systems and reductionist approaches in complex trait analysis. Cell 162:23-32. -<BR> -<BR> - -<LI>Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25215496" target="_blank" class="fwn">2014</A>) Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population. Cell 158:1415-1430 -<BR> -<BR> - -<LI> -Hayes SK, Hager R, Grencis RK (2014) Sex-dependent genetics effects on immune responses to parasitic nematodes. BMC Genomics 15:193 -<BR> -<BR> - -<LI>Harenza JL, Muldoon PP, De Biasi M, Damaj MI, Miles MF (2014) Genetic variation within the Chrna7 gene modulates nicotine reward-like phenotypes in mice. Genes Brain Behav 13:213-225 -<BR> -<BR> - - -<LI> -Ye R, Carneiro AM, Airey D, Sanders-Bush E, Williams RW, Lu L, Wang J, Zhang B, Blakely RD (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24102824" target="_blank" class="fwn">2014</A>) Evaluation of heritable determinants of blood and brain serotonin homeostasis using recombinant inbred mice. Genes Brain Behav. 13:247-260 - -<BR> -<BR> -<LI> -Houtkooper RH, Mouchiroud L, Ryu D, Moullan N, Katsyuba E, Knott G, Williams RW, Auwerx J (<A HREF="https://ncbi.nlm.nih.gov/pubmed/23698443" target="_blank" class="fwn">2013</A>) Mitonuclear protein imbalance as a conserved longevity mechanism. Nature 497:451-457 <A HREF="/images/upload/Houtkooper_Williams_Auwerx_Nature_2013.pdf" target="_blank" class="fwn">PDF version</A> - -<BR> -<BR> - -</OL> - -</Blockquote> - - - - - - - - - - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="Key" class="subtitle">Key References</A> -<BLOCKQUOTE > - -<P>The first section lists key technical papers that are appropriate references when citing GeneNetwork and WebQTL. The second section lists publications and other resources that have made use of GeneNetwork.<P> - -</Blockquote> -<OL> - - -<LI> Mulligan MK, Mozhui K, Prins P, Williams RW (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26092713" target="_blank" class="fwn">2016</A>) GeneNetwork – A toolbox for systems genetics. In <I>Systems Genetics</I>, Methods in Molecular Biology; Schughart K, Williams RW eds.; Humana Press, in press -[This is a currently the most comprehensive protocol and guide (20 Mb) for GeneNetwork.] -<SMALL><A HREF="/images/upload/Mulligan_How_To_Use_GeneNetwork_2016_v1.pdf" target="_blank" class="fwn">PDF version</A></SMALL> - - -<LI> -Williams RW, Mulligan MK (<A HREF="https://ncbi.nlm.nih.gov/pubmed/23195314" target="_blank" class="fwn">2012</A>) Genetic and molecular network analysis of behavior. Int Rev Neurobiol. 104:135-57. [Explains the use of GeneNetwork in behavioral neurogenetics] -<SMALL><A HREF="/images/upload/Williams_Mulligan_Bioinformatics of Brain Short 2012.pdf" target="_blank" class="fwn">PDF version</A> -</SMALL> - -<LI> Williams EG, Auwerx J (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26140590" target="_blank" class="fwn">2015</A>) The convergence of systems and reductionist approaches in complex trait analysis. Cell 162:23-32. [Research into the genetic and environmental factors behind complex trait variation has traditionally been segregated into distinct scientific camps. The reductionist approach aims to decrypt phenotypic variability bit by bit, founded on the underlying hypothesis that genome-to-phenome relations are largely constructed from the additive effects of their molecular players. In contrast, the systems approach aims to examine large-scale interactions of many components simultaneously, on the premise that interactions in gene networks can be both linear and non-linear. Both approaches are complementary, and they are becoming increasingly intertwined due to developments in gene editing tools, omics technologies, and population resources. Together, these strategies are beginning to drive the next era in complex trait research, paving the way to improve agriculture and toward more personalized medicine.] <SMALL><A HREF="/images/upload/WilliamsEG_Auwerx_Cell2015.pdf" target="_blank" class="fwn">PDF version</A> -</SMALL> - -<LI> -Wang J, Williams RW, Manly KF (<a href="http://journals.humanapress.com/ArticleDetail.pasp?issn=1539-2791&acode=NI:1:4:299" target="_blank" class="fwn">2003</a>) WebQTL: Web-based complex trait analysis. Neuroinformatics 1: 299-308 <A href="http://www.genenetwork.org/pdf/webqtl.pdf" class="fwn"><I>Full Text PDF Version</I></A>. [A good technical reference to WebQTL and GeneNetwork] -<LI> -Williams RW, Gu J, Qi S, Lu L (<a href="http://journals.humanapress.com/ArticleDetail.pasp?issn=1539-2791&acode=NI:1:4:299" target="_blank" class="fwn">2003</a>) The genetic structure of recombinant inbred mice: high-resolution consensus maps for complex trait analysis. Genome Biology 2(11)<A href="http://genomebiology.com/content/2/11/RESEARCH0046" class="fwn"><I>Full Text Version</I></A>. [A detailed analysis of the genetics of recombinant inbred strains] -<LI> -Chesler EJ, Wang J, Lu L, Qu Y, Manly KF, Williams RW (<a href="http://journals.humanapress.com/ArticleDetail.pasp?issn=1539-2791&acode=NI:1:4:343" target="_blank" class="fwn">2003</a>) Genetic correlates of gene expression in recombinant inbred strains: a relational model to explore for neurobehavioral phenotypes. Neuroinformatics 1: 343-357. <A href="http://www.nervenet.org/pdf/Genetic_Correlation_webQTL.pdf" class="fwn"><I>Full Text PDF Version</I></A>. [Best reference regarding interpretation of genetic correlations.] -<LI> -Chesler EJ, Lu L, Wang J, Williams RW, Manly KF (<a href="http://www.nature.com/cgi-taf/DynaPage.taf?file=/neuro/journal/v7/n5/full/nn0504-485.html" target="_blank" class="fwn">2004</a>) WebQTL: rapid exploratory analysis of gene expression and genetic networks for brain and behavior. Nature Neuroscience 7: 485-486. <A href="http://www.genenetwork.org/pdf/nn0504-485.pdf" class="fwn"><I>Full Text PDF Version</I></A> [A short review] -<LI> -Chesler EJ, Williams RW (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15474587" target="_blank" class="fwn">2004</a>) Brain gene expression: genomics and genetics. International Review of Neurobiology 60:59-95. (<I>DNA Arrays in Neurobiology</I>, edited by MF Miles, Elsevier, Amsterdam). [A longer discussion, both statistical and conceptual, on the genetic analysis of gene expression and relations to higher order behavioral phenotypes]</A> -<LI> -Bystrykh L, Weersing E, Dontje B, Sutton S, Pletcher MT, Wiltshire T, Su AI, Vellenga E, Wang J, Manly KF, Lu L, Chesler EJ, Alberts R, Jansen RC, Williams RW, Cooke M, de Haan G (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15711547" target="_blank" class="fwn">2005</A>) Uncovering regulatory pathways affecting hematopoietic stem cell function using "genetical genomics." Nature Genetics 37:225-232. [Please cite this article if you have used the GNF-Groningen hematopoietic stem cell data set.] -<LI> -Chesler EJ, Lu L, Shou S, Qu Y, Gu J, Wang J, Hsu HC, Mountz JD, Baldwin N, Langston MA, Threadgill DW, Manly KF, Williams RW (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15711545" target="_blank" class="fwn">2005</A>) Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function. Nature Genetics 37: 233-242. [Please cite this article if you have used one of the UTHSC brain data sets.] -<LI> -Damerval C, Maurice A, Josse JM, de Vienne D (<A HREF="http://www.genetics.org/cgi/content/abstract/137/1/289" class="fwn" target="_blank">1994</A>) Quantitative trait loci underlying gene product variation: a novel perspective for analyzing regulation of genome expression. Genetics 137: 289-301 <A href="http://www.genetics.org/cgi/reprint/137/1/289" class="fwn" target="_blank"><I>Full Text PDF Version</I></A> [The first published paper on system genetics. Impressive; before its time.] - -<Blockquote><SMALL>[Damerval et al., 1994 abstract] A methodology to dissect the genetic architecture of quantitative variation of numerous gene products simultaneously is proposed. For each individual of a segregating progeny, proteins extracted from a given organ are separated using two-dimensional electrophoresis, and their amounts are estimated with a computer-assisted system for spot quantification. Provided a complete genetic map is available, statistical procedures allow determination of the number, effects and chromosomal locations of factors controlling the amounts of individual proteins. This approach was applied to anonymous proteins of etiolated coleoptiles of maize, in an F(2) progeny between two distant lines. The genetic map included both restriction fragment length polymorphism and protein markers. Minimum estimates of one to five unlinked regulatory factors were found for 42 of the 72 proteins analyzed, with a large diversity of effects. Dominance and epistasis interactions were involved in the control of 38% and 14% of the 72 proteins, respectively. Such a methodology might help understanding the architecture of regulatory networks and the possible adaptive or phenotypic significance of the polymorphism of the genes involved. -</SMALL></Blockquote> - -<LI> -Grisham W, Schottler NA, Valli-Marill J, Beck L, Beatty J (<a href="http://www.ncbi.nlm.nih.gov/pubmed/20516355" target="_blank" class="fwn" >2010</a>) Teaching bioinformatics and neuroinformatics by using free web-based tools. CBE--Life Sciences Education 9: 98-107 <A href="http://www.lifescied.org/content/9/2/98.full.pdf+html" target="_blank" class="fwn" ><I>Full Text PDF Version</I></A> -<BR><SMALL> A terrific introduction to a wide range of bioinformatic resources, including GeneNetwork, that have been assembled as a coherent teaching module. A detailed student/instructor’s manual, PDFs of handouts, PowerPoint slides, and sample exams are available for free at <A HREF="http://mdcune.psych.ucla.edu/modules/bioinformatics" target="_blank" class="fwn" >http://mdcune.psych.ucla.edu/modules/bioinformatics</A>. - -<BR><B>Youtube videos of Dr. William Grisham teaching neurogenetics at UCLA</B>: -<BR><A HREF="http://www.youtube.com/watch?v=5UniEc_pzs0" target="_blank" class="fwn" >Part 1</A> -<BR><A HREF="http://www.youtube.com/watch?v=zjdOWC7zxt0" target="_blank" class="fwn" >Part 2</A> -<BR><A HREF="http://www.youtube.com/watch?v=caC0YGhDoo8" target="_blank" class="fwn" >Part 3</A> -<BR><A HREF="http://www.youtube.com/watch?v=eTzIcM3aspM" target="_blank" class="fwn">Part 4</A> -<BR><A HREF="http://www.youtube.com/watch?v=Dnq7w4RIAXI" target="_blank" class="fwn">Part 5</A> -</SMALL> -<BR> -<BR> -<LI> -Grisham W (<a href="http://www.funjournal.org/downloads/200981/grisham81.pdf" target="_blank" class="fwn">2009</a>) Modular digitial course in undergraduate neuroscience education (MDCUNE): A website offering free digital tools for neuroscience educators. Journal of Undergraduate Neuroscience Education 8:A26-A31 <A href="http://www.funjournal.org/downloads/200981/grisham81.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<BR><SMALL> -An excellent example of how resources such as GeneNetwork and the Mouse Brain Library can be used in class room labs. -</SMALL> -<LI> -Hübner N, Wallace CA, Zimdahl H, Petretto E, Schulz H, Maciver F, Mueller M, Hummel O, Monti J, Zidek V, Musilova A, Kren V, Causton H, Game L, Born G, Schmidt S, Muller A, Cook SA, Kurtz TW, Whittaker J, Pravenec M, Aitman TJ (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15711544" target="_blank" class="fwn">2005</A>) Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease. Nature Genetics 37: 243-253. [Please cite this article if you have used one of the rat HXB kidney or peritoneal fat data sets.] -<LI> -Kang HM, Ye C, Eskin E (2008) Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots. Genetics 180:1909-1925 -<A href="http://www.genetics.org/cgi/content/abstract/genetics.108.094201v1" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>. [An important method that can greatly improve the ability to resolve true genetic interactions in expression genetic studies.] -<LI> -Ljungberg K, Holmgren S, Carlborg O (<A HREF="http://bioinformatics.oupjournals.org/cgi/content/abstract/bth175?ijkey=21Pp0pgOuBL6Q&keytype=ref" class="fwn" target="_blank">2004</A>) Simultaneous search for multiple QTL using the global optimization algorithm DIRECT. Bioinformatics 20:1887-1895. [Please review and cite this article if you have exploited the DIRECT pair-scan tool and output graphs in WebQTL.] -<LI> -Manly KF, Wang J, Williams RW (<A HREF="http://genomebiology.com/2005/6/3/R27" class="fwn" target="_blank">2005</A>) Weighting by heritability for detection of quantitative trait loci with microarray estimates of gene expression. Genome Biology 6: R27 <A href="http://genomebiology.com/2005/6/3/R27" class="fwn" target="_blank"><I>Full Text HTML and PDF Version</I></A>. [Please cite this article if you have used one of the HWT (Heritability Weighted Transform) data sets.] -<LI> -Manly K, Williams RW (2001) WEBQTL—WWW service for mapping quantitative trait loci. International Mouse Genome Conference 15: 74. [First published abstract on WebQTL, presented Oct 2001, Edinburgh; also see <A HREF="http://www.complextrait.org/archive/2002/HTML/manly.html" class="fwn" target="_blank">2002</A> CTC abstract] -<LI> -Taylor BA, Heiniger HJ, Meier H (<A HREf="http://www.ncbi.nlm.nih.gov/pubmed/4719448">1973</A>) Genetic analysis of resistance to cadmium-induced teticular damage in mice. Proc Soc Exp Biol Med 143:629-33 [This is one of the first full paper on the use of recombinant inbred strains in biomedical research and the first paper to use BXD lines of mice. The <I>cdm</I> locus that they mapped to distal Chr 3 was subsequently defined as the <I>Slc38a8</I> metal testicular metal ion transporter. <A HREF="/images/upload/Taylor_1973.pdf"> Full text</A> -<LI> -Webster JA, Gibbs JR, Clarke J, Ray M, Zhang W, Holmans P, Rohrer K, Zhao A, Marlowe L, Kaleem M, McCorquodale DS 3rd, Cuello C, Leung D, Bryden L, Nath P, Zismann VL, Joshipura K, Huentelman MJ, Hu-Lince D, Coon KD, Craig DW, Pearson