From df6a70c9a06bc30856a1bc46023bd67e5325f5c9 Mon Sep 17 00:00:00 2001 From: Zachary Sloan Date: Wed, 25 Jun 2014 20:19:02 +0000 Subject: Added Karl's correlation matrix code Improved the "scatterplot matrix" feature on the trait page so that it matches the chosen trait against every selected trait --- wqflask/base/data_set.py | 10 +- wqflask/base/species.py | 6 +- wqflask/base/trait.py | 2 +- wqflask/maintenance/gen_select_dataset.py | 47 +- .../wqflask/correlation_matrix/show_corr_matrix.py | 153 ++- .../wqflask/marker_regression/marker_regression.py | 16 +- wqflask/wqflask/my_pylmm/data/genofile_parser.py | 14 +- wqflask/wqflask/show_trait/show_trait.py | 1 + wqflask/wqflask/static/new/css/charts.css | 28 + .../javascript/compare_traits_scatterplot.coffee | 76 +- .../new/javascript/compare_traits_scatterplot.js | 57 +- .../static/new/javascript/corr_matrix.coffee | 275 ++++ .../wqflask/static/new/javascript/corr_matrix.js | 157 +++ .../new/javascript/create_corr_matrix.coffee | 42 + .../static/new/javascript/create_corr_matrix.js | 47 + .../new/javascript/dataset_menu_structure.json | 1366 +++++++++++++++++--- .../javascript/get_traits_from_collection.coffee | 75 +- .../new/javascript/get_traits_from_collection.js | 77 +- .../wqflask/static/new/javascript/lod_chart.coffee | 24 +- wqflask/wqflask/static/new/javascript/lod_chart.js | 82 +- .../static/new/javascript/marker_regression.coffee | 85 +- .../static/new/javascript/marker_regression.js | 48 +- .../static/new/javascript/show_trait.coffee | 6 +- .../wqflask/static/new/javascript/show_trait.js | 4 + .../new/javascript/show_trait_mapping_tools.coffee | 12 +- .../new/javascript/show_trait_mapping_tools.js | 12 +- wqflask/wqflask/templates/correlation_matrix.html | 19 +- wqflask/wqflask/templates/interval_mapping.html | 6 +- .../templates/show_trait_statistics_new.html | 5 +- wqflask/wqflask/views.py | 7 +- 30 files changed, 2361 insertions(+), 398 deletions(-) create mode 100644 wqflask/wqflask/static/new/css/charts.css create mode 100644 wqflask/wqflask/static/new/javascript/corr_matrix.coffee create mode 100644 wqflask/wqflask/static/new/javascript/corr_matrix.js create mode 100644 wqflask/wqflask/static/new/javascript/create_corr_matrix.coffee create mode 100644 wqflask/wqflask/static/new/javascript/create_corr_matrix.js (limited to 'wqflask') diff --git a/wqflask/base/data_set.py b/wqflask/base/data_set.py index a2b13748..843862aa 100755 --- a/wqflask/base/data_set.py +++ b/wqflask/base/data_set.py @@ -164,6 +164,7 @@ class Markers(object): marker['chr'] = int(marker['chr']) else: marker['chr'] = 19 + print("Mb:", marker['Mb']) marker['Mb'] = float(marker['Mb']) self.markers = markers @@ -670,6 +671,7 @@ class PhenotypeDataSet(DataSet): def get_trait_info(self, trait_list, species = ''): for this_trait in trait_list: + if not this_trait.haveinfo: this_trait.retrieve_info(get_qtl_info=True) @@ -679,6 +681,7 @@ class PhenotypeDataSet(DataSet): #phenotype traits, then display the pre-publication description instead #of the post-publication description if this_trait.confidential: + this_trait.description_display = "" continue # for now if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait( @@ -688,7 +691,12 @@ class PhenotypeDataSet(DataSet): description = this_trait.pre_publication_description - this_trait.description_display = description.strip() + if len(description) > 0: + this_trait.description_display = description.strip() + else: + this_trait.description_display = "" + + print("this_trait.description_display is:", this_trait.description_display) if not this_trait.year.isdigit(): this_trait.pubmed_text = "N/A" diff --git a/wqflask/base/species.py b/wqflask/base/species.py index ebc2bfed..52bd8297 100755 --- a/wqflask/base/species.py +++ b/wqflask/base/species.py @@ -13,7 +13,7 @@ from pprint import pformat as pf class TheSpecies(object): def __init__(self, dataset): self.dataset = dataset - print("self.dataset is:", pf(self.dataset.__dict__)) + #print("self.dataset is:", pf(self.dataset.__dict__)) self.chromosomes = Chromosomes(self.dataset) self.genome_mb_length = self.chromosomes.get_genome_mb_length() @@ -56,8 +56,8 @@ class Chromosomes(object): InbredSet.Name = %s Order by OrderId """, self.dataset.group.name).fetchall() - print("group: ", self.dataset.group.name) - print("bike:", results) + #print("group: ", self.dataset.group.name) + #print("bike:", results) for item in results: self.chromosomes[item.OrderId] = IndChromosome(item.Name, item.Length) diff --git a/wqflask/base/trait.py b/wqflask/base/trait.py index 3f80d4a4..2bbd1f2a 100755 --- a/wqflask/base/trait.py +++ b/wqflask/base/trait.py @@ -645,7 +645,7 @@ def get_sample_data(): trait_ob = GeneralTrait(name=trait, dataset_name=dataset) - return json.dumps({key: value.value for key, value in trait_ob.data.iteritems() }) + return json.dumps([trait, {key: value.value for key, value in trait_ob.data.iteritems() }]) #jsonable_sample_data = {} #for sample in trait_ob.data.iteritems(): diff --git a/wqflask/maintenance/gen_select_dataset.py b/wqflask/maintenance/gen_select_dataset.py index ad560659..694efeca 100755 --- a/wqflask/maintenance/gen_select_dataset.py +++ b/wqflask/maintenance/gen_select_dataset.py @@ -99,7 +99,7 @@ def get_groups(species): def get_types(groups): """Build types list""" types = {} - print("Groups: ", pf(groups)) + #print("Groups: ", pf(groups)) for species, group_dict in groups.iteritems(): types[species] = {} for group_name, _group_full_name in group_dict: @@ -118,15 +118,15 @@ def build_types(species, group): """ - print("""select distinct Tissue.Name - from ProbeFreeze, ProbeSetFreeze, InbredSet, Tissue, Species - where Species.Name = '{}' and Species.Id = InbredSet.SpeciesId and - InbredSet.Name = '{}' and - ProbeFreeze.TissueId = Tissue.Id and - ProbeFreeze.InbredSetId = InbredSet.Id and - ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and - ProbeSetFreeze.public > 0 - order by Tissue.Name""".format(species, group)) + #print("""select distinct Tissue.Name + # from ProbeFreeze, ProbeSetFreeze, InbredSet, Tissue, Species + # where Species.Name = '{}' and Species.Id = InbredSet.SpeciesId and + # InbredSet.Name = '{}' and + # ProbeFreeze.TissueId = Tissue.Id and + # ProbeFreeze.InbredSetId = InbredSet.Id and + # ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and + # ProbeSetFreeze.public > 0 + # order by Tissue.Name""".format(species, group)) Cursor.execute("""select distinct Tissue.Name from ProbeFreeze, ProbeSetFreeze, InbredSet, Tissue, Species where Species.Name = %s and Species.Id = InbredSet.SpeciesId and @@ -150,7 +150,7 @@ def get_datasets(types): for species, group_dict in types.iteritems(): datasets[species] = {} for group, type_list in group_dict.iteritems(): - print("type_list: ", type_list) + #print("type_list: ", type_list) datasets[species][group] = {} for type_name in type_list: datasets[species][group][type_name[0]] = build_datasets(species, group, type_name[0]) @@ -174,14 +174,14 @@ def build_datasets(species, group, type_name): if dataset_value: return [(dataset_value, dataset_text)] else: - print("""select ProbeSetFreeze.Name, ProbeSetFreeze.FullName from - ProbeSetFreeze, ProbeFreeze, InbredSet, Tissue, Species where - Species.Name = '{}' and Species.Id = InbredSet.SpeciesId and - InbredSet.Name = '{}' and - ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and Tissue.Name = '{}' - and ProbeFreeze.TissueId = Tissue.Id and ProbeFreeze.InbredSetId = - InbredSet.Id and ProbeSetFreeze.public > 0 order by - ProbeSetFreeze.CreateTime desc""".format(species, group, type_name)) + #print("""select ProbeSetFreeze.Name, ProbeSetFreeze.FullName from + # ProbeSetFreeze, ProbeFreeze, InbredSet, Tissue, Species where + # Species.Name = '{}' and Species.Id = InbredSet.SpeciesId and + # InbredSet.Name = '{}' and + # ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and Tissue.Name = '{}' + # and ProbeFreeze.TissueId = Tissue.Id and ProbeFreeze.InbredSetId = + # InbredSet.Id and ProbeSetFreeze.public > 0 order by + # ProbeSetFreeze.CreateTime desc""".format(species, group, type_name)) Cursor.execute("""select ProbeSetFreeze.Name, ProbeSetFreeze.FullName from ProbeSetFreeze, ProbeFreeze, InbredSet, Tissue, Species where Species.Name = %s and Species.Id = InbredSet.SpeciesId and @@ -200,6 +200,7 @@ def main(): species = get_species() groups = get_groups(species) + print("groups:", groups) types = get_types(groups) datasets = get_datasets(types) @@ -217,22 +218,22 @@ def main(): datasets=datasets, ) - print("data:", data) + #print("data:", data) output_file = """../wqflask/static/new/javascript/dataset_menu_structure.json""" with open(output_file, 'w') as fh: json.dump(data, fh, indent=" ", sort_keys=True) - print("\nWrote file to:", output_file) + #print("\nWrote file to:", output_file) def _test_it(): """Used for internal testing only""" types = build_types("Mouse", "BXD") - print("build_types:", pf(types)) + #print("build_types:", pf(types)) datasets = build_datasets("Mouse", "BXD", "Hippocampus") - print("build_datasets:", pf(datasets)) + #print("build_datasets:", pf(datasets)) if __name__ == '__main__': Conn = MySQLdb.Connect(**parse_db_uri(our_settings.DB_URI)) diff --git a/wqflask/wqflask/correlation_matrix/show_corr_matrix.py b/wqflask/wqflask/correlation_matrix/show_corr_matrix.py index b556927c..4069b07f 100755 --- a/wqflask/wqflask/correlation_matrix/show_corr_matrix.py +++ b/wqflask/wqflask/correlation_matrix/show_corr_matrix.py @@ -66,30 +66,118 @@ class CorrelationMatrix(object): self.get_trait_db_obs(trait_db_list) - self.corr_results = {} + #self.corr_results = {} + #for trait_db in self.trait_list: + # this_trait = trait_db[0] + # this_db = trait_db[1] + # + # this_db_samples = this_db.group.samplelist + # this_sample_data = this_trait.data + # print("this_sample_data", len(this_sample_data)) + # + # corr_result_row = {} + # + # for target in self.trait_list: + # target_trait = target[0] + # target_db = target[1] + # target_samples = target_db.group.samplelist + # + # if this_trait == target_trait and this_db == target_db: + # corr_result_row[this_trait.name] = {'sample_r': 1, + # 'sample_p': 0, + # 'num_overlap': len(target_samples), + # 'this_trait': this_trait.name, + # 'this_db': this_trait.dataset.name, + # 'target_trait': this_trait.name, + # 'target_db': this_trait.dataset.name} + # continue + # + # target_sample_data = target_trait.data + # print("target_samples", len(target_samples)) + # + # this_trait_vals = [] + # target_vals = [] + # for index, sample in enumerate(target_samples): + # + # if (sample in this_sample_data) and (sample in target_sample_data): + # sample_value = this_sample_data[sample].value + # target_sample_value = target_sample_data[sample].value + # this_trait_vals.append(sample_value) + # target_vals.append(target_sample_value) + # + # #print("this_trait_vals:", this_trait_vals) + # #print("target_vals:", target_vals) + # + # this_trait_vals, target_vals, num_overlap = corr_result_helpers.normalize_values( + # this_trait_vals, target_vals) + # + # sample_r, sample_p = scipy.stats.pearsonr(this_trait_vals, target_vals) + # + # corr_matrix_cell = {"sample_r": sample_r, + # "sample_p": sample_p, + # "num_overlap": num_overlap, + # "this_trait": this_trait.name, + # "this_db": this_trait.dataset.name, + # "target_trait": target_trait.name, + # "target_db": target_trait.dataset.name} + # + # corr_result_row[target_trait.name] = corr_matrix_cell + # + # self.corr_results[this_trait.name] = corr_result_row + + self.all_sample_list = [] + self.traits = [] + for trait_db in self.trait_list: + this_trait = trait_db[0] + self.traits.append(this_trait.name) + this_sample_data = this_trait.data + + for sample in this_sample_data: + if sample not in self.all_sample_list: + self.all_sample_list.append(sample) + + self.sample_data = [] + for trait_db in self.trait_list: + this_trait = trait_db[0] + this_sample_data = this_trait.data + + #self.sample_data[this_trait.name] = [] + this_trait_vals = [] + for sample in self.all_sample_list: + if sample in this_sample_data: + this_trait_vals.append(this_sample_data[sample].value) + #self.sample_data[this_trait.name].append(this_sample_data[sample].value) + else: + this_trait_vals.append('') + #self.sample_data[this_trait.name].append('') + self.sample_data.append(this_trait_vals) + + self.corr_results = [] for trait_db in self.trait_list: this_trait = trait_db[0] this_db = trait_db[1] this_db_samples = this_db.group.samplelist + + #for sample in this_db_samples: + # if sample not in self.samples: + # self.samples.append(sample) + this_sample_data = this_trait.data print("this_sample_data", len(this_sample_data)) - corr_result_row = {} - + #for sample in this_sample_data: + # if sample not in self.all_sample_list: + # self.all_sample_list.append(sample) + + corr_result_row = [] for target in self.trait_list: target_trait = target[0] target_db = target[1] - target_samples = target_db.group.samplelist + target_samples = target_db.group.samplelist if this_trait == target_trait and this_db == target_db: - corr_result_row[this_trait.name] = {'sample_r': 1, - 'sample_p': 0, - 'num_overlap': len(target_samples), - 'this_trait': this_trait.name, - 'this_db': this_trait.dataset.name, - 'target_trait': this_trait.name, - 'target_db': this_trait.dataset.name} + corr_result_row.append(1) continue target_sample_data = target_trait.data @@ -113,19 +201,38 @@ class CorrelationMatrix(object): sample_r, sample_p = scipy.stats.pearsonr(this_trait_vals, target_vals) - corr_matrix_cell = {'sample_r': sample_r, - 'sample_p': sample_p, - 'num_overlap': num_overlap, - 'this_trait': this_trait.name, - 'this_db': this_trait.dataset.name, - 'target_trait': target_trait.name, - 'target_db': target_trait.dataset.name} + corr_result_row.append(sample_r) - corr_result_row[target_trait.name] = corr_matrix_cell - - self.corr_results[this_trait.name] = corr_result_row - - print("corr_results:", pf(self.corr_results)) + self.corr_results.append(corr_result_row) + + #self.sample_data = {} + #for trait_db in self.trait_list: + # this_trait = trait_db[0] + # + # this_sample_data = this_trait.data + # + # self.sample_data[this_trait.name] = [] + # for sample in self.all_sample_list: + # if sample in this_sample_data: + # self.sample_data[this_trait.name].append(this_sample_data[sample].value) + # else: + # self.sample_data[this_trait.name].append('') + + print("corr_results:", pf(self.traits)) + + groups = [] + for sample in self.all_sample_list: + groups.append(1) + + self.js_data = dict(traits = self.traits, + groups = groups, + cols = range(len(self.traits)), + rows = range(len(self.traits)), + samples = self.all_sample_list, + sample_data = self.sample_data, + corr_results = self.corr_results,) + + def get_trait_db_obs(self, trait_db_list): diff --git a/wqflask/wqflask/marker_regression/marker_regression.py b/wqflask/wqflask/marker_regression/marker_regression.py index 525a2253..d43fe37c 100755 --- a/wqflask/wqflask/marker_regression/marker_regression.py +++ b/wqflask/wqflask/marker_regression/marker_regression.py @@ -56,7 +56,8 @@ class MarkerRegression(object): self.vals.append(value) self.mapping_method = start_vars['method'] - print("self.mapping_method:", self.mapping_method) + self.maf = start_vars['maf'] # Minor allele frequency + print("self.maf:", self.maf) if self.mapping_method == "gemma": qtl_results = self.run_gemma() @@ -64,9 +65,12 @@ class MarkerRegression(object): qtl_results = self.run_plink() #print("qtl_results:", pf(qtl_results)) elif self.mapping_method == "pylmm": + print("RUNNING PYLMM") #self.qtl_results = self.gen_data(tempdata) qtl_results = self.gen_data(str(temp_uuid)) - + else: + print("RUNNING NOTHING") + self.lod_cutoff = 2 self.filtered_markers = [] for marker in qtl_results: @@ -83,6 +87,9 @@ class MarkerRegression(object): chromosome_mb_lengths[key] = self.species.chromosomes.chromosomes[key].mb_length self.js_data = dict( + this_trait = self.this_trait.name, + data_set = self.dataset.name, + maf = self.maf, chromosomes = chromosome_mb_lengths, qtl_results = self.filtered_markers, ) @@ -169,7 +176,7 @@ class MarkerRegression(object): self.gen_pheno_txt_file_plink(pheno_filename = plink_output_filename) - plink_command = './plink --noweb --ped %s.ped --no-fid --no-parents --no-sex --no-pheno --map %s.map --pheno %s/%s.txt --pheno-name %s --missing-phenotype -9999 --out %s%s --assoc ' % (self.dataset.group.name, self.dataset.group.name, webqtlConfig.TMPDIR, plink_output_filename, self.this_trait.name, webqtlConfig.TMPDIR, plink_output_filename) + plink_command = './plink --noweb --ped %s.ped --no-fid --no-parents --no-sex --no-pheno --map %s.map --pheno %s/%s.txt --pheno-name %s --maf %s --missing-phenotype -9999 --out %s%s --assoc ' % (self.dataset.group.name, self.dataset.group.name, webqtlConfig.TMPDIR, plink_output_filename, self.this_trait.name, self.maf, webqtlConfig.TMPDIR, plink_output_filename) os.system(plink_command) @@ -382,6 +389,7 @@ class MarkerRegression(object): #p_values = self.trim_results(p_values) else: + print("NOW CWD IS:", os.getcwd()) genotype_data = [marker['genotypes'] for marker in self.dataset.group.markers.markers] no_val_samples = self.identify_empty_samples() @@ -410,7 +418,7 @@ class MarkerRegression(object): ) json_params = json.dumps(params) - print("json_params:", json_params) + #print("json_params:", json_params) Redis.set(key, json_params) Redis.expire(key, 60*60) print("before printing command") diff --git a/wqflask/wqflask/my_pylmm/data/genofile_parser.py b/wqflask/wqflask/my_pylmm/data/genofile_parser.py index 4ebadb6e..baf6aee4 100755 --- a/wqflask/wqflask/my_pylmm/data/genofile_parser.py +++ b/wqflask/wqflask/my_pylmm/data/genofile_parser.py @@ -44,6 +44,7 @@ class ConvertGenoFile(object): self.output_file = output_file self.mb_exists = False + self.cm_exists = False self.markers = [] self.latest_row_pos = None @@ -94,7 +95,10 @@ class ConvertGenoFile(object): this_marker.name = row_items[1] this_marker.chr = row_items[0] #this_marker.cM = row_items[2] - if self.mb_exists: + if self.cm_exists and self.mb_exists: + this_marker.Mb = row_items[3] + genotypes = row_items[4:] + elif self.mb_exists: this_marker.Mb = row_items[2] genotypes = row_items[3:] else: @@ -106,8 +110,8 @@ class ConvertGenoFile(object): this_marker.genotypes.append("NA") #print("this_marker is:", pf(this_marker.__dict__)) - if this_marker.chr == "14": - self.markers.append(this_marker.__dict__) + #if this_marker.chr == "14": + self.markers.append(this_marker.__dict__) with open(self.output_file, 'w') as fh: json.dump(self.markers, fh, indent=" ", sort_keys=True) @@ -136,6 +140,8 @@ class ConvertGenoFile(object): if row.startswith('Chr'): if 'Mb' in row.split(): self.mb_exists = True + if 'cM' in row.split(): + self.cm_exists = True continue if row.startswith('@'): key, _separater, value = row.partition(':') @@ -187,7 +193,7 @@ if __name__=="__main__": New_Geno_Directory = """/home/zas1024/gene/web/new_genotypes/""" #Input_File = """/home/zas1024/gene/web/genotypes/BXD.geno""" #Output_File = """/home/zas1024/gene/wqflask/wqflask/pylmm/data/bxd.snps""" - convertob = ConvertGenoFile("/home/zas1024/gene/web/genotypes/HSNIH.geno.gz", "/home/zas1024/gene/web/new_genotypes/HSNIH.json") + convertob = ConvertGenoFile("/home/zas1024/gene/web/genotypes/Linsenbardt-Boehm.geno", "/home/zas1024/gene/web/new_genotypes/Linsenbardt-Boehm.json") convertob.convert() #ConvertGenoFile.process_all(Old_Geno_Directory, New_Geno_Directory) #ConvertGenoFiles(Geno_Directory) diff --git a/wqflask/wqflask/show_trait/show_trait.py b/wqflask/wqflask/show_trait/show_trait.py index c0403bbd..670a1188 100755 --- a/wqflask/wqflask/show_trait/show_trait.py +++ b/wqflask/wqflask/show_trait/show_trait.py @@ -1193,6 +1193,7 @@ class ShowTrait(object): primary_sample_names = all_samples_ordered + print("self.dataset.group", pf(self.dataset.group.__dict__)) print("-*- primary_samplelist is:", pf(primary_sample_names)) other_sample_names = [] diff --git a/wqflask/wqflask/static/new/css/charts.css b/wqflask/wqflask/static/new/css/charts.css new file mode 100644 index 00000000..5f2d4d23 --- /dev/null +++ b/wqflask/wqflask/static/new/css/charts.css @@ -0,0 +1,28 @@ +body { + font-family: sans-serif; +} + +svg { + margin-top: 10px; + margin-left: 50px; +} + +.line { + stroke-width: 1; + fill: none; +} + +text { + font-family: sans-serif; + font-size: 11pt; +} + +p { + font-family: sans-serif; + font-size: 12pt; +} + +p#caption { + margin-left: 100px; + width: 500px; +} diff --git a/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.coffee b/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.coffee index 73eb1466..64400c7d 100644 --- a/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.coffee +++ b/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.coffee @@ -2,7 +2,7 @@ root = exports ? this