JV; NACC-Neuropathology Group, Heward CB, Reiman EM, Stephan D, Hardy J, Myers AJ (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed/19361613" class="fwn" target="_blank">2009</A>) Genetic control of human brain transcript expression in Alzheimer disease. Am J Hum Genet 84:445-58. [Please review and cite this article if you have used the HUMAN data set by Myers and colleagues in GeneNetwork.] -<LI> -Williams RW, Shou S, Lu L, Wang J, Manly KF, Hsu HC, Mountz J, Threadgill DW (<A HREF="http://www.complextrait.org/ctc2002/williams.html" class="fwn" target="_blank">2002</A>) Genomic analysis of transcriptional networks: combining microarrays with complex trait analysis. Complex Trait Consortium 1 [One of the first published abstracts on system genetic analysis of microarray data sets, presented May 2002.] -<LI> -Zhang B, Schmoyer D, Kirov S, Snoddy J (<a href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=14975175" target="_blank" class="fwn">2004</a>) GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies. BMC Bioinformatics 5:16. [This reference describes GOTM--the predecessor of WebGestalt that is now used to analyze sets of covarying transcripts.] - -</OL> -</Blockquote> - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2019" class="subtitle"">GeneNetwork (2019) </A> (not complete) -<BLOCKQUOTE> - -</Blockquote> -<OL> - -<LI> -Théberge ET, Baker JA, Dubose C, Boyle JK, Balce K, Goldowitz D, Hamre KM (<A HREF="https://ncbi.nlm.nih.gov/pubmed/30589433" target="_blank" class="fwn">2019</A>) Genetic influences on the amount of cell death in the neural tube of BXD mice exposed to acute ethanol at midgestation. Alcohol Clin Exp Res 43:439-452 -<LI> -Roy S, Zaman KI, Williams RW, Homayouni R (<A HREF="https://ncbi.nlm.nih.gov/pubmed/30871457" target="_blank" class="fwn">2019</A>) Evaluation of Sirtuin-3 probe quality and co-expressed genes using literature cohesion. BMC Bioinformatics 20(Suppl 2):104 - - -</OL> -</Blockquote> - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2018" class="subtitle"">GeneNetwork (2018) </A> (not complete) -<BLOCKQUOTE> - -</Blockquote> -<OL> - -<LI>Ashbrook DG, Mulligan MK, Williams RW Post-genomic behavioral genetics: From revolution to routine (<A HREF="https://ncbi.nlm.nih.gov/pubmed/29193773" target="_blank" class="fwn">2018</A>) Genes Brain Behav 17:e12441 -<LI> -de Vries M, Faiz A, Woldhuis RR, Postma DS, de Jong TV, Sin DD, Bossé Y, Nickle DC, Guryev V, Timens W, van den Berge M, Brandsma CA (<A HREF="https://ncbi.nlm.nih.gov/pubmed/29212667" target="_blank" class="fwn">2018</A>) Lung tissue gene-expression signature for the ageing lung in COPD. Thorax 73:609-617 -<LI> -Diessler S, Jan M, Emmenegger Y, Guex N, Middleton B, Skene DJ, Ibberson M, Burdet F, Götz L, Pagni M, Sankar M, Liechti R, Hor CN, Xenarios I, Franken P (<A HREF="https://ncbi.nlm.nih.gov/pubmed/30091978" target="_blank" class="fwn">2018</A>) A systems genetics resource and analysis of sleep regulation in the mouse. PLoS Biology 16(8):e2005750 -<LI> -King R, Struebing FL, Li Y, Wang J, Koch AA, Cooke Bailey JN, Gharahkhani P; International Glaucoma Genetics Consortium; NEIGHBORHOOD Consortium, MacGregor S, Allingham RR, Hauser MA, Wiggs JL, Geisert EE (<A HREF="https://ncbi.nlm.nih.gov/pubmed/29370175" target="_blank" class="fwn">2018</A>) Genomic locus modulating corneal thickness in the mouse identifies POU6F2 as a potential risk of developing glaucoma. PLoS Genet 14:e1007145 -<LI> -Lu Y, Zhou D, King R, Zhu S, Simpson CL, Jones BC, Zhang W, Geisert EE, Lu L (<A HREF="https://ncbi.nlm.nih.gov/pubmed/30619460" target="_blank" class="fwn">2018</A>) The genetic dissection of Myo7a gene expression in the retinas of BXD mice. Mol Vis 24:115-126 -<LI> -Struebing FL, King R, Li Y, Cooke Bailey JN; NEIGHBORHOOD consortium, Wiggs JL, Geisert EE (<A HREF="https://ncbi.nlm.nih.gov/pubmed/29421330" target="_blank" class="fwn">2018</A>) Genomic loci modulating retinal ganglion cell death following elevated IOP in the mouse. Exp Eye Res 169:61-67 - - -</OL> -</Blockquote> - - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2017" class="subtitle"">GeneNetwork (2017) </A> (not complete) -<BLOCKQUOTE> - -</Blockquote> -<OL> - -<LI> -Baker JA, Li J, Zhou D, Yang M, Cook MN, Jones BC, Mulligan MK, Hamre KM, Lu L (<A HREF="https://ncbi.nlm.nih.gov/pubmed/28027852" target="_blank" class="fwn">2017</A>) Analyses of differentially expressed genes after exposure to acute stress, acute ethanol, or a combination of both in mice. Alcohol 58:139-151 -<LI> -Baud A, Mulligan MK, Casale FP, Ingels JF, Bohl CJ, Callebert J, Launay JM, Krohn J, Legarra A, Williams RW, Stegle O (<A HREF="https://ncbi.nlm.nih.gov/pubmed/28121987" target="_blank" class="fwn">2017</A>) Genetic variation in the social environment contributes to health and disease. PLoS Genet 13(1):e1006498 -<LI>Brockmann GA, Arends D, Heise S, Dogan A (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27933540" target="_blank" class="fwn">2017</A>) Systems genetics of obesity. Methods Mol Biol. 2017;1488:481-497 -<LI> -Grisham W, Brumberg JC, Gilbert T, Lanyon L, Williams RW, Olivo R (<A HREF="https://ncbi.nlm.nih.gov/pubmed/29371844" target="_blank" class="fwn">2017</A>) Teaching with Big Data: Report from the 2016 Society for Neuroscience Teaching Workshop. J Undergrad Neurosci Educ 16:A68-A76 -<LI> - -Jones BC, Jellen LC (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27933539" target="_blank" class="fwn">2017</A>) Systems genetics analysis of iron and its regulation in brain and periphery. Methods Mol Biol 1488:467-480 -<LI> -Lopez MF, Miles MF, Williams RW, Becker HC (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27793543" target="_blank" class="fwn">2017</A>) Variable effects of chronic intermittent ethanol exposure on ethanol drinking in a genetically diverse mouse cohort. Alcohol 58:73-82 -<LI> -Parker CC, Dickson PE, Philip VM, Thomas M, Chesler EJ (<A HREF="https://ncbi.nlm.nih.gov/pubmed/28398643" target="_blank" class="fwn">2017</A>) Curr Protoc Neurosci 79:8.39.1-8.39.20 -<LI> -Porcu P, O'Buckley TK, Lopez MF, Becker HC, Miles MF, Williams RW, Morrow AL (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27884493" target="_blank" class="fwn">2017</A>) Initial genetic dissection of serum neuroactive steroids following chronic intermittent ethanol across BXD mouse strains. Alcohol 58:107-125 -<LI> -Rinker JA, Fulmer DB, Trantham-Davidson H, Smith ML, Williams RW, Lopez MF, Randall PK, Chandler LJ, Miles MF, Becker HC, Mulholland PJ (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27884493" target="_blank" class="fwn">2017</A>) Differential potassium channel gene regulation in BXD mice reveals novel targets for pharmacogenetic therapies to reduce heavy alcohol drinking. Alcohol 58:33-45 -<LI> -van der Vaart AD, Wolstenholme JT, Smith ML, Harris GM, Lopez MF, Wolen AR, Becker HC, Williams RW, Miles MF (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27838001" target="_blank" class="fwn">2017</A>) The allostatic impact of chronic ethanol on gene expression: A genetic analysis of chronic intermittent ethanol treatment in the BXD cohort. Alcohol 58:93-106 - - -</OL> -</Blockquote> - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2016" class="subtitle"">GeneNetwork (2016) </A> -<BLOCKQUOTE> - -</Blockquote> -<OL> - -<LI> -Alam G, Miller DB, O'Callaghan JP, Lu L, Williams RW, Jones BC (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27182044" target="_blank" class="fwn">2016</A>) MPTP neurotoxicity is highly concordant between the sexes among BXD recombinant inbred mouse strains. Neurotoxicology 55:40-7 -<LI> -Chintalapudi SR, Wang X, Li H, Lau YH, Williams RW, Jablonski MM (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27881906" target="_blank" class="fwn">2016</A>) Genetic and immunohistochemical analysis of HSPA5 in mouse and human retinas. Molecular Vision 22:1318-1331 -<LI> -Lu H, Lu L, Williams RW, Jablonski MM (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27011731" target="_blank" class="fwn">2016</A>) Iris transillumination defect and its gene modulators do not correlate with intraocular pressure in the BXD family of mice. Molecular Vision 22:224-233 -<LI> -Merkwirth C, Jovaisaite V, Durieux J, Matilainen O, Jordan SD, Quiros PM, Steffen KK, Williams EG, Mouchiroud L, Tronnes SU, Murillo V, Wolff SC, Shaw RJ, Auwerx J, Dillin A (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27133168" target="_blank" class="fwn">2016</A>) Two conserved histone demethylases regulate mitochondrial stress-induced longevity. Cell 165:1209-1223 -<LI> -Neuner SM, Garfinkel BP, Wilmott LA, Ignatowska-Jankowska BM, Citri A, Orly J, Lu L, Overall RW, Mulligan MK, Kempermann G, Williams RW, O'Connell KM, Kaczorowski CC (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27460150" target="_blank" class="fwn">2016</A>) Systems genetics identifies Hp1bp3 as a novel modulator of cognitive aging. Neurobiol Aging 46:58-67 -<LI> -Shi X, Walter NA, Harkness JH, Neve KA, Williams RW, Lu L, Belknap JK, Eshleman AJ, Phillips TJ, Janowsky A (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27031617" target="_blank" class="fwn">2016</A>) Genetic polymorphisms affect mouse and human Trace Amine-Associated Receptor 1 function. PLoS One 11(3):e0152581 -<LI> -Schultz NG, Ingels J, Hillhouse A, Wardwell K, Chang PL, Cheverud JM, Lutz C, Lu L, Williams RW, Dean MD (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26935419" target="_blank" class="fwn">2016</A>) The genetic basis of baculum size and shape variation in mice. G3 (Bethesda) 6(5):1141-1151 -<LI> -Sloan Z, Arends D, Broman KW, Centeno A, Furlotte N, Nijveen H, Yan L, Zhou X, Williams RW, Prins P (2016) GenetNetwork: framework for web-based genetics. The Journal of Open Source Software http://joss.theoj.org/papers/10.21105/joss.00025 (http://dx.doi.org/10.21105/joss.00025) -<LI> -Wang X, Pandey AK, Mulligan MK, Williams EG, Mozhui K, Li Z, Jovaisaite V, Quarles LD, Xiao Z, Huang J, Capra JA, Chen Z, Taylor WL, Bastarache L, Niu X, Pollard KS, Ciobanu DC, Reznik AO, Tishkov AV, Zhulin IB, Peng J, Nelson SF, Denny JC, Auwerx J, Lu L, Williams RW (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26833085" target="_blank" class="fwn">2016</A>) Joint mouse-human phenome-wide association to test gene function and disease risk. Nat Commun 7:10464 - <LI> -Williams EG, Wu Y, Jha P, Dubuis S, Blattmann P, Argmann CA, Houten SM, Amariuta T, Wolski W, Zamboni N, Aebersold R, Auwerx J (<A HREF="https://ncbi.nlm.nih.gov/pubmed/27284200" target="_blank" class="fwn">2016</A>) Systems proteomics of liver mitochondria function. Science 352(6291):aad0189 - - - -</OL> -</Blockquote> - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2015" class="subtitle"">GeneNetwork (2015) </A> -<BLOCKQUOTE> - -</Blockquote> -<OL> - -<LI> -Ashbrook DG, Gini B, Hager R (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26701914" target="_blank" class="fwn">2015</A>) Genetic variation in offspring indirectly influences the quality of maternal behaviour in mice. eLIFE 4:e11814 -<LI> -Ashbrook DG, Williams RW, Lu L, Hager R (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26190982" target="_blank" class="fwn">2015</A>) A cross-species genetic analysis identifies candidate genes for mouse anxiety and human bipolar disorder. Frontiers in Behavioral Neuroscience 9:171 -<LI> -Chaum E, Winborn CS, Bhattacharya S (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25963977" target="_blank" class="fwn">2015</A>) Genomic regulation of senescence and innate immunity signaling in the retinal pigment epithelium. Mammalian Genome 26:210-221 <A HREF="/images/upload/ChaumMammGenome2015.pdf"> Full text</A> -<LI> -Cheng Q, Seltzer Z, Sima C, Lakschevitz FS, Glogauer M (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25608512" target="_blank" class="fwn">2015</A>) Quantitative trait loci and candidate genes for neutrophil recruitment in sterile inflammation mapped in AXB-BXA recombinant inbred mice. PLoS One 10:e0124117 -<LI> -Cook MN, Baker JA, Heldt SA, Williams RW, Hamre KM, Lu L (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25991709" target="_blank" class="fwn">2015</A>) Identification of candidate genes that underlie the QTL on chromosome 1 that mediates genetic differences in stress-ethanol interactions. Physiol Genomics 47:308-317 -<LI> -Delprato A, Bonheur B, Algéo MP, Rosay P, Lu L, Williams RW, Crusio WE (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26449520" target="_blank" class="fwn">2015</A>) Systems genetic analysis of hippocampal neuroanatomy and spatial learning in mice. Genes Brain Behav 14(8):591-606 -<LI> -Ferguson B, Ram R, Handoko HY, Mukhopadhyay P, Muller HK, Soyer HP, Morahan G, Walker GJ (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25088201" target="_blank" class="fwn">2015</A>) Melanoma susceptibility as a complex trait: genetic variation controls all stages of tumor progression. Oncogene 34:2879-86 -<LI> -King R, Lu L, Williams RW, Geisert EE. (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26604663" target="_blank" class="fwn">2015</A>) Transcriptome networks in the mouse retina: An exon level BXD RI database. Mol Vis 21:1235-1251 -<LI> -Lee J, Seol MY, Jeong S, Kwon HJ, Lee CR, Ku CR, Kang SW, Jeong JJ, Shin DY, Nam KH, Lee EJ, Chung WY, Jo YS (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25942439" target="_blank" class="fwn">2015</A>) KSR1 is coordinately regulated with Notch signaling and oxidative phosphorylation in thyroid cancer. J Mol Endocrinol 54:115-124 -<LI> -Padula AE, Griffin WC 3rd, Lopez MF, Nimitvilai S, Cannady R, McGuier NS, Chesler EJ, Miles MF, Williams RW, Randall PK, Woodward JJ, Becker HC, Mulholland PJ (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25942439" target="_blank" class="fwn">2015</A>) KCNN genes that encode small-conductance Ca(2+)-activated K(+) channels influence alcohol and drug addiction. Neuropsychopharmacology 40:1928-1939 -<LI> -Scott RE, Ghule PN, Stein JL, Stein GS (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25662840" target="_blank" class="fwn">2015</A>) Cell cycle gene expression networks discovered using systems biology: Significance in carcinogenesis. J Cell Physiol 230:2533-42 -<LI> -Shea CJ, Carhuatanta KA, Wagner J, Bechmann N, Moore R, Herman JP, Jankord R (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26079812" target="_blank" class="fwn">2015</A>) Variable impact of chronic stress on spatial learning and memory in BXD mice. Physiol Behav. 150:69-77 <A HREF="http://www.sciencedirect.com/science/article/pii/S0031938415003583"> Full text</A> -<LI> -Xue Y, Li J, Yan L, Lu L, Liao FF (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26092713" target="_blank" class="fwn">2015</A>) Genetic variability to diet-induced hippocampal dysfunction in BXD recombinant inbred (RI) mouse strains. Behav Brain Res 292:83-94 -<LI> -Williams EG, Auwerx J (<A HREF="https://ncbi.nlm.nih.gov/pubmed/26140590" target="_blank" class="fwn">2015</A>) The convergence of systems and reductionist approaches in complex trait analysis. Cell 162:23-32. <SMALL><A HREF="/images/upload/WilliamsEG_Auwerx_Cell2015.pdf" target="_blank" class="fwn">PDF version</A></SMALL> - - -</OL> -</Blockquote> - - - - - - - - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2014" class="subtitle"">GeneNetwork (2014) </A> -<BLOCKQUOTE> - -</Blockquote> -<OL> - - -<LI> -Ashbrook GN, Delprato A, Grellmann C, Klein M, Wetzel R, Overall RW, Badea A (<A HREF="https://ncbi.nlm.nih.gov/pubmed/get" target="_blank" class="fwn">2014</A>) Transcript co-variance with Nestin in two mouse genetic reference populations identifies Lef1 as a novel candidate regulator of neural precursor cell proliferation in the adult hippocampus. Frontiers in Neuroscience in press -<LI> -Ashbrook DG, Williams RW, Lu L, Stein JL, Hibar DP, Nichols TE, Medland SE, Thompson PM, Hager R. (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25280473" target="_blank" class="fwn">2014</A>) Joint genetic analysis of hippocampal size in mouse and human identifies a novel gene linked to neurodegenerative disease. BMC Genomics 15:850 -<LI> -Carhuatanta KA, Shea CJ, Herman JP, Jankord R (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25374516" target="_blank" class="fwn">2014</A>) Unique genetic loci identified for emotional behavior in control and chronic stress conditions. Front Behav Neurosci 8:341 -<LI> -Emery FD, Parvathareddy J, Pandey AK, Cui Y, Williams RW, Miller MA (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24687986" target="_blank" class="fwn">2014</A>) Genetic control of weight loss during pneumonic Burkholderia pseudomallei infection. Pathog Dis 71:249-264 -<LI> -Goldowitz D, Lussier AA, Boyle JK, Wong K, Lattimer SL, Dubose C, Lu L, Kobor MS, Hamre KM (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25076964" target="_blank" class="fwn">2014</A>) Molecular pathways underpinning ethanol-induced neurodegeneration. Front Genet 5:203 -<LI> -Graybeal C, Bachu M, Mozhui K, Saksida LM, Bussey TJ, Sagalyn E, Williams RW, Holmes A (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24586288" target="_blank" class="fwn">2014</A>) Strains and stressors: an analysis of touchscreen learning in genetically diverse mouse strains. PLoS One 9(2):e87745 -<LI> -Hall RA, Liebe R, Hochrath K, Kazakov A, Alberts R, Laufs U, Böhm M, Fischer HP, Williams RW, Schughart K, Weber SN, Lammert F (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24586654" target="_blank" class="fwn">2014</A>) Systems genetics of liver fibrosis: Identification of fibrogenic and expression quantitative trait loci in the BXD murine reference population.PLoS One 9(2):e89279 -<LI> -Harenza JL, Muldoon PP, Biasi MD, Imad Damaj M, Miles MF (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24289814" target="_blank" class="fwn">2014</A>) Genetic variation within the Chrna7 gene modulates nicotine reward-like phenotypes in mice. Genes, Brain & Behavior 13:213-225 -<LI> -Hayes SK, Hager R, Grencis RK (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24628794" target="_blank" class="fwn">2014</A>) Sex-dependent genetics effects on immune responses to parasitic nematodes. BMC Genomics 15:193 -<LI> -Huang Y, Zhu X, Wang L, Liu X, Lu L, Gu W, Jiao Y (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25133246" target="_blank" class="fwn">2014</A>) Genome wide analysis of sex difference in gene expression profiles of bone formations using sfx mice and BXD RI strains. ScientificWorldJournal 2014:584910 -<LI> -Hasenfuss SC, Bakiri L, Thomsen MK, Williams EG, Auwerx J, Wagner EF (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24411941" target="_blank" class="fwn">2014</A>) Regulation of steatohepatitis and PPARγ signaling by distinct AP-1 dimers. Cell Metab. 2014 Jan 7;19(1):84-95. -<LI> -Jones BC, O'Callaghan JP, Lu L, Williams RW, Alam G, Miller DB (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25192776" target="_blank" class="fwn">2014</A>) Genetic correlational analysis reveals no association between MPP+ and the severity of striatal dopaminergic damage following MPTP treatment in BXD mouse strains. Neurotoxicol Teratol pii: S0892-0362(14)00159-7 -<LI> -Keeley PW, Whitney IE, Madsen NR, St John AJ, Borhanian S, Leong SA, Williams RW, Reese BE (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24954025" target="_blank" class="fwn">2014</A>) Independent genomic control of neuronal number across retinal cell types. Dev Cell 30:103-109 -<LI> -Keeley PW, Zhou C, Lu L, Williams RW, Melmed S, Reese BE (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24927528" target="_blank" class="fwn">2014</A>) Pituitary tumor-transforming gene 1 regulates the patterning of retinal mosaics. Proc Natl Acad Sci USA 111:9295- -<LI> -Kweon KH, Lee CR, Jung SJ, Ban EJ, Kang SW, Jeong JJ, Nam KH, Jo YS, Lee J, Chung WY (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25109285" target="_blank" class="fwn">2014</A>) Sirt1 induction confers resistance to etoposide-induced genotoxic apoptosis in thyroid cancers. Int J Oncol 45:2065-2075 -<LI> -Loos M, Mueller T, Gouwenberg Y, Wijnands R, van der Loo RJ, Birchmeier C, Smit AB, Spijker S (<A HREF="/images/upload/Loos_Spijker_Nrg3Impulsive_BioPsch_2014.pdf" target="_blank" class="fwn">2014</A>) Neuregulin-3 in the mouse medial prefrontal cortex regulates impulsive action. Biol Psychiatry 76:648-655 -<LI> -Lotan A, Fenckova M, Fralten J, Alttoa A, Dixson L, Williams RW, van der Voet M (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25414627" target="_blank" class="fwn">2014</A>) Neuroinformatic analyses of common and distinct genetic components associate with major neuropsychiatric disorders. Frontiers in Neuroscience 8:331 -<LI> -McLachlan SM, Aliesky H, Banuelos B, Magana J, Williams RW, Rapoport B. (<A HREF="https://ncbi.nlm.nih.gov/pubmed/25051451" target="_blank" class="fwn">2014</A>) Immunoglobulin heavy chain variable region and major histocompatibility region genes are linked to induced graves' disease in females from two very large families of recombinant inbred mice. Endocrinology 155:4094-4103 -<LI> -McLachlan SM, Hamidi S, Aliesky H, Williams RW, Rapoport B (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24564389" target="_blank" class="fwn">2014</A>) Sex, genetics and the control of thyroxine and thyrotropin in mice. Thyroid 24:1080-1087 -<LI> -Muldoon PP, Jackson KJ, Perez E, Harenza JL, Molas S, Rais B, Anwar H, Zaveri NT, Maldonado R, Maskos U, McIntosh JM, Dierssen M, Miles MF, Chen X, De Biasi M, Damaj MI (<A HREF="https://ncbi.nlm.nih.gov/pubmed/24750073" target="_blank" class="fwn">2014</A>) The alpha3beta4* nicotinic ACh receptor subtype mediates physical dependence to morphine: mouse and human studies. 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Invest Ophthalmol Vis Sci. 52:4132-4142 -<LI> -McLachlan SM, Aliesky HA, Chen CR, Williams RW, Rapoport B (<a href="http://www.ncbi.nlm.nih.gov/pubmed/21738647" target="_blank" class="fwn">2011</a>) Exceptional Hyperthyroidism and a role for both major histocompatibility class I and class II genes in a murine model of Graves' disease. PLoS One 6:e21378 -<LI> -McLachlan SM, Lu L, Aliesky HA, Williams RW, Rapoport B (<a href="http://www.ncbi.nlm.nih.gov/pubmed/21209025" target="_blank" class="fwn">2011</a>) Distinct genetic signatures for variability in total and free serum thyroxine levels in four sets of recombinant inbred mice. Endocrinology 152:1172-9 -<LI> -McCall RD (<a href="http://www.ncbi.nlm.nih.gov/pubmed/21384758" target="_blank" class="fwn">2011</a>) HPNS seizure risk: a role for the Golgi-associated retrograde protein complex? 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PhD diss., University of Tennessee <a href="http://trace.tennessee.edu/utk_graddiss/727" target="_blank" class="fwn" >http://trace.tennessee.edu/utk_graddiss/727</a> -<LI> -Malkki HA, Donga LA, de Groot SE, Battaglia FP; NeuroBSIK Mouse Phenomics Consortium, Pennartz CM (<a href="http://www.ncbi.nlm.nih.gov/pubmed/21119771" target="_blank" class="fwn" >2010</a>) Appetitive operant conditioning in mice: heritability and dissociability of training stages. Front Behav Neuroscience 4:171 <A href="/images/upload/BXD_immunophenotypes_2010.pdf" target="_blank" class="fwn" ><I>Full Text PDF version</I> </A> -<LI> -Mulligan MK, Lu L, Overall RW, Kempermann G, Rogers GL, Langston MA, Williams RW (<a href="http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5510847" target="_blank" class="fwn" >2010</a>) Genetic analysis of BDNF expression cliques and adult neurogenesis in the hippocampus. Biomedical Sciences and Engineering Conference (BSEC) DOI: 10.1109/BSEC.2010.5510848 <A href="/images/upload/BDNF_Clique_Apr13.pdf" target="_blank" class="fwn" ><I>Full Text PDF version</I> </A> -<LI> -Peidis P, Giannakouros T, Burow ME, Williams RW, Scott RE (<a href="http://www.ncbi.nlm.nih.gov/pubmed/20184719" target="_blank" class="fwn" >2010</a>) Systems genetics analyses predict a transcription role for P2P-R: molecular confirmation that P2P-R is a transcriptional co-repressor. BMC Systems Biology 4:14 <A href="http://www.biomedcentral.com/content/pdf/1752-0509-4-14.pdf" target="_blank" class="fwn" ><I>Full Text PDF version</I> and </A> -<LI> -Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Laviviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19958391" target="_blank" class="fwn">2010</a>) High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strains. 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Journal of Undergraduate Neuroscience Education 8:A26-A31 <A href="http://www.funjournal.org/downloads/200981/grisham81.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<BR><SMALL> -An excellent example of how resources such as GeneNetwork and the Mouse Brain Library can be used in class room labs. -</SMALL> -<LI> -Jellen LC, Beard JL, Jones BC (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19393285" target="_blank" class="fwn">2009</a>) Systems genetics analysis of iron regulation. Biochemie in press. -19393285 -<LI> -Koutnikova H, Markku L, Lu L, Combe R, Paananen J, Kuulasmaa T, Kuusisto J, Häring H, Hansen T, Pedersen,O, Smith U, Hanefel M, Williams RW, Auwerx J (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19662162" target="_blank" class="fwn">2009</a>) Identification of UBP1 as a critical blood pressure determinant. PLoS Genetics 5:e1000591 -<A href="http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1000591" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>, -<A HREF="http://www.plosgenetics.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pgen.1000591&representation=PDF" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Michaelson JJ, Loguercio S, Beyer A (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19303049" target="_blank" class="fwn">2009</a>) Detection and interpretation of expression quantitative trait loci (eQTL). Methods 48:265-276 -<A href="http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WN5-4VVXSVN-2&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1065487428&_rerunOrigin=google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=df0a2763fb94c714825793af492de045" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (<a href="http://www.ncbi.nlm.nih.gov/pubmed/20582282" target="_blank" class="fwn">2009</a>) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Frontiers in Neuroscience 3:55 -<A href="http://www.frontiersin.org/neurogenomics/10.3389/neuro.15.003.2009/full" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>, -<A HREF="javascript:__doPostBack('ctl00$ContentAreaRightMenu$ArchiveRightMenu$lnkPDF','')" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Overton JD, Adams GS, McCall RD, Kinsey ST (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19100334" target="_blank" class="fwn">2009</a>)High energy phosphate concentrations and AMPK phosphorylation in skeletal muscle from mice with inherited differences in hypoxic exercise tolerance. Comp Biochem Physiol A Mol Integr Physiol 152:478-85 -<LI> -Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Laviviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19958391" target="_blank" class="fwn">2009</a>) High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strains. Genes, Brain and Behavior 8:in press PMID: 19958391 <A href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2855868/" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Ruden DM, Chen L, Possidente D, Possidente B, Rasouli P, Wang L, Lu X, Garfinkel MD, Hirsch HV, Page GP (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19737576" target="_blank" class="fwn">2009</a>) Genetical toxicogenomics in Drosophila identifies master-modulatory loci that are regulated by developmental exposure to lead. Neurotoxicology 30:898-914 -<LI> -Rosen GL, Pung C, Owens C, Caplow J, Kim H, Lu L, Williams RW (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19191878" target="_blank" class="fwn">2009</a>) Genetic modulation of striatal volume in BXD recombinant inbred mice. Genes, Brain & Behavior 8:296-308 -<LI> -Saccone SF, Bierut LJ, Chesler EJ, Kalivas PW, Lerman C, Saccone NL, Uhl GR, Li CY, Philip VM, Edenberg HJ, Sherry ST, Feolo M, Moyzis RK, Rutter JL (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19381300" target="_blank" class="fwn">2009</a>) Supplementing high-density SNP microarrays for additional coverage of disease-related genes: addiction as a paradigm. PLoS ONE 4:e5225. <A href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0005225" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>, -<A HREF=http://www.plosone.