root.create_scatterplot = (json_ids, json_data) -> - console.log("TESTING TESTING2") + console.log("TESTING2") h = 400 w = 500 @@ -38,49 +38,81 @@ root.create_scatterplot = (json_ids, json_data) -> .on "mouseout", (d) -> d3.select(this).attr("r", mychart.pointsize()) -root.create_scatterplots = (json_ids, json_data) -> - h = 400 - w = 500 +root.create_scatterplots = (trait_names, json_ids, json_data) -> + + #There are various places where 1 is subtracted from the number of traits; this is because + #we don't want to show a first graph consisting of the trait vs itself. There might be a better + #way to deal with this. + + console.log("json_data:", json_data) + console.log("trait_names:", trait_names) + + num_traits = json_data.length + console.log("num_traits:", num_traits) + + h = 300 + w = 400 margin = {left:60, top:40, right:40, bottom: 40, inner:5} halfh = (h+margin.top+margin.bottom) - totalh = halfh*2 + totalh = halfh*(num_traits-1) + #totalh = halfh*2 halfw = (w+margin.left+margin.right) - totalw = halfw*2 + #totalw = halfw*2 + totalw = halfw + + xvar = [] + yvar = [] + xshift = [] + yshift = [] + for i in [0..num_traits-1] + xvar.push(i) + yvar.push(0) + xshift.push(0) + yshift.push(halfh*i) + + console.log("xvar:", xvar) + console.log("yvar:", yvar) # Example 2: three scatterplots within one SVG, with brushing #d3.json "data.json", (data) -> - xvar = [1, 2, 2] - yvar = [0, 0, 1] - xshift = [0, halfw, halfw] - yshift = [0, 0, halfh] - - svg = d3.select("div#chart2") + #xvar = [1, 2, 2] + #yvar = [0, 0, 1] + #console.log("num_traits_array:", xvar) + #xshift = [0, halfw, halfw] + #yshift = [0, 0, halfh] + #xshift = [0, 0] + #yshift = [0, halfh] + + svg = d3.select("div#comparison_scatterplot") .append("svg") .attr("height", totalh) .attr("width", totalw) mychart = [] chart = [] - for i in [0..2] - mychart[i] = scatterplot().xvar(xvar[i]) + for i in [1..num_traits-1] + mychart[i-1] = scatterplot().xvar(xvar[i]) .yvar(yvar[i]) .nxticks(6) .height(h) .width(w) .margin(margin) .pointsize(4) - .xlab("X#{xvar[i]+1}") - .ylab("X#{yvar[i]+1}") - .title("X#{yvar[i]+1} vs. X#{xvar[i]+1}") + .xlab("#{trait_names[i-1]}") + .ylab("#{trait_names[0]}") + .title("#{trait_names[0]} vs. #{trait_names[i-1]}") + + data = json_data + indID = json_ids - chart[i] = svg.append("g").attr("id", "chart#{i}") - .attr("transform", "translate(#{xshift[i]},#{yshift[i]})") - chart[i].datum({data:data}).call(mychart[i]) + chart[i-1] = svg.append("g").attr("id", "chart#{i-1}") + .attr("transform", "translate(#{xshift[i]},#{yshift[i-1]})") + chart[i-1].datum({data:data, indID:indID}).call(mychart[i-1]) brush = [] brushstart = (i) -> () -> - for j in [0..2] + for j in [0..num_traits-2] chart[j].call(brush[j].clear()) if j != i svg.selectAll("circle").attr("opacity", 0.6).classed("selected", false) @@ -104,7 +136,7 @@ root.create_scatterplots = (json_ids, json_data) -> xscale = d3.scale.linear().domain([margin.left,margin.left+w]).range([margin.left,margin.left+w]) yscale = d3.scale.linear().domain([margin.top,margin.top+h]).range([margin.top,margin.top+h]) - for i in [0..2] + for i in [0..num_traits-2] brush[i] = d3.svg.brush().x(xscale).y(yscale) .on("brushstart", brushstart(i)) .on("brush", brushmove(i)) diff --git a/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.js b/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.js index c1596a14..a45eb3c0 100644 --- a/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.js +++ b/wqflask/wqflask/static/new/javascript/compare_traits_scatterplot.js @@ -6,7 +6,7 @@ root.create_scatterplot = function(json_ids, json_data) { var data, h, halfh, halfw, indID, margin, mychart, totalh, totalw, w; - console.log("TESTING TESTING2"); + console.log("TESTING2"); h = 400; w = 500; margin = { @@ -34,10 +34,14 @@ }); }; - root.create_scatterplots = function(json_ids, json_data) { - var brush, brushend, brushmove, brushstart, chart, h, halfh, halfw, i, margin, mychart, svg, totalh, totalw, w, xscale, xshift, xvar, yscale, yshift, yvar, _i, _j, _results; - h = 400; - w = 500; + root.create_scatterplots = function(trait_names, json_ids, json_data) { + var brush, brushend, brushmove, brushstart, chart, data, h, halfh, halfw, i, indID, margin, mychart, num_traits, svg, totalh, totalw, w, xscale, xshift, xvar, yscale, yshift, yvar, _i, _j, _k, _ref, _ref1, _ref2, _results; + console.log("json_data:", json_data); + console.log("trait_names:", trait_names); + num_traits = json_data.length; + console.log("num_traits:", num_traits); + h = 300; + w = 400; margin = { left: 60, top: 40, @@ -46,28 +50,39 @@ inner: 5 }; halfh = h + margin.top + margin.bottom; - totalh = halfh * 2; + totalh = halfh * (num_traits - 1); halfw = w + margin.left + margin.right; - totalw = halfw * 2; - xvar = [1, 2, 2]; - yvar = [0, 0, 1]; - xshift = [0, halfw, halfw]; - yshift = [0, 0, halfh]; - svg = d3.select("div#chart2").append("svg").attr("height", totalh).attr("width", totalw); + totalw = halfw; + xvar = []; + yvar = []; + xshift = []; + yshift = []; + for (i = _i = 0, _ref = num_traits - 1; 0 <= _ref ? _i <= _ref : _i >= _ref; i = 0 <= _ref ? ++_i : --_i) { + xvar.push(i); + yvar.push(0); + xshift.push(0); + yshift.push(halfh * i); + } + console.log("xvar:", xvar); + console.log("yvar:", yvar); + svg = d3.select("div#comparison_scatterplot").append("svg").attr("height", totalh).attr("width", totalw); mychart = []; chart = []; - for (i = _i = 0; _i <= 2; i = ++_i) { - mychart[i] = scatterplot().xvar(xvar[i]).yvar(yvar[i]).nxticks(6).height(h).width(w).margin(margin).pointsize(4).xlab("X" + (xvar[i] + 1)).ylab("X" + (yvar[i] + 1)).title("X" + (yvar[i] + 1) + " vs. X" + (xvar[i] + 1)); - chart[i] = svg.append("g").attr("id", "chart" + i).attr("transform", "translate(" + xshift[i] + "," + yshift[i] + ")"); - chart[i].datum({ - data: data - }).call(mychart[i]); + for (i = _j = 1, _ref1 = num_traits - 1; 1 <= _ref1 ? _j <= _ref1 : _j >= _ref1; i = 1 <= _ref1 ? ++_j : --_j) { + mychart[i - 1] = scatterplot().xvar(xvar[i]).yvar(yvar[i]).nxticks(6).height(h).width(w).margin(margin).pointsize(4).xlab("" + trait_names[i - 1]).ylab("" + trait_names[0]).title("" + trait_names[0] + " vs. " + trait_names[i - 1]); + data = json_data; + indID = json_ids; + chart[i - 1] = svg.append("g").attr("id", "chart" + (i - 1)).attr("transform", "translate(" + xshift[i] + "," + yshift[i - 1] + ")"); + chart[i - 1].datum({ + data: data, + indID: indID + }).call(mychart[i - 1]); } brush = []; brushstart = function(i) { return function() { - var j, _j; - for (j = _j = 0; _j <= 2; j = ++_j) { + var j, _k, _ref2; + for (j = _k = 0, _ref2 = num_traits - 2; 0 <= _ref2 ? _k <= _ref2 : _k >= _ref2; j = 0 <= _ref2 ? ++_k : --_k) { if (j !== i) { chart[j].call(brush[j].clear()); } @@ -99,7 +114,7 @@ xscale = d3.scale.linear().domain([margin.left, margin.left + w]).range([margin.left, margin.left + w]); yscale = d3.scale.linear().domain([margin.top, margin.top + h]).range([margin.top, margin.top + h]); _results = []; - for (i = _j = 0; _j <= 2; i = ++_j) { + for (i = _k = 0, _ref2 = num_traits - 2; 0 <= _ref2 ? _k <= _ref2 : _k >= _ref2; i = 0 <= _ref2 ? ++_k : --_k) { brush[i] = d3.svg.brush().x(xscale).y(yscale).on("brushstart", brushstart(i)).on("brush", brushmove(i)).on("brushend", brushend); _results.push(chart[i].call(brush[i])); } diff --git a/wqflask/wqflask/static/new/javascript/corr_matrix.coffee b/wqflask/wqflask/static/new/javascript/corr_matrix.coffee new file mode 100644 index 00000000..4ecee1d4 --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/corr_matrix.coffee @@ -0,0 +1,275 @@ +# iplotCorr.coffee +# +# Left panel is a heat map of a correlation matrix; hover over pixels +# to see the values; click to see the corresponding scatterplot on the right + +root = exports ? this + +iplotCorr = (data, chartOpts) -> + + # data is an object with 7 components + # data.indID vector of character strings, of length n, with IDs for individuals + # data.var vector of character strings, of length p, with variable names + # data.corr matrix of correlation values, of dim q x r, with q and r each <= p + # data.rows vector of indicators, of length q, with values in {0, 1, ..., p-1}, + # for each row in data.corr, it says which is the corresponding column in data.dat + # data.cols vector of indicators, of length r, with values in {0, 1, ..., p-1} + # for each column in data.corr, it says which is the corresponding column in data.dat + # data.dat numeric matrix, of dim n x p, with data to be plotted in scatterplots + # rows correspond to data.indID and columns to data.var + # data.group numeric vector, of length n, with values in {1, ..., k}, + # used as categories for coloring points in the scatterplot + + # chartOpts start + height = chartOpts?.height ? 450 # height of each panel in pixels + width = chartOpts?.width ? height # width of each panel in pixels + margin = chartOpts?.margin ? {left:70, top:40, right:5, bottom: 70, inner:5} # margins in pixels (left, top, right, bottom, inner) + corcolors = chartOpts?.corcolors ? ["darkslateblue", "white", "crimson"] # heat map colors (same length as `zlim`) + zlim = chartOpts?.zlim ? [-1, 0, 1] # z-axis limits + rectcolor = chartOpts?.rectcolor ? d3.rgb(230, 230, 230) # color of background rectangle + cortitle = chartOpts?.cortitle ? "" # title for heatmap panel + scattitle = chartOpts?.scattitle ? "" # title for scatterplot panel + scatcolors = chartOpts?.scatcolors ? null # vector of point colors for scatterplot + # chartOpts end + chartdivid = chartOpts?.chartdivid ? 'chart' + + totalh = height + margin.top + margin.bottom + totalw = (width + margin.left + margin.right)*2 + + svg = d3.select("div##{chartdivid}") + .append("svg") + .attr("height", totalh) + .attr("width", totalw) + + # panel for correlation image + corrplot = svg.append("g") + .attr("id", "corplot") + .attr("transform", "translate(#{margin.left},#{margin.top})") + + # panel for scatterplot + scatterplot = svg.append("g") + .attr("id", "scatterplot") + .attr("transform", "translate(#{margin.left*2+margin.right+width},#{margin.top})") + + # no. data points + nind = data.indID.length + nvar = data.var.length + ncorrX = data.cols.length + ncorrY = data.rows.length + + corXscale = d3.scale.ordinal().domain(d3.range(ncorrX)).rangeBands([0, width]) + corYscale = d3.scale.ordinal().domain(d3.range(ncorrY)).rangeBands([height, 0]) + corZscale = d3.scale.linear().domain(zlim).range(corcolors) + pixel_width = corXscale(1)-corXscale(0) + pixel_height = corYscale(0)-corYscale(1) + + # create list with correlations + corr = [] + for i of data.corr + for j of data.corr[i] + corr.push({row:i, col:j, value:data.corr[i][j]}) + + + # gray background on scatterplot + scatterplot.append("rect") + .attr("height", height) + .attr("width", width) + .attr("fill", rectcolor) + .attr("stroke", "black") + .attr("stroke-width", 1) + .attr("pointer-events", "none") + + corr_tip = d3.tip() + .attr('class', 'd3-tip') + .html((d) -> d3.format(".2f")(d.value)) + .direction('e') + .offset([0,10]) + corrplot.call(corr_tip) + + + cells = corrplot.selectAll("empty") + .data(corr) + .enter().append("rect") + .attr("class", "cell") + .attr("x", (d) -> corXscale(d.col)) + .attr("y", (d) -> corYscale(d.row)) + .attr("width", corXscale.rangeBand()) + .attr("height", corYscale.rangeBand()) + .attr("fill", (d) -> corZscale(d.value)) + .attr("stroke", "none") + .attr("stroke-width", 2) + .on("mouseover", (d) -> + d3.select(this).attr("stroke", "black") + corr_tip.show(d) + corrplot.append("text").attr("class","corrlabel") + .attr("x", corXscale(d.col)+pixel_width/2) + .attr("y", height+margin.bottom*0.2) + .text(data.var[data.cols[d.col]]) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "middle") + corrplot.append("text").attr("class","corrlabel") + .attr("y", corYscale(d.row)+pixel_height/2) + .attr("x", -margin.left*0.1) + .text(data.var[data.rows[d.row]]) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "end")) + .on("mouseout", (d) -> + corr_tip.hide(d) + d3.selectAll("text.corrlabel").remove() + d3.select(this).attr("stroke","none")) + .on("click",(d) -> drawScatter(d.col, d.row)) + + # colors for scatterplot + nGroup = d3.max(data.group) + if !(scatcolors?) or scatcolors.length < nGroup + if nGroup == 1 + scatcolors = [ d3.rgb(150, 150, 150) ] + else if nGroup <= 3 + scatcolors = ["crimson", "green", "darkslateblue"] + else + if nGroup <= 10 + colorScale = d3.scale.category10() + else + colorScale = d3.scale.category20() + scatcolors = (colorScale(i) for i of d3.range(nGroup)) + + scat_tip = d3.tip() + .attr('class', 'd3-tip') + .html((d,i) -> data.indID[i]) + .direction('e') + .offset([0,10]) + scatterplot.call(scat_tip) + + drawScatter = (i,j) -> + d3.selectAll("circle.points").remove() + d3.selectAll("text.axes").remove() + d3.selectAll("line.axes").remove() + console.log("data.dat:", data.dat) + console.log("data.cols:", data.cols) + xScale = d3.scale.linear() + .domain(d3.extent(data.dat[data.cols[i]])) + .range([margin.inner, width-margin.inner]) + yScale = d3.scale.linear() + .domain(d3.extent(data.dat[data.rows[j]])) + .range([height-margin.inner, margin.inner]) + # axis labels + scatterplot.append("text") + .attr("id", "xaxis") + .attr("class", "axes") + .attr("x", width/2) + .attr("y", height+margin.bottom*0.7) + .text(data.var[data.cols[i]]) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "middle") + .attr("fill", "slateblue") + scatterplot.append("text") + .attr("id", "yaxis") + .attr("class", "axes") + .attr("x", -margin.left*0.8) + .attr("y", height/2) + .text(data.var[data.rows[j]]) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "middle") + .attr("transform", "rotate(270,#{-margin.left*0.8},#{height/2})") + .attr("fill", "slateblue") + # axis scales + xticks = xScale.ticks(5) + yticks = yScale.ticks(5) + scatterplot.selectAll("empty") + .data(xticks) + .enter() + .append("text") + .attr("class", "axes") + .text((d) -> formatAxis(xticks)(d)) + .attr("x", (d) -> xScale(d)) + .attr("y", height+margin.bottom*0.3) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "middle") + scatterplot.selectAll("empty") + .data(yticks) + .enter() + .append("text") + .attr("class", "axes") + .text((d) -> formatAxis(yticks)(d)) + .attr("x", -margin.left*0.1) + .attr("y", (d) -> yScale(d)) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "end") + scatterplot.selectAll("empty") + .data(xticks) + .enter() + .append("line") + .attr("class", "axes") + .attr("x1", (d) -> xScale(d)) + .attr("x2", (d) -> xScale(d)) + .attr("y1", 0) + .attr("y2", height) + .attr("stroke", "white") + .attr("stroke-width", 1) + scatterplot.selectAll("empty") + .data(yticks) + .enter() + .append("line") + .attr("class", "axes") + .attr("y1", (d) -> yScale(d)) + .attr("y2", (d) -> yScale(d)) + .attr("x1", 0) + .attr("x2", width) + .attr("stroke", "white") + .attr("stroke-width", 1) + # the points + scatterplot.selectAll("empty") + .data(d3.range(nind)) + .enter() + .append("circle") + .attr("class", "points") + .attr("cx", (d) -> xScale(data.dat[data.cols[i]][d])) + .attr("cy", (d) -> yScale(data.dat[data.rows[j]][d])) + .attr("r", (d) -> + x = data.dat[data.cols[i]][d] + y = data.dat[data.rows[j]][d] + if x? and y? then 3 else null) + .attr("stroke", "black") + .attr("stroke-width", 1) + .attr("fill", (d) -> scatcolors[data.group[d]-1]) + .on("mouseover", scat_tip.show) + .on("mouseout", scat_tip.hide) + + # boxes around panels + corrplot.append("rect") + .attr("height", height) + .attr("width", width) + .attr("fill", "none") + .attr("stroke", "black") + .attr("stroke-width", 1) + .attr("pointer-events", "none") + + scatterplot.append("rect") + .attr("height", height) + .attr("width", width) + .attr("fill", "none") + .attr("stroke", "black") + .attr("stroke-width", 