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pone.0005225&representation=PDF" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>. [Supplementary table 1 provides links to many transcripts and genes, some of which were mined from an analysis of GeneNetwork data sets.] -<LI> -Silva GL, Junta CM, Sakamoto-Hojo ET, Donadi EA, Louzada-Junior P, Passos GA (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19758195" target="_blank" class="fwn">2009</a>) Genetic susceptibility loci in rheumatoid arthritis establish transcriptional regulatory networks with other genes. Ann N Y Acad Sci 1173:521-37 -<LI> -Tapocik JD, Letwin N, Mayo CL, Frank B, Luu T, Achinike O, House C, Williams R, Elmer GI, Lee NH (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19386926" target="_blank" class="fwn">2009</a>) Identification of candidate genes and gene networks specifically associated with analgesic tolerance to morphine. J Neurosci 2:5295-307 <A href="http://www.jneurosci.org/cgi/content/full/29/16/5295" target="_blank" class="fwn"><I>Full Text HTML</I></A> -<LI> -Thomas C, Gioiello A, Noriega L, Strehle A, Oury J, Rizzo G, Macchiarulo A, Yamamoto H, Mataki C, Pruzanski M, Pellicciari R, Auwerx J, Schoonjans K (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19723493" target="_blank" class="fwn">2009</a>) TGR5-mediated bile acid sensing controls glucose homeostasis. Cell Metab 10:167-77 -<A href="http://www.genenetwork.org/images/upload/Thomas_Auwerx_2009.pdf" target="_blank" class="fwn"><I>Full Text PDF</I></A> -<LI> -Webb BT, McClay JL, Vargas-Irwin C, York TP, van den Oord EJCG (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19723493" target="_blank" class="fwn">2009</a>) In silico whole genome association scan for murine prepulse inhibition. PLoS ONE 4: e5246. doi:10.1371/journal.pone.0005246 -<A href="http://www.plosone.org/article/info:doi%2F10.1371%2Fjournal.pone.0005246" target="_blank" class="fwn"><I>Full Text HTML</I></A>, -<A href="http://www.plosone.org/article/fetchObjectAttachment.action;jsessionid=18CBF1DF825C97C45A98D0256635C650?uri=info%3Adoi%2F10.1371%2Fjournal.pone.0005246&representation=PDF" target="_blank" class="fwn"><I>Full Text HTML</I></A> -<LI> -Weng J, Symons MN, Singh SM (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19107586" target="_blank" class="fwn">2009</a>) Studies on syntaxin 12 and alcohol preference involving C57BL/6J and DBA/2J strains of mice. Behav Genet. 39:183-191 -<A href="http://www.iovs.org/cgi/content/abstract/50/5/1996" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Whitney IE, Raven MA, Ciobanu DC, Williams RW, Reese BE (<a href="http://www.iovs.org/cgi/content/abstract/50/5/1996" target="_blank" class="fwn">2009</a>) Multiple genes on chromosome 7 regulate dopaminergic amacrine cell number in the mouse. Investigative Ophthalmology & Visual Science 50:1996-2003. -<A href="http://www.iovs.org/cgi/content/abstract/50/5/1996" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. -<LI> -Wu S, Lusis AJ, Drake TA (<a href="http://www.jlr.org/cgi/reprint/R800067-JLR200v1.pdf" target="_blank" class="fwn">2009</a>) A systems-based framework for understanding complex metabolic and cardiovascular disorders. Journal of Lipid Research, in press <A href="http://www.jlr.org/cgi/reprint/R800067-JLR200v1.pdf" target="_blank" class="fwn"><I>Full Text PDF</I></A> -<LI> -Zheng QY, Ding D, Yu H, Salvi RJ, Johnson KR (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18280008" target="_blank" class="fwn">2009</a>) A locus on distal chromosome 10 (<I>ahl4</I>) affecting age-related hearing loss in A/J mice. Neurobiol Aging. 2009 Oct;30(10):1693-705. - -</OL> -</Blockquote> - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2008" class="subtitle"">GeneNetwork (2008) </A> -<BLOCKQUOTE> - -</Blockquote> -<OL> -<LI> -Abdeltawab NF, Aziz RK, Kansal R, Rowe SL, Su Y, Gardner L, Brannen C, Nooh MM, Attia RR, Abdelsamed HA, Taylor WL, Williams RW, Kotb M (2008) An unbiased systems genetics approach to mapping genetic loci modulating susceptibility to severe streptococcal sepsis. PLoS Pathogens 4:e1000042 -<A href="http://www.plospathogens.org/article/info%3Adoi%2F10.1371%2Fjournal.ppat.1000042" target="_blank" class="fwn"><I>Full Text HTML Version</I>, -<A href="http://www.plospathogens.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.ppat.1000042&representation=PDF" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> - -<LI> -Bertrand L, Fan Y, Nissanov J, Rioux L (2008) Genetic regulation of the anatomy of the olfactory bulb. Society for Neuroscience <A HREF="http://www.sfn.org/skins/main/pdf/abstracts/am2008/poster_presentations/tuesday_pm.pdf" target="_blank" class="fwn">2008</A> - -<!-- -Abstract: Development of the nervous system results from an interaction between environmental and genetic factors. Neurodevelopmental diseases with a strong genetic etiology like schizophrenia and autism are associated with functional and structural abnormalities in various areas of the brain, including the olfactory system. Because these diseases are characterized by numerous subjective symptoms, research has begun to identify objectively measurable symptomatology; these quantitative traits are called endophenotypes. One such trait associated with schizophrenia is abnormality of the olfactory bulb (OB). We sought to model the structural aspect of OB abnormalities by examining strain variability of OB volumes in mice. Through the analysis of parental strains, C57BL/6J (B6) and DBA/2J (D2), as well as 35 BXD recombinant inbred strains, mapping of a quantitative trait locus (QTL) associated with OB variability could be the first step in the identification of potential genes correlated with this -olfactory endophenotype. Our study was conducted entirely in silico through the use of the Mouse Brain Library (www.mbl.org), imaging analysis softwares (NIH Object Image, Skill Image and Matlab), and a web-based QTL analysis tool (www.webqtl.org). 4 um/pixel images of sectioned mouse brains (300 um apart) were downloaded from the MBL website. The sample included 11 B6, 8 D2, and 157 BXDs mice. The OB consists of concentric layers: olfactory nerve, glomerular, plexiform, mitral cell and granule cell layers. The main OB and its layers were delineated and their volume was estimated using Cavalieri formula. Results show that B6 main OB volume is larger than that of D2. While the olfactory neuron and glomerular layers are larger in B6, the external plexiform and granular layers are larger in D2. This suggests that the development of the various OB layers is modulated by different genes. Residual volumes were calculated by removal of variance attributed to age and sex. Using the web-based QTL analysis tool, main OB volume was mapped to a significant linkage peak on chromosome 16. This QTL contains genes controlling the development of the main OB and potential candidate genes for schizophrenia. Determination of QTLs for individual layers is in progress. ---> - - -<LI> -Bhoumik A, Singha N, O'Connell MJ, Ronai ZA (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18397884" target="_blank" class="fwn">2008</a>) Regulation of TIP60 by ATF2 modulates ATM activation. J Biol Chem 283:17605-14 -<A href="http://www.jbc.org/content/283/25/17605.long" target="_blank" class="fwn"><I>Full Text HTML Version</I>, <http://www.jbc.org/content/early/2008/04/08/jbc.M802030200.full.pdf -" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> - - - -<LI> -Bjork K, Rimondini R, Hansson AC, Terasmaa A, Hyytiä P, Heilig M, Sommer WH (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18367649" target="_blank" class="fwn">2008</a>) Modulation of voluntary ethanol consumption by beta-arrestin 2. FASEB J 22:2552-60 -<A href="http://www.fasebj.org/cgi/content/full/22/7/2552" target="_blank" class="fwn"><I>Full Text HTML Version</I>, -<A href="http://www.fasebj.org/cgi/reprint/22/7/2552.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Boone EM, Hawks BW, Li W, Garlow SJ (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18199428" target="_blank" class="fwn">2008</a>) Genetic regulation of hypothalamic cocaine and amphetamine-regulated transcript (CART) in BxD inbred mice. Brain Res 1194:1-7 -<LI> -Crawford NP, Alsarraj J, Lukes L, Walker RC, Officewala JS, Yang HH, Lee MP, Ozato K, Hunter KW (2008) Bromodomain 4 activation predicts breast cancer survival. Proc Natl Acad Sci USA 105:6380-6385 -<A href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=18427120" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Crawford NP, Walker RC, Lukes L, Officewala JS, Williams RW, Hunter KW (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18301994 -" target="_blank" class="fwn">2008</a>) The Diasporin Pathway: a tumor progression-related transcriptional network that predicts breast cancer survival. Clin Exp Metastasis 25:357-69 -<A href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=18301994" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Danciger M, Ogando D, Yang H, Matthes MT, Yu N, Ahern K, Yasumura D, Williams RW, Lavail MM (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18344445 -" target="_blank" class="fwn">2008</a>) Genetic modifiers of retinal degeneration in the <I>rd3</I> mouse. Invest Ophthalmol Vis Sci 49:2863-2869 -<A href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=18344445" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Druka A, Druka I, Centeno AG, Li H, Sun Z, Thomas WT, Bonar N, Steffenson BJ, Ullrich SE, Kleinhofs A, Wise RP, Close TJ, Potokina E, Luo Z, Wagner C, Schweizer GF, Marshall DF, Kearsey MJ, Williams RW, Waugh R (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19017390 -" target="_blank" class="fwn">2008</a>) Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork. BMC Genet 9:73 -<A href="http://www.biomedcentral.com/1471-2156/9/73" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Dykstra B, de Haan G (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18008087 -" target="_blank" class="fwn">2008</a>) Hematopoietic stem cell aging and self-renewal. Cell Tissue Res 331:91-101 -<LI> -Ferrara CT, Wang P, Neta EC, Stevenes RD, Bain JR, Wenner BR, Ilkayeva OR, Keller MP, Blasiole DA, Kendziorski C, Yandell BS, Newgard CB, Attie AD (2008) Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling. PLoS Genetics 4: e1000034. doi:10.1371/journal.pgen.1000034 -<A href="http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1000034" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Gerrits A, Dykstra B, Otten M, Bystrykh L, de Haan G (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18560825 -" target="_blank" class="fwn">2008</a>) Combining transcriptional profiling and genetic linkage analysis to uncover gene networks operating in hematopoietic stem cells and their progeny. Immunogenetics. 60:411-22. -<LI> -Grieve IC, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19112506" target="_blank" class="fwn">2008</a>) Genome-wide co-expression analysis in multiple tissues. PLoS One. 3:e4033. PMID: 19706712 <A href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0004033" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>, -<A HREF="http://www.plosone.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pone.0004033&representation=PDF" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Hall R, Hillebrandt S, Hochrath K, Gruenhage F, Weber S, Schwartz S, Yildiz Y , Sauerbruch T, Lammert F (2008) BXD recombinant inbred mouse lines–a genetic reference population for dissection of the complex genetics of liver fibrosis. Zeitschrift fur Gastroenterologie 46:in press -<A href="http://www.thieme-connect.com/ejournals/abstract/zfg/doi/10.1055/s-2008-1037508" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Han B, Altman NS, Mong JA, Klein LC, Pfaff DW, Vandenbergh DJ (2008) Comparing quantitative trait loci and gene expression data. Advances in Bioinformatics, doi:10.1155/2008/719818. -<A href="http://hindawi.com/RecentlyAcceptedArticlePDF.aspx?journal=ABI&number=719818" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> and <A href="http://www.hindawi.com/journals/abi/2008/719818.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Hayat Y, Yang J, Xu HM, Zhu J (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19067460 -" target="_blank" class="fwn">2008</a>) Influence of outliers on QTL mapping for complex traits. J Zhejiang Univ Sci B. 9:931-7 -<LI> -Heimel JA, Hermans JM, Sommeijer JP; Neuro-Bsik Mouse Phenomics consortium, Levelt CN (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18700840 -" target="_blank" class="fwn">2008</a>) Genetic control of experience-dependent plasticity in the visual cortex. Genes Brain Behav 7:915-23. -<A href="http://www.genenetwork.org/images/upload/Heimel_2008_BXDVisualCortex.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Jan TA, Lu L, Li CX, Williams RW, Waters RS (<a href="http://www.biomedcentral.com/1471-2202/9/3" target="_blank" class="fwn">2008</a>) Genetic analysis of posterior medial barrel subfield (PMBSF) size in somatosensory cortex (SI) in recombinant inbred strains of mice. BMC Neuroscience 9:3 -<A href="http://www.biomedcentral.com/content/pdf/1471-2202-9-3.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Johnson KR, Longo-Guessa C, Gagnona LH, Yub H, Zhengb QY (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18662770" target="_blank" class="fwn">2008</a>) A locus on distal chromosome 11 (<I>ahl8</I>) and its interaction with <I>Cdh23 ahl</I> underlie the early onset, age-related hearing loss of DBA/2J mice. Genomics 92:219-225 -<LI> -Jones LC, Beard JL, Jones BC (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18189309 -" target="_blank" class="fwn">2008</a>) Genetic analysis reveals polygenic influences on iron, copper, and zinc in mouse hippocampus with neurobiological implications. Hippocampus 18:398-410 -<A href="images/upload/Jones_2008_Hippocampus.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Jones LC, Earley CJ, Allen RP, Jones BC (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18189309 -" target="_blank" class="fwn">2008</a>) Of mice and men, periodic limb movements and iron: how the human genome informs the mouse genome. Genes, Brain and Behavior 7:513-514. -<A href="/images/upload/Jones_OfMiceandMen.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Kang HM, Ye C, Eskin E (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18791227 -" target="_blank" class="fwn">2008</a>) Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots. Genetics doi:10.1534/genetics.108.094201 -<A href="http://www.genetics.org/cgi/content/abstract/genetics.108.094201v1" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>. [An important method that can greatly improve the ability to resolve true genetic interactions in expression genetic studies.] -<LI> -Kadarmideen HN (<a href="http://www.ncbi.nlm.nih.gov/pubmed/19045837 -" target="_blank" class="fwn">2008</a>) Genetical systems biology in livestock: Application to gonadotrophin releasing hormone and reproduction. IET Systems Biology 2:423-441 -<A href="/images/upload/Kadarmideen_2008.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Kerns RT, Miles MF (2008) Microarray analysis of ethanol-induced changes in gene expression. Alcohol: Methods and Protocols. In: Methods in Molecular Biology 447:395-410 -<A href="http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-242-7_26" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Kotb M, Fathey N, Aziz R, Rowe S, Williams RW, Lu L (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18972751" target="_blank" class="fwn">2008</a>) Unbiased forward genetics and systems biology approaches to understanding how gene-environment interactions work to predict susceptibility and outcomes of infections. Novartis Found Symp 293:156-165; discussion pp 165-167, 181-183 -<LI> -Loos M (2008) The PhenoTyper automated home cage environment as a high throughput tool to detect behavioral abnormalities in mutant mice. Proceeding of Measuring Behavior (Maastricht, The Netherlands, Aug 26-29, 2008). -<A href="http://www.neurobsik.nl/Loos_2008.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Loudet O, Michael TP, Burger BT, Le Metté C, Mockler TC, Weigel D, Chory J (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18971337 -" target="_blank" class="fwn">2008</a>) A zinc knuckle protein that negatively controls morning-specific growth in Arabidopsis thaliana. Proc Natl Acad Sci USA 105:17193-8 -<A href="http://www.pnas.org/content/105/44/17193.long" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>, and <A href="http://www.pnas.org/content/suppl/2008/10/29/0807264105.DCSupplemental/0807264105SI.pdf" target="_blank" class="fwn"><I>Full Text Supplement</I></A> -<LI> -Lu L, Wei L, Peirce JL, Wang X, Zhou J, Homayouni R, Williams RW, Airey DC (2008) Using gene expression databases for classical trait QTL candidate gene discovery in the BXD recombinant inbred genetic reference population: mouse forebrain weight. BMC Genomics 9:444 -<A href="http://www.biomedcentral.com/1471-2164/9/444" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>, and <A href="http://www.biomedcentral.com/content/pdf/1471-2164-9-444.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Macedo C, Magalhaes DA, Tonani M, Marques MC, Junta CM, Passos GA (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18597059" target="_blank" class="fwn">2008</a>) Genes that code for T cell signaling proteins establish transcriptional regulatory networks during thymus ontogeny. -Mol Cell Biochem 318:63-71 -<LI> -Morahan G, Peeva V, Munish M, Williams R (2008) Systems genetics can provide new insights in to immune regulation and autoimmunity. 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PLoS Genet 4(2): e1000007. doi:10.1371/journal.pgen.1000007 -<A href="http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1000007" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> - -</OL> -</Blockquote> - - - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2007" class="subtitle"">GeneNetwork (2007) </A> -<BLOCKQUOTE> - -</Blockquote> - -<OL> -<LI> -Aziz RK, Kansal R, Abdeltawab NF, Rowe SL, Su Y, Carrigan D, Nooh MM, Attia RR, Brannen C, Gardner LA, Lu L, Williams RW, Kotb M (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17525705" target="_blank" class="fwn">2007</a>) Susceptibility to severe Streptococcal sepsis: use of a large set of isogenic mouse lines to study genetic and environmental factors. Genes and Immunity 8:404-415 -<LI> -Bao L, Peirce JL, Zhou M, Li H, Goldowitz D, Williams RW, Lu L, Cui Y (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17428815" target="_blank" class="fwn">2007</a>) An integrative genomics strategy for systematic characterization of genetic loci modulating phenotypes. Hum Mol Genet 16:1381-1390 -<LI> -Bao L, Zhou M, Wu L, Lu L, Goldowitz D, Williams RW, Cui Y (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17099235" target="_blank" class="fwn">2007</a>) PolymiRTS Database: linking polymorphisms in microRNA target sites with complex traits. 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Blackwell Publishing, p. <a href="http://books.google.com/books?id=taE276KCyecC&pg=PA379&lpg=PA379&dq=genenetwork+webqtl&source=web&ots=2CjGbbDh3B&sig=tXdbQ7KAGOyxOee9TECF40GXyywl" target="_blank" class="fwn">379</a>), ISBN 1405127414 -<LI> -Bennett B, Downing C, Carosone-Link P, Ponicsan H, Ruf C, Johnson TE (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17250610" target="_blank" class="fwn">2007</a>) Quantitative trait locus mapping for acute functional tolerance to ethanol in the L x S recombinant inbred panel. Alcohol Clin Exp Res. 31:200-208. [Phenotype data described in this paper are accessible in GeneNetwork in the LXS Phenotype database; ID numbers 10126, 10127, 10132, 10134, 10138, and 10139 (select Species=MOUSE, Group=LXS, Type=PHENOTYPES and search the ALL field with the term "functional" or just enter the ID numbers above.] -<LI> -Cervino ACL, Darvasi A, Fallah Mi, Mader CC, Tsinoremas NF (<a href="http://www.genetics.org/cgi/content/full/175/1/321" target="_blank" class="fwn">2007</a>) An integrated in silico gene mapping strategy in inbred mice. Genetics 175:321-333 -<A href="http://www.genetics.org/cgi/reprint/175/1/321" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Chesler EJ (<a href="http://www3.interscience.wiley.com/cgi-bin/summary/114171173/SUMMARY" target="_blank" class="fwn">2007</a>) Bioinformatics of behavior. In Neurobehavioral Genetics, ed Jones BC, Mormede P -CRC Press ISBN 084931903X InterScience -<a href="http://books.google.com/books?id=ZNYE-FcvYloC&pg=PA102&lpg=PA102&dq=genenetwork+webqtl&source=web&ots=q3RfjmnLjt&sig=sDjpfmvzdx2lKigtJKqbb-H8Di8&hl=en&sa=X&oi=book_result&resnum=3&ct=result#PPA95,M1" target="_blank" class="fwn">95-114</a>), ISBN 1405127414 -<LI> -Chesler EJ (<a href="http://www3.interscience.wiley.com/cgi-bin/summary/114171173/SUMMARY" target="_blank" class="fwn">2007</a>) Combining quantitative trait and gene-expression data. 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Genome Biology 8:R221 -<A href="http://www.plosgenetics.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pgen.0030214&representation=PDF" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://genomebiology.com/2007/8/10/R221" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Crawford NP, Qian X, Ziogas A, Papageorge AG, Boersma BJ, Walker RC, Lukes L, Rowe WL, Zhang J, Ambs S, Lowy DR, Anton-Culver H, Hunter KW (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18081427" target="_blank" class="fwn">2007</a>) Rrp1b, a new candidate susceptibility gene for breast cancer progression and metastasis. PLoS Genetics 3: e214 -<A href="http://www.plosgenetics.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pgen.0030214&representation=PDF" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0030214" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Dong H, Martin MV, Colvin J, Ali Z, Wang L, Lu L, Williams RW, Rosen GD, Csernansky JG, Cheverud JM (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17406662" target="_blank" class="fwn">2007</a>) Quantitative trait loci linked to thalamus and cortex gray matter volumes in BXD recombinant inbred mice. Heredity 99:62-69 -<LI> -Fox JG, Barthold SW, Davisson MT, Newcomer CE (<a href="http://books.google.com/books?id=vnRpW-gI9JMC" target="_blank" class="fwn">2007</a>) The mouse in biomedical research. (2nd ed). 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Biological Aging: Methods and Protocols, ed Tollefsbol TO, Humana Press, Inc., Netlibrary, Springer -<A href="http://books.google.com/books?id=fbTsCdQv7cEC&pg=RA4-PA332&lpg=RA4-PA332&dq=genenetwork+webqtl&source=web&ots=PawLDYAUam&sig=hOHsKDfumr3U-ZEUtT7Ag6gJAYg&hl=en&sa=X&oi=book_result&resnum=9&ct=result#PRA4-PA321,M1" target="_blank" class="fwn"><I>Google Book Search</I></A> -<LI> -Jawad M, Giotopoulos G, Fitch S, Cole C, Plumb M, Talbot CJ (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17185011" target="_blank" class="fwn">2007</a>) Mouse bone marrow and peripheral blood erythroid cell counts are regulated by different autosomal genetic loci. Blood Cells Mol Disease 38:69-77 -<LI> -Jessberger S, Gage FH (<a href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1800354" target="_blank" class="fwn">2007</a>) ZOOMING IN: a new high-resolution gene expression atlas of the brain. 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Bioinformatics 23:1545-1549 -<A href="http://bioinformatics.oxfordjournals.org/cgi/reprint/23/12/1545" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://bioinformatics.oxfordjournals.org/cgi/content/full/23/12/1545" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Vazquez-Chona F, Lu L, Williams RW, Geisert EE (2007) Genetic influences on retinal gene expression and wound healing. Gene Regulation and Systems Biology 1:327-348 -<A href="/images/upload/Vazquez2007.pdf" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -von Rohr P, Friberg M, Kadarmideen HN (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17688316" target="_blank" class="fwn">2007</a>) Prediction of transcription factor binding sites using results from genetical genomics investigations. Journal of Bioinformatics and Computational Biology 5:773-793 -<A href="/images/upload/vonRohr_etal_2007.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Wan X, Pavlidis P (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17917127" target="_blank" class="fwn">2007</a>) Sharing and reusing gene expression profiling data in neuroscience. Neuroinformatics 5:161-75. -<A href="http://www.bioinformatics.ubc.ca/pavlidis/lab/reuse/walkthrough.pdf" target="_blank" class="fwn"><I>HTML example of using GEMMA and GeneNetwork</I></A>. -<LI> -Zou W, Aylor DL, Zeng ZB (<a href="http://www.biomedcentral.com/1471-2105/8/7" target="_blank" class="fwn">2007</a>) eQTL Viewer: visualizing how sequence variation affects genome-wide transcription. BMC Bioinformatics 8:7. -<A href="http://www.biomedcentral.com/content/pdf/1471-2105-8-7.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://www.biomedcentral.com/1471-2105/8/7" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. -</OL> - -</Blockquote> - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2006" class="subtitle"">GeneNetwork (2006) </A> -<BLOCKQUOTE> - -</Blockquote> - -<OL> -<LI> -Aliesky HA, Pichurin PN, Chen CR, Williams RW, Rapoport B, McLachlan SM (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16543368" class="fwn">2006</a>) Probing the genetic basis for thyrotropin receptor antibodies and hyperthyroidism in immunized CXB recombinant inbred mice. Endocrinology 147:2789-800. -<A href="http://endo.endojournals.org/cgi/reprint/147/6/2789.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://endo.endojournals.org/cgi/content/full/147/6/2789" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. -<LI> -Bao L, Wei L, Peirce JL, Homayouni R, Li H, Zhou M, Chen H, Lu L, Williams RW, Pfeffer LM, Goldowitz D, Cui Y (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16783639" class="fwn">2006</a>) Combining gene expression QTL mapping and phenotypic spectrum analysis to uncover gene regulatory relationships. Mammalian Genome 17:575-583 -<A href="http://www.springerlink.com/content/v32720xj70343812/fulltext.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://www.springerlink.com/content/v32720xj70343812/fulltext.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. -<LI> -Beatty J, Laughlin RE (<a href="http://www.biomedcentral.com/1471-2202/7/16" class="fwn">2006</a>) Genomic regulation of natural variation in cortical and noncortical brain volume. BMC Neuroscience 7:16 [This mapping study made use of both the <A HREF="www.mbl.org" target="_blank" class="fwn">Mouse Brain Libray</A> online collection of sections of BXD brains and GeneNetwork/WebQTL.] -<LI> -Bennett B, Carosone-Link P, Zahniser NR, Johnson TE (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16803863&query_hl=2&itool=pubmed_docsum" target="_blank" class="fwn">2006</a>) Confirmation and fine mapping of ethanol sensitivity quantitative trait loci, and candidate gene testing in the LXS recombinant inbred mice. J Pharmacol Exp Ther 319:299-307 (doi: 10.1038/ng1938) -<A href="http://jpet.aspetjournals.org/cgi/reprint/319/1/299.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Bennett B, Downing C, Parker C, Johnson TE (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16730093" target="_blank" class="fwn">2006</a>) Mouse genetic models in alcohol research. Trends Genet 22:367-74 -<LI> -Cervino ACL, Darvasi A, Fallahi M, Mader CC, Tsinoremas NF (2006) An integrated in silico gene mapping strategy in inbred mice (<a href="http://www.genetics.org/cgi/content/full/175/1/321" target="_blank" class="fwn">2006</a>) Genetics 175:321-333 -<LI> -Chesler EJ, Langston MA (<a href="http://www.springerlink.com/content/ut638ph1845x1768/" target="_blank" class="fwn">2006</a>) Combinatorial genetic regulatory network analysis tools for high throughput transcriptomic data. In: Lecture Notes in Computer Science. Springer, Heidelberg, Vol. 4023: 150-165. -<LI> -De Haro L, Panda S(<a href="http://www.ncbi.nlm.nih.gov/pubmed/17107940" target="_blank" class="fwn">2006</a>) Systems biology of circadian rhythms: an outlook. Journal of Biological Rhythms 21:507 -<A href="http://jbr.sagepub.com/cgi/reprint/21/6/507.pdf " target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Jones LC, McCarthy KA, Beard JL, Keen CL, Jones BC (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16910173" target="_blank" class="fwn">2006</a>) Quantitative genetic analysis of brain copper and zinc in BXD recombinant inbred mice. Nutritional Neuroscience 9:81-92 [This paper includes a large data set consisting of 16 traits related to copper and zinc metabolism in the CNS that is part of the Mouse BXD Phenotype database in GeneNetwork. The entire data set can be found by entering the search term "Jones LC" in the ALL search field.] -<LI> -Kadarmideen HN, Janss LLG (<a href="http://www.ncbi.nlm.nih.gov//pubmed/17132818" class="fwn" target="_blank" >2006</a>) Population and systems genetics analyses of cortisol in pigs divergently selected for stress. Physiological Genomics 29:57-65 <A href="http://physiolgenomics.physiology.org/cgi/reprint/29/1/57?ck=nck" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, <A href="http://physiolgenomics.physiology.org/cgi/content/full/29/1/57?ck=nck" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. [One of several great papers in a freely available (open) Special Issue of Mammalian Genome devoted to QTLs, Expression and Complex Trait Analysis. This study makes great use of the BXD INIA Brain mRNA M430 PDNN data set and GeneNetwork/WebQTL.] -<LI> -Kadarmideen HN, von Rohr, P, Janss LLG (<a href="http://www.ncbi.nlm.nih.gov//pubmed/16783637" class="fwn" target="_blank" >2006</a>) From genetical genomics to systems genetics: potential applications in quantitative genomics and animal breeding. Mammalian Genome 17:548-564 <A href="http://www.springerlink.com/media/788y661n1l5tvhac6eet/contributions/4/4/2/5/4425640024004428.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, <A href="http://www.springerlink.com/media/12d237nvvh7krwan8q9x/contributions/4/4/2/5/4425640024004428_html/fulltext.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. [One of several great papers in a freely available (open) Special Issue of Mammalian Genome devoted to QTLs, Expression and Complex Trait Analysis. This study makes great use of the BXD INIA Brain mRNA M430 PDNN data set and GeneNetwork/WebQTL.] -<LI> -Kamminga LM, Bystrykh LV, de Boer A, Houwer S, Douma J, Weersing E, Dontje B, de Haan G (<A HREF="http://www.ncbi.nlm.nih.gov//pubmed/16293602" target="_blank" class="fwn">2006</A>) The Polycomb group gene Ezh2 prevents hematopoietic stem cell exhaustion. Blood 107:2170-2179 -<A href="http://bloodjournal.hematologylibrary.org/cgi/reprint/2005-09-3585v1.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Keeley MB, Wood MA, Isiegas C, Stein J, Hellman K, Hannenhalli S, Abel T (<a href="http://www.learnmem.org/cgi/reprint/13/2/135.pdf?ck=nck" class="fwn" target="_blank>2006</A>) Differential transcriptional response to nonassociative and associative components of classical fear conditioning in the amygdala and hippocampus. Learning and Memory 13:135-142103:780-785. -<LI> -Kempermann G, Chesler EJ, Lu L, Williams RW, Gage FH (<a href="http://www.pnas.org/cgi/content/full/103/3/780" class="fwn" target="_blank>2006</A>) Natural variation and genetic covariance in adult hippocampal neurogenesis. Proceedings of the National Academy of Science 103:780-785. -<LI> -Korostynski M, Kaminska-Chowaniec D, Piechota M, Przewlocki R (<a href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1553451" target="_blank" class="fwn">2006</a>) Gene expression profiling in the striatum of inbred mouse strains with distinct opioid-related phenotypes. BMC Genomics 7: 146 (doi: 10.1186/1471-2164-7-146). <A href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1553451" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. [A combination of data sources including the Rosen HBP Striatum data set used to study opioid-related traits. Their <a href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1553451&rendertype=figure&id=F3" target="_blank" class="fwn">Fig 3C</a> and <a href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1553451&rendertype=figure&id=F5" target="_blank" class="fwn">Fig 5</a> take good advantage of GeneNetwork and WebQTL output graphs.] -<LI> -Lan H, Chen M, Flowers JB, Yandell BS, Stapleton DS, Mata CM, Mui ET, Flowers MT, Schueler KL, Manly KF, Williams RW, Kendziorski C, Attie A (<a href="http://genetics.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pgen.0020006" target="_blank" class="fwn">2006</a>) Combined expression trait correlations and expression quantitative trait locus mapping. PLoS Genetics 2:e6 [Please cite this work if you make use of the B6BTBRF2 liver transcriptome data.] -<LI> -Liu Y, Li J, Sam L, Goh CS, Gerstein M, Lussier YA (<a href="http://compbiol.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pcbi.0020159" target="_blank" class="fwn">2006</a>) An integrative genomic approach to uncover molecular mechanisms of prokaryotic traits. PLoS Computional Biology 2:e159 -<LI> -Loney KD, Uddin RK, Singh SM (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16433728" target="_blank" class="fwn">2006</a>) Analysis of metallothionein brain gene expression in relation to ethanol preference in mice using cosegregation and gene knockouts. Alcohol Clin Exp Res 30:15-25 -<LI> -Martin MV, Dong H, Vallera D, Lee D, Lu L, Williams RW, Rosen GD, Cheverud JM, Csernansky JG (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=17081266&query_hl=1&itool=pubmed_docsum" target="_blank" class="fwn">2006</a>) Independent quantitative trait loci influence ventral and dorsal hippocampal volume in recombinant inbred strains of mice. Gene, Brain and Behavior 5:614-623. -<LI> -van Os R, Ausema A, Noach EJ, van Pelt K, Dontje BJ, Vellenga E, de Haan G (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16371023" target="_blank" class="fwn">2006</a>) Identification of quantitative trait loci regulating haematopoietic parameters in B6AKRF2 mice. British Journal of Haematolology 132:80-90. -<LI> -Peirce JL, Li H, Wang J, Manly KF, Hitzemann RJ, Belknap JK, Rosen GD, Goodwin S, Sutter TR, Williams RW, Lu L (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=Abstract&list_uids=16783644&query_hl=1&itool=pubmed_docsum" class="fwn">2006</a>) How replicable are mRNA expression QTL? Mammalian Genome 17:643-656. <A href="http://www.springerlink.com/content/a23g75163p624324/fulltext.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, <A href="http://www.springerlink.com/content/a23g75163p624324/fulltext.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. [An important paper in which four matched expression data sets (whole brain and striatum) generated using both recombinant inbred and F2 intercrosses were directly compared.] -<LI> -Ponomarev I, Maiya R, Harnett MT, Schafer GL, Ryabinin AE, Blednov YA, Morikawa H, Boehm SL 2nd, Homanics GE, Berman AE, Lodowski KH, Bergeson SE, Harris RA (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16783644" class="fwn">2006</a>) Transcriptional signatures of cellular plasticity in mice lacking the alpha1 subunit of GABAA receptors. J Neurosci 26:5673-83 -<A href="http://www.jneurosci.org/cgi/reprint/26/21/5673.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://www.jneurosci.org/cgi/content/full/26/21/5673" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Radcliffe RA, Lee MJ, Williams RW (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=Abstract&list_uids=16783639&query_hl=1&itool=pubmed_docsum" class="fwn">2006</a>) Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Mammalian Genome 17:629-642 <A href="http://www.springerlink.com/content/3u641hgk642221r6/fulltext.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, <A href="http://www.springerlink.com/content/3u641hgk642221r6/fulltext.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Rulten SL, Ripley TL, Hunt CL, Stephens DN, Mayne LV (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16594979&query_hl=2&itool=pubmed_docsum" target="_blank" class="fwn">2006</a>) Sp1 and NFkappaB pathways are regulated in brain in response to acute and chronic ethanol. Genes Brain Behav 5:257-273 [This study exploited the original GeneNetwork Affymetrix U74Av2 brain data set to validate a set of transcripts modulated by ethanol treatment.] -<LI> -Saba L, Bhave SV, Grahame N, Bice P, Lapadat R, Belknap J, Hoffman PL, Tabakoff B (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16783646&query_hl=8&itool=pubmed_docsum" class="fwn">2006</a>) Candidate genes and their regulatory elements: alcohol preference and tolerance. Mammalian Genome 17:669-688 <A href="http://www.springerlink.com/content/224237686jx80v61/fulltext.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, <A href="http://www.springerlink.com/content/224237686jx80v61/fulltext.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> [A lovely paper describing results of a whole brain BXD study involving males from 30 strains (four individual arrays (not pooled) per strain). The data described in this study have been made accessible from GeneNetwork.] -<LI> -Shifman S, Bell JT, Copley BR, Taylor M, Williams RW, Mott R, Flint J (<A HREF="http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.0040395" target="_blank" class="fwn">2006</A>) A high resolution single nucleotide polymorphism genetic map of the mouse genome. PLoS Biology 4:2227-2237 <A HREF="http://biology.plosjournals.org/archive/1545-7885/4/12/pdf/10.1371_journal.pbio.0040395-L.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> [A comprehensive analysis of recombination rates using several populations of mice, including most major genetic reference populations.] -<LI> -van Os R, Ausema A, Noach EJ, van Pelt K, Dontje BJ, Vellenga E, de Haan G (<a href="http://www.blackwell-synergy.com/doi/abs/10.1111/j.1365-2141.2005.05835.x" class="fwn">2006</a>) Identification of quantitative trait loci regulating haematopoietic parameters in B6AKRF2 mice. British Journal of Haematology 132:80-90 -<LI> -Veenstra-VanderWeele J, Qaadir A, Palmer AA, Cook EH Jr, de Wit H. (<a href="http://www.ncbi.nlm.nih.gov/pubmed/16237383" class="fwn">2006</a>) Association between the casein kinase 1 epsilon gene region and subjective response to D-amphetamine. Neuropsychopharmacology 31:1056-1063 <A href="http://www.nature.com/npp/journal/v31/n5/full/1300936a.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> [This mapping study made use of GeneNetwork/WebQTL to show that "the region that contains Csnk1e was also found to contain a QTL for MA sensitivity, and complementary data from WebQTL (Chesler et al, 2005) showed that this same region of mouse chromosome 15 influenced Csnk1e transcript abundance, indicating the presence of a cis-acting eQTL."] -<LI> -Voy BH, Scharff JA, Perkins AD, Saxton AM, Borate B, Chesler EJ, Branstetter LK, Langston MA (<a href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=16854212" target="_blank" class="fwn">2006</a>) Extracting gene networks for low-dose radiation using graph theoretical algorithms. PLoS Computational Biology 2:e89. [A paper that introduces the use of cliques in analyzing microarray data sets. One of the GeneNetwork databases (BXD Hematopoietic Stem Cells) was used to follow up on a strong candidate gene, Tubby-like protein 4 <I>Tulp4</I>) that may have a role in immune function. -<LI> -Williams RH, Cotsapas CJ, Cowley MJ, Chan E, Nott DJ, Little PF (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=Abstract&list_uids=16874319&query_hl=3&itool=pubmed_docsum" target="_blank" class="fwn">2006</a>) Normalization procedures and detection of linkage signal in genetical-genomics experiments. Nature Genetics 38:855-856. [A set of letters to the editor by Rohan Williams and colleagues, Chesler and colleagues, and Petretto and colleagues. All three letters highlight some of the technical challenges of analyzing expression data in a genetic context and point to the need for great care and attention to normalization methods. Well worth reviewing. Normalization is still very much an art, and it is quite likely that no one normalization procedure will be optimal for all different research questions. The old adage: "different horses for different courses" is likley to apply.] -<LI> -Williams RW (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=Abstract&list_uids=16783631&query_hl=1&itool=pubmed_docsum" class="fwn">2006</a>) Expression genetics and the phenotype revolution. Mammalian Genome 17:496-502 <A href="http://www.springerlink.com/content/921734n56j08400n/fulltext.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, <A href="http://www.springerlink.com/content/921734n56j08400n/fulltext.html" target="_blank" class="fwn"><I>Full Text HTML Version</I></A>. [My take on where systems genetics may take us in the next few years.] - -</OL> - - - - - - - - - - -</Blockquote> - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2005" class="subtitle"">GeneNetwork (2005) </A> -<BLOCKQUOTE> - -</Blockquote> -<OL> -<LI>Alberts R, Terpstra P, Bystrykh LV, de Haan G, Jansen RC (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed&dopt=Abstract&list_uids=15711547&query_hl=10" target="_blank" class="fwn">2005</A>) A statistical multiprobe model for analyzing cis and trans genes in genetical genomics experiments with short-oligonucleotide arrays Genetics 171:1437-1439 -<LI>Alberts R, Fu J, Swertz MA, Lubbers LA, Albers CJ, Jansen RC (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed/15975223" target="_blank" class="fwn">2005</A>) Combining microarrays and genetic analysis. Brief Bioinform. 6:135-145 -<A href="http://bib.oxfordjournals.org/cgi/reprint/6/2/135.pdf" target="_blank" class="fwn"><I> Full text PDF version</I></A> -<LI> -Bystrykh L, Weersing E, Dontje B, Sutton S, Pletcher MT, Wiltshire T, Su AI, Vellenga E, Wang J, Manly KF, Lu L, Chesler EJ, Alberts R, Jansen RC, Williams RW, Cooke M, de Haan G (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed/15711547" target="_blank" class="fwn">2005</A>) Uncovering regulatory pathways affecting hematopoietic stem cell function using “genetical genomics." Nature Genetics, 37:225-232 -<LI> -Chesler EJ, Lu L, Shou S, Qu Y, Gu J, Wang J, Hsu HC, Mountz JD, Baldwin N, Langston MA, Threadgill DW, Manly KF, Williams RW (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15711545&query_hl=10" target="_blank" class="fwn">2005</A>) Genetic dissection of gene expression reveals polygenic and pleiotropic networks modulating brain structure and function. Nature Genetics 37: 233-242 -<LI> -Flaherty L, Herron B, Symula D (<A HREF="http://www.genome.org/cgi/content/abstract/15/12/1741" target="_blank" class="fwn">2005</A>) Genome Research 15:1741-1745 <A href="http://www.genome.org/cgi/reprint/15/12/1741.pdf" target="_blank" class="fwn"><I> Full text PDF version</I></A> -<LI> -Garlow SJ, Boone E, Li W, Owens MJ, Nemeroff CB (<A HREF="http://endo.endojournals.org/cgi/content/abstract/146/5/2362" target="_blank" class="fwn">2005</A>) Genetic analysis of hypothalamic corticotropin-releasing factor system. Endocrinology 146: 2362-2368 -<LI> -Gammie SC, Hasen NS, Awad TA, Auger AP, Jessen HM, Panksepp JB, Bronikowski AM (<A HREF="http://www.eeob.iastate.edu/faculty/BronikoA/annespdfs/MBres.pdf" target="_blank" class="fwn">2005</A>) Gene array profiling of large hypothalamic CNS regions in lactating and randomly cycling virgin mice. Molecular Brain Research 139: 201-211 -<LI> -Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (<A HREF="http://www.jneurosci.org/cgi/content/full/25/9/2255" target="_blank" class="fwn">2005</A>) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266 [<A HREF="http://www.brainchip.vcu.edu/kerns_apptable1.pdf" target="_blank" class="fwn">www.brainchip.vcu.edu/kerns_apptable1.pdf</A> for a complete table of modulated transcripts.] -<LI> -Li HQ, Lu L, Manly KF, Wang J, Zhou M, Williams RW, Cui Y (<A HREF="http://hmg.oupjournals.org/cgi/content/abstract/ddi124v1" target="_blank" class="fwn">2005</A>) Inferring gene transcriptional modulatory relations: a genetical genomics approach. Human Molecular Genetics 14: 1119-1125 -<LI> -Li J, Burmeister M (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16244315&query_hl=5&itool=pubmed_docsum" target="_blank" class="fwn">2005</A>) Genetical genomics: combining genetics with gene expression analysis. Human Molecular Genetics 14:163-169. - [<A href="/images/upload/Li_Burmeister_2005.pdf" target="_blank" class="fwn"><I> Full text PDF version</I></A>] - -<LI> -Lozier JN, Tayebi N, Zhang P (<A HREF="http://www.bloodjournal.org/cgi/content/abstract/" target="_blank" class="fwn">2005</A>) Mapping of genes that control the antibody response to human factor IX in mice. Blood 105: 1029-1035 -<LI> -MacLaren EJ, Sikela JM (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16205357&query_hl=3&itool=pubmed_docsum" target="_blank" class="fwn">2005</A>) Cerebellar gene expression profiling and eQTL analysis in inbred mouse strains selected for ethanol sensitivity. Alcoholism: Clinical and Experimental Research 29: 1568-1579. -<A HREF="http://www.alcoholism-cer.com/pt/re/alcoholism/abstract.00000374-200509000-00002.htm;jsessionid=HBGNJpQldfCKvpYr6XLCzW3fF4YT1mzCVTXGcCMNYCL6N4WlDLlK!901085598!181195628!8091!-1" target="_blank" class="fwn"><I>HTML</I></A> and -<A HREF="http://www.alcoholism-cer.com/pt/re/alcoholism/pdfhandler.00000374-200509000-00002.pdf;jsessionid=HBGNJpQldfCKvpYr6XLCzW3fF4YT1mzCVTXGcCMNYCL6N4WlDLlK!901085598!181195628!8091!-1" target="_blank" class="fwn"><I>PDF</I> reprints.</A> -<LI> -Matthews B, Bhave SV, Belknap JK, Brittingham C, Chesler EJ, Hitzemann RJ, Hoffman PL, Lu L, McWeeney S, Miles MR, Tabakoff B, Williams RW (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16205371&query_hl=1&itool=pubmed_docsum" target="_blank" class="fwn">2005</A>) Complex genetics of interactions of alcohol and CNS function and behavior. Alcoholism: Clinical and Experimental Research 29:1706-1719 -<LI> -Mountz JD, Yang P, Wu Q, Zhou J, Tousson A, Fitzgerald A, Allen J, Wang X, Cartner S, Grizzle WE, Yi N, Lu L, Williams RW, Hsu HC (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15683449&query_hl=4" target="_blank" class="fwn">2005</A>) Genetic segregation of spontaneous erosive arthritis and generalized autoimmune disease in BXD2 recombinant inbred strain of mice. Scadinavian Journal of Immunology 61:1-11 -<A href="/images/upload/Mountz2005.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> -<LI> -Li CX, Wei X, Lu L, Peirce JL, Wiliams RW, Waters RS (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=16338823&query_hl=12&itool=pubmed_docsum" target="_blank" class="fwn">2005</A>) Genetic analysis of barrel field size in the first somatosensory area (S1) in inbred and recombinant inbred strains of mice. Somatosensory and Motor Research 22:141-150 -<LI> -Palmer AA, Verbitsky M, Suresh R, Kamen HM, Reed CI, Li N, Burkhart-Kasch S, McKinnon CS, Belknap JK, Gilliam TC, Phillips TJ (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed/16104378" target="_blank" class="fwn">2005</A>) Gene expression differences in mice divergently selected for methamphetamine sensitivity. Mammalian Genome 16:291-305 -<LI> -Pravenec M, Kren V (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed/15728137" target="_blank" class="fwn">2005</A>) Genetic analysis of complex cardiovascular traits in the spontaneously hypertensive rat. Exp Physiol 90:273-276 -<A href="http://ep.physoc.org/cgi/reprint/90/3/273.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>, -<A href="http://ep.physoc.org/cgi/content/full/90/3/273" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Scott RE, White-Grindley E, Ruley HE, Chesler EJ, Williams RW (<A HREF="http://www3.interscience.wiley.com/cgi-bin/fulltext/109860478/HTMLSTART" target="_blank" class="fwn">2005</A>) P2P-R expression is genetically coregulated with components of the translation machinery and with PUM2, a translational repressor that associates with the P2P-R mRNA. Journal of Cellular Physiology 204:99-105 <A href="http://www3.interscience.wiley.com/cgi-bin/fulltext/109860478/HTMLSTART" target="_blank" class="fwn"><I> Full text HTML version</I></A> -<LI> -Vazquez-Chona FR, Khan AN, Chan CK, Moore AN, Dash PK, Rosario Hernandez R, Lu L, Chesler EJ, Manly KF, Williams RW, Geisert Jr EE (<A HREF="http://www.molvis.org/molvis/v11/a115/" target="_blank" class="fwn">2005</A>) Genetic networks controlling retinal injury. Molecular Vision 11:958-970 -<LI> -Yang H, Crawford N, Lukes L, Finney R, Lancaster M, Hunter KW (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed/15728137" target="_blank" class="fwn">2005</A>) Metastasis predictive signature profiles pre-exist in normal tissues. Clin Exp Metastasis 22:593-603 -<A href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=16475030" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> - - - -</OL> -</Blockquote> - - - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2004" class="subtitle"">GeneNetwork (2004) </A> -<BLOCKQUOTE> - -</Blockquote> -<OL> -<LI>Baldwin NE, Chesler EJ, Kirov S, Langston MA, Snoddy JR, Williams RW, Zhang B (2004) Computational, integrative and comparative methods for the elucidation of genetic co-expression networks. Journal of Biomedicine and Biotechnology 2:172-180 -<A HREF="http://www.pubmedcentral.gov/articlerender.fcgi?tool=pubmed&pubmedid=16046823" target="_blank" class="fwn"><I>HTML</I></A> and -<A HREF="http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=1184052&blobtype=pdf" target="_blank" class="fwn"><I>PDF</I> reprints.</A> -<LI> -Carlborg O, De Koning DJ, Chesler EJ, Manly KM, Williams RW, Haley CS (<A HREF="http://bioinformatics.oupjournals.org/cgi/content/abstract/bti241v1" target="_blank" class="fwn">2004</A>) Methological aspects of the genetic dissection of gene expression. Bioinformatics 10:1093 -<LI> -Chesler EJ, Williams RW (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15474587&query_hl=10" target="_blank" class="fwn">2004</A>) Brain gene expression: genomics and genetics. International Review of Neurobiology 60:59-95 -<LI> -Fernandes K, Paya-Cano JL, Sluyter F, D'Souza U, Plomin R, Schalkwyk LC (<A HREF="http://www.blackwell-synergy.com/links/doi" target="_blank" class="fwn">2004</A>) Hippocampal gene expression profiling across eight mouse inbred strains: towards understanding the molecular basis for behaviour. European Journal of Neuroscience 19:2576-2582 -<A href="http://www.bloodjournal.org/cgi/content/full/104/2/374" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Henckaerts E, Langer JC, Hans-Willem Snoeck HW (2004) Quantitative genetic variation in the hematopoietic stem cell and progenitor cell compartment and in lifespan are closely linked at multiple loci in BXD recombinant inbred mice. Blood 104:374-379 <A href="http://www.bloodjournal.org/cgi/content/full/104/2/374" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15597075" target="_blank" class="fwn">2004</a>) On the integration of alcohol-related quantitative trait loci and gene expression analyses. Alcoholism: Clinical and Experimental Research 28:1437-1448 [Please cite this paper is you plan to use the B6D2F2 OHSU data set.] -<LI> -Maiya RP (<a href="http://64.233.179.104/search?q=cache:3ajOyi3RpywJ:www.lib.utexas.edu/etd/d/2004/maiyar34683/maiyar34683.pdf+webqtl&hl=en" target="_blank" class="fwn">2004</a>) Regulation of dopamine transporter: a role for ethanol and protein interactions. Dissertation, University of Texas, Austin -<LI> -Orth AP, Batalow S, Perrone M, Chanda SK (<a href="http://www.ashley-pub.com/doi/abs/10.1517/14728222.8.6.587" target="_blank" class="fwn">2004</a>) The promise of genomics to identify novel therapeutic targets. Expert Opion of Therapeutic Targets 8:587-596 -<LI> -Pomp D, Allan MF, Wesolowski SR (<a href="http://www.animal-science.org/cgi/content/full/82/13_suppl/E300" target="_blank" class="fwn">2004</a>) Quantitative genomics: Exploring the genetic architecture of complex trait predisposition. J Anim Sci 82:E300-E312 -<A href="http://jas.fass.org/cgi/reprint/82/13_suppl/E300.pdf" target="_blank" class="fwn"><I>Full Text HTML Version</I></A> -<LI> -Ponomarev I, Schafer GL, Blednov YA, Williams RW, Iver VR, Harris A (<A HREF="http://www.ncbi.nlm.nih.gov/pubmed/15544578" target="_blank" class="fwn">2004</A>) Convergent analysis of cDNA and short oligomer microarrays, mouse null mutant, and bioinformatics resources to study complex traits. Genes, Brain and Behavior 3:360-368 -<LI> -Simon P, Schott K, Williams RW, Schaeffel F (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15610169" target="_blank" class="fwn">2004</A>) Post-translational regulation of the immediate early gene EGR1 by light in the mouse retina. European Journal of Neuroscience 20:3371-3377 -<LI> -Zareparsi S, Hero A, Zack DJ, Williams RW, Swaroop A (<A HREF="http://www.iovs.org/cgi/content/full/45/8/2457" target="_blank" class="fwn">2004</A>) Seeing the unseen: microarray-based gene expression profiling in vision. Investigative Ophthalmology and Visual Science 45:2457-2462 <A href="http://www.iovs.org/cgi/content/full/45/8/2457" target="_blank" class="fwn"><I> Full text HTML version</I></A> -</OL - - - - - - - - - - - - - - -</Blockquote> - - - - - -<BLOCKQUOTE style="font-size: 14px;"> - <A NAME="2003" class="subtitle"">GeneNetwork (2003) </A> -<BLOCKQUOTE> - -</Blockquote> - -<OL> -<LI> -Bolivar V, Flaherty L (2003) A region on chromosome 15 controls intersession habituation in mice. Journal of Neuroscience 23: 9435-9438 <A href="http://www.jneurosci.org/cgi/content/full/23/28/9435" target="_blank" class="fwn"><I> Full Text HTML and PDF Versions</I></A> -<LI> -Jones BC, Reed CL, Hitzemann R, Wiesinger JA, McCarthy KA, Buwen JP, Beard JL <A HREF="http://www.ncbi.nlm.nih.gov/pubmed/14744041" target="_blank" class="fwn">2003</A>) Quantitative genetic analysis of ventral midbrain and liver iron in BXD recombinant inbred mice. Nutr Neuroscience 6:369-77 -<A href="images/upload/Jones_2003_NN1203.pdf" target="_blank" class="fwn"><I> Full Text PDF Version</I></A> - -<LI> -Hitzemann R, Hitzemann B, Rivera S, Gatley J, Thanos P, Shou S, Lu L, Williams RW (<a href="http://www.ncbi.nlm.nih.gov/pubmed/12543998" target="_blank" class="fwn">2003</a>) Dopamine D2 receptor binding, Drd2 expression and the number of dopamine neurons in the BXD recombinant inbred series: genetic relationships to alcohol and other drug associated phenotypes. Alcoholism: Clinical and Experimental Research 27:1-11 -<!-- <A href="http://www.alcoholism-cer.com/pt/re/alcoholism/abstract.00000374-200301000-00002.htm;jsessionid=Bd5vCAYkgweCpQQfVUDL32NyFP8vi8xbCG1JwnOLMdUZFaIgvgU5!1564676086!-949856032!9001!-1 -" target="_blank" class="fwn"><I> Full Text HTML and PDF Versions</I></A> ---> -<LI> -Hitzemann R, Malmanger B, Reed C, Lawler M, Hitzemann B, Coulombe S, Buck K, Rademacher B, Walter N, Polyakov Y, Sikela J, Williams RW, Flint J, Talbot C (<a href="http://www.ncbi.nlm.nih.gov/pubmed/14722723" target="_blank" class="fwn">2003</a>) A strategy for integration of QTL, gene expression, and sequence analyses. Mammalian Genome 14:733-747 -<LI> -Lionikas A, Blizard DA, Vandenbergh DJ, Glover MG, Stout JT, Vogler GP, McClearn GE, Larsson L (<a href="http://physiolgenomics.physiology.org/cgi/content/full/16/1/141" target="_blank" class="fwn">2003</a>) Genetic architecture of fast- and slow-twitch skeletal muscle weight in 200-day-old mice of the C57BL/6J and DBA/2J lineage. Physiological Genomics 16:141-152 -<LI> -Peirce J, Chesler EJ, Williams RW, Lu L (2003) Genetic architecture of the mouse hippocampus: identification of gene loci with regional effects. Genes, Brain and Behavior 2:238–252 -<A href="images/upload/Peirce_Lu_2003.pdf" target="_blank" class="fwn"><I> Full Text PDF Version</I></A> -<LI> -Rosen GD, La Porte NT, Diechtiareff B, Pung, CJ, Nissanov J, Gustafson C, Bertrand L, Gefen S, Fan Y, Tretiak OJ, Manly KF, Parks MR, Williams AG, Connolly MT, Capra JA, Williams RW (2003) Informatics center for mouse genomics: the dissection of complex traits of the nervous system. Neuroinformatics 1:327–342 -<A href="images/upload/Rosen_2003.pdf" target="_blank" class="fwn"><I> Full Text PDF Version</I></A> - -</OL> - -</Blockquote> - -<Blockquote class="fwn"><A NAME="Background" class="subtitle">Background references on inbred strains and other key resources</A> - -<Blockquote style="font-size: 14px;"> -Williams RW, Gu J, Qi S, Lu L (<a href="https://ncbi.nlm.nih.gov/pubmed/11737945" class="fwn" target="_blank">2001</a>) The genetic structure of recombinant inbred mice: high-resolution consensus maps for complex trait analysis. Genome Biology 2:46.1–46.18 <A href="http://genomebiology.com/content/2/11/RESEARCH0046" target="_blank" class="fwn"><I> Full Text HTML and PDF Version</I></A>. [General background on recombinant inbred strains.] -</Blockquote> - -<Blockquote style="font-size: 14px;"> -Peirce JL, Lu L, Gu J, Silver LM, Williams RW (<a href="http://www.biomedcentral.com/1471-2156/5/7" target="_blank" class="fwn">2004</a>) A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genetics 5:7 <A href="http://www.genenetwork.org/pdf/Peirce_and_Lu_2004.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>. [Background on the expanded set of BXD strains.] -</Blockquote> - -<Blockquote style="font-size: 14px;"> -Williams RW, Bennett B, Lu L, Gu J, DeFries JC, Carosone-Link PJ, Rikke BA, Belknap JK, Johnson TE (<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15457343" target="_blank" class="fwn">2004</a>) Genetic structure of the LXS panel of recombinant inbred mouse strains: a powerful resource for complex trait analysis. Mammalian Genome 15:637-647 [Background on origins and the genetic structure large panel of LXS strains. Please cite this paper is you have used LXS data sets.] -</Blockquote> - -<Blockquote style="font-size: 14px;"> -Grubb SC, Churchill GA, Bogue MA (<a href="http://www.ncbi.nlm.nih.gov/pubmed/15130929" target="_blank" class="fwn">2004</a>) A collaborative database of inbred mouse strain characteristics. Bioinformatics 20:2857-2859 [One of two key papers on the Mouse Phenome Project and database at The Jackson Laboratory. The mouse diversity panel (MDP) is a superset of strains that are part of the Phenome Project. <a href="http://bioinformatics.oxfordjournals.org/cgi/reprint/20/16/2857" target="_blank" class="fwn"><I>Full Text PDF Version</I></A>.] -</Blockquote> - -<Blockquote style="font-size: 14px;"> -Bogue MA, Grubb SC (<a href="http://www.ncbi.nlm.nih.gov/pubmed/15619963" target="_blank" class="fwn">2004</a>) The mouse phenome project. Genetica 122:71-74 [One of two key papers on the Mouse Phenome Project and database at The Jackson Laboratory. The mouse diversity panel (MDP) is a superset of strains that are part of the Phenome Project. Please contact Dr. Molly Bogue for information on the Phenome Project: mollyb@jax.org] -</Blockquote> - -<Blockquote style="font-size: 14px;"> -Frazer KA, Eskin E, Kang HM, Bogue MA, Hinds DA, Beilharz EJ, Gupta RV, Montgomery J, Morenzoni MM, Nilsen GB, Pethiyagoda CL, Stuve LL, Johnson FM, Daly MJ, Wade CM, Cox DR (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17660834" target="_blank" class="fwn">2007</a>) A sequence-based variation map of 8.27 million SNPs in inbred mouse strains. Nature 448, 1050-3 -</Blockquote> - - -<Blockquote style="font-size: 14px;"> -Loudet O, Chaillou S, Camilleri C, Bouchez D, Daniel-Vedele F (<A HREF="http://www.inra.fr/qtlat/BayxSha/Loudet2002.pdf" target="_blank" class="fwn">2002</A>) Bay-0 x Shahdara recombinant inbred line population: a powerful tool for the genetic dissection of complex traits in Arabidopsis. Theoretical and Applied Genetics 104:1173-1184 <A HREF="http://www.inra.fr/qtlat/BayxSha/Loudet2002.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> [Please cite this paper is you have used the BXS Arabidopsis data sets.] -</Blockquote> - -<Blockquote style="font-size: 14px;"> -Jirout M, Krenova D, Kren V, Breen L, Pravenec M, Schork NJ, Printz MP (<A HREF="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=12925886&query_hl=3" target="_blank" class="fwn">2003</A>) A new framework marker-based linkage map and SDPs for the rat HXB/BXH strain set. expression differences in mice diverently selected for methamphetamine sensitivity. Mammalian Genome 14: 537-546 -</Blockquote> - -<Blockquote style="font-size: 14px;"> -Shifman S, Bell JT, Copley BR, Taylor M, Williams RW, Mott R, Flint J (<A HREF="http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.0040395" target="_blank" class="fwn">2006</A>) A high resolution single nucleotide polymorphism genetic map of the mouse genome. PLoS Biology 4:2227-2237 <A HREF="http://biology.plosjournals.org/archive/1545-7885/4/12/pdf/10.1371_journal.pbio.0040395-L.pdf" target="_blank" class="fwn"><I>Full Text PDF Version</I></A> [A comprehensive analysis of recombination rates using several populations of mice, including most major GRPs.] -</Blockquote> - - -</Blockquote> -<Blockquote class="subtitle">Information about this HTML page:</P> </Blockquote> -<Blockquote style="font-size: 14px;"> -<Blockquote ><P><P>This text originally generated by RWW, April 2003. Updated by RWW, Oct 15, Dec 17, 2004; RWW Jan 19, 2005; EJC Mar 9; RWW Mar 29, Apr 15; RWW Jan 7, 2006, Jan 21, July 26, Aug 26, 2006s; May 2007; Feb 2008; March 19 2008 -</P></Blockquote> - - </Blockquote> - <P></P> - - - -{% endblock %} diff --git a/wqflask/wqflask/templates/references.html b/wqflask/wqflask/templates/references.html new file mode 100644 index 00000000..f723a1e8 --- /dev/null +++ b/wqflask/wqflask/templates/references.html @@ -0,0 +1,19 @@ +{% extends "base.html" %} +{% block title %}Reference{% endblock %} +{% block css %} +<link rel="stylesheet" type="text/css" href="/static/new/css/markdown.css" /> +{% endblock %} +{% block content %} +<div class="github-btn-container"> + <div class="github-btn"> + <a href="https://github.com/genenetwork/gn-docs"> + Edit Text + <img src="/static/images/edit.png"> + </a> + </div> +</div> +<div id="markdown" class="container"> + {{ rendered_markdown|safe }} +</div> + +{% endblock %}
\ No newline at end of file diff --git a/wqflask/wqflask/templates/search_result_page.html b/wqflask/wqflask/templates/search_result_page.html index 8e2b06a4..2a8d6931 100644 --- a/wqflask/wqflask/templates/search_result_page.html +++ b/wqflask/wqflask/templates/search_result_page.html @@ -2,6 +2,7 @@ {% block title %}Search Results{% endblock %} {% block css %} <link rel="stylesheet" type="text/css" href="{{ url_for('css', filename='DataTables/css/jquery.dataTables.css') }}" /> + <link rel="stylesheet" type="text/css" href="{{ url_for('css', filename='fontawesome/css/font-awesome.min.css') }}" /> <link rel="stylesheet" type="text/css" href="{{ url_for('js', filename='DataTablesExtensions/scroller/css/scroller.dataTables.min.css') }}"> <link rel="stylesheet" type="text/css" href="{{ url_for('js', filename='DataTablesExtensions/buttonStyles/css/buttons.dataTables.min.css') }}"> <link rel="stylesheet" type="text/css" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.1/css/all.min.css"> @@ -440,8 +441,6 @@ 'processing': 'Loading...' } } ); - - console.timeEnd("Creating table"); $('.toggle-vis').on( 'click', function (e) { e.preventDefault(); diff --git a/wqflask/wqflask/templates/show_trait_transform_and_filter.html b/wqflask/wqflask/templates/show_trait_transform_and_filter.html index 0418d972..d7eac378 100644 --- a/wqflask/wqflask/templates/show_trait_transform_and_filter.html +++ b/wqflask/wqflask/templates/show_trait_transform_and_filter.html @@ -4,7 +4,7 @@ <strong>Reset</strong> option as needed. </p> - <div id="blockMenuSpan" class="input-append block-by-index-div"> + <div id="blockMenuSpan" class="input-append block-div"> <label for="remove_samples_field">Block samples by index:</label> <input type="text" id="remove_samples_field" placeholder="Example: 3, 5-10, 12"> <select id="block_group" size="1"> @@ -21,19 +21,64 @@ Please check that your input is formatted correctly, e.g. <strong>3, 5-10, 12</strong> </div> {% if sample_groups[0].attributes %} - <div class="input-append block-by-attribute-div"> - <label for="exclude_menu">Block samples by group:</label> - <select id="exclude_menu" size=1> + <div class="input-append block-div-2"> + <label for="exclude_column">Block samples by group:</label> + <select id="exclude_column" size=1> {% for attribute in sample_groups[0].attributes %} - <option value="{{ sample_groups[0].attributes[attribute].name.replace(' ', '_') }}"> - {{ sample_groups[0].attributes[attribute].name }}</option> + {% if sample_groups[0].attributes[attribute].distinct_values|length <= 10 %} + <option value="{{ loop.index }}"> + {{ sample_groups[0].attributes[attribute].name }} + </option> + {% endif %} {% endfor %} </select> <select id="attribute_values" size=1> </select> - <input type="button" id="exclude_group" class="btn" value="Block"> + <select id="exclude_by_attr_group" size="1"> + <option value="primary"> + {{ sample_group_types['samples_primary'] }} + </option> + <option value="other"> + {{ sample_group_types['samples_other'] }} + </option> + </select> + <input type="button" id="exclude_by_attr" class="btn btn-danger" value="Block"> </div> {% endif %} + <div id="filterMenuSpan" class="input-append block-div-2"> + <label for="filter_samples_field">Filter samples by {% if not sample_groups[0].attributes %}value{% endif %} </label> + {% if sample_groups[0].attributes %} + <select id="filter_column"> + <option value="value">Value</option> + {% if js_data.se_exists %} + <option value="stderr">SE</option> + {% endif %} + {% for attribute in sample_groups[0].attributes %} + + <option value="{{ loop.index }}"> + {{ sample_groups[0].attributes[attribute].name }} + </option> + + {% endfor %} + </select> + {% endif %} + <select id="filter_logic" size="1"> + <option value="greater_than">></option> + <option value="less_than"><</option> + <option value="greater_or_equal">≥</option> + <option value="less_or_equal">≤</option> + </select> + <input type="text" id="filter_value" placeholder="Example: 3, 10, 15"> + <select id="filter_group" size="1"> + <option value="primary"> + {{ sample_group_types['samples_primary'] }} + </option> + <option value="other"> + {{ sample_group_types['samples_other'] }} + </option> + </select> + <input type="button" id="filter_by_value" class="btn btn-danger" value="Filter"> + </div> <div> <input type="button" id="hide_no_value" class="btn btn-default" value="Hide No Value"> <input type="button" id="block_outliers" class="btn btn-default" value="Block Outliers"> diff --git a/wqflask/wqflask/views.py b/wqflask/wqflask/views.py index bf2e9026..3557a62a 100644 --- a/wqflask/wqflask/views.py +++ b/wqflask/wqflask/views.py @@ -301,28 +301,13 @@ def news(): doc = Docs("news", request.args) return render_template("docs.html", **doc.__dict__) -@app.route("/references") -def references(): - doc = Docs("references", request.args) - # return render_template("reference.html") - return render_template("docs.html", **doc.__dict__) @app.route("/intro") def intro(): doc = Docs("intro", request.args) return render_template("docs.html", **doc.__dict__) -@app.route("/policies") -def policies(): - doc = Docs("policies", request.args) - #return render_template("policies.html") - return render_template("docs.html", **doc.__dict__) -@app.route("/links") -def links(): - #doc = Docs("links", request.args) - #return render_template("docs.html", **doc.__dict__) - return render_template("links.html") @app.route("/tutorials") def tutorials(): @@ -336,12 +321,6 @@ def credits(): #return render_template("docs.html", **doc.__dict__) return render_template("credits.html") -@app.route("/environments") -def environments(): - doc = Docs("environments", request.args) - return render_template("docs.html", **doc.__dict__) - #return render_template("environments.html", **doc.__dict__) - @app.route("/update_text", methods=('POST',)) def update_page(): update_text(request.form) @@ -718,6 +697,8 @@ def mapping_results_page(): 'maf', 'use_loco', 'manhattan_plot', + 'color_scheme', + 'manhattan_single_color', 'control_marker', 'control_marker_db', 'do_control', |