1) + .attr("pointer-events", "none") + + # text above + corrplot.append("text") + .text(cortitle) + .attr("id", "corrtitle") + .attr("x", width/2) + .attr("y", -margin.top/2) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "middle") + + scatterplot.append("text") + .text(scattitle) + .attr("id", "scattitle") + .attr("x", width/2) + .attr("y", -margin.top/2) + .attr("dominant-baseline", "middle") + .attr("text-anchor", "middle") + + d3.select("div#caption") + .style("opacity", 1) + +root.corr_matrix = iplotCorr \ No newline at end of file diff --git a/wqflask/wqflask/static/new/javascript/corr_matrix.js b/wqflask/wqflask/static/new/javascript/corr_matrix.js new file mode 100644 index 00000000..17625f99 --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/corr_matrix.js @@ -0,0 +1,157 @@ +// Generated by CoffeeScript 1.6.1 +(function() { + var iplotCorr, root; + + root = typeof exports !== "undefined" && exports !== null ? exports : this; + + iplotCorr = function(data, chartOpts) { + var cells, chartdivid, colorScale, corXscale, corYscale, corZscale, corcolors, corr, corr_tip, corrplot, cortitle, drawScatter, height, i, j, margin, nGroup, ncorrX, ncorrY, nind, nvar, pixel_height, pixel_width, rectcolor, scat_tip, scatcolors, scatterplot, scattitle, svg, totalh, totalw, width, zlim, _ref, _ref1, _ref2, _ref3, _ref4, _ref5, _ref6, _ref7, _ref8, _ref9; + height = (_ref = chartOpts != null ? chartOpts.height : void 0) != null ? _ref : 450; + width = (_ref1 = chartOpts != null ? chartOpts.width : void 0) != null ? _ref1 : height; + margin = (_ref2 = chartOpts != null ? chartOpts.margin : void 0) != null ? _ref2 : { + left: 70, + top: 40, + right: 5, + bottom: 70, + inner: 5 + }; + corcolors = (_ref3 = chartOpts != null ? chartOpts.corcolors : void 0) != null ? _ref3 : ["darkslateblue", "white", "crimson"]; + zlim = (_ref4 = chartOpts != null ? chartOpts.zlim : void 0) != null ? _ref4 : [-1, 0, 1]; + rectcolor = (_ref5 = chartOpts != null ? chartOpts.rectcolor : void 0) != null ? _ref5 : d3.rgb(230, 230, 230); + cortitle = (_ref6 = chartOpts != null ? chartOpts.cortitle : void 0) != null ? _ref6 : ""; + scattitle = (_ref7 = chartOpts != null ? chartOpts.scattitle : void 0) != null ? _ref7 : ""; + scatcolors = (_ref8 = chartOpts != null ? chartOpts.scatcolors : void 0) != null ? _ref8 : null; + chartdivid = (_ref9 = chartOpts != null ? chartOpts.chartdivid : void 0) != null ? _ref9 : 'chart'; + totalh = height + margin.top + margin.bottom; + totalw = (width + margin.left + margin.right) * 2; + svg = d3.select("div#" + chartdivid).append("svg").attr("height", totalh).attr("width", totalw); + corrplot = svg.append("g").attr("id", "corplot").attr("transform", "translate(" + margin.left + "," + margin.top + ")"); + scatterplot = svg.append("g").attr("id", "scatterplot").attr("transform", "translate(" + (margin.left * 2 + margin.right + width) + "," + margin.top + ")"); + nind = data.indID.length; + nvar = data["var"].length; + ncorrX = data.cols.length; + ncorrY = data.rows.length; + corXscale = d3.scale.ordinal().domain(d3.range(ncorrX)).rangeBands([0, width]); + corYscale = d3.scale.ordinal().domain(d3.range(ncorrY)).rangeBands([height, 0]); + corZscale = d3.scale.linear().domain(zlim).range(corcolors); + pixel_width = corXscale(1) - corXscale(0); + pixel_height = corYscale(0) - corYscale(1); + corr = []; + for (i in data.corr) { + for (j in data.corr[i]) { + corr.push({ + row: i, + col: j, + value: data.corr[i][j] + }); + } + } + scatterplot.append("rect").attr("height", height).attr("width", width).attr("fill", rectcolor).attr("stroke", "black").attr("stroke-width", 1).attr("pointer-events", "none"); + corr_tip = d3.tip().attr('class', 'd3-tip').html(function(d) { + return d3.format(".2f")(d.value); + }).direction('e').offset([0, 10]); + corrplot.call(corr_tip); + cells = corrplot.selectAll("empty").data(corr).enter().append("rect").attr("class", "cell").attr("x", function(d) { + return corXscale(d.col); + }).attr("y", function(d) { + return corYscale(d.row); + }).attr("width", corXscale.rangeBand()).attr("height", corYscale.rangeBand()).attr("fill", function(d) { + return corZscale(d.value); + }).attr("stroke", "none").attr("stroke-width", 2).on("mouseover", function(d) { + d3.select(this).attr("stroke", "black"); + corr_tip.show(d); + corrplot.append("text").attr("class", "corrlabel").attr("x", corXscale(d.col) + pixel_width / 2).attr("y", height + margin.bottom * 0.2).text(data["var"][data.cols[d.col]]).attr("dominant-baseline", "middle").attr("text-anchor", "middle"); + return corrplot.append("text").attr("class", "corrlabel").attr("y", corYscale(d.row) + pixel_height / 2).attr("x", -margin.left * 0.1).text(data["var"][data.rows[d.row]]).attr("dominant-baseline", "middle").attr("text-anchor", "end"); + }).on("mouseout", function(d) { + corr_tip.hide(d); + d3.selectAll("text.corrlabel").remove(); + return d3.select(this).attr("stroke", "none"); + }).on("click", function(d) { + return drawScatter(d.col, d.row); + }); + nGroup = d3.max(data.group); + if (!(scatcolors != null) || scatcolors.length < nGroup) { + if (nGroup === 1) { + scatcolors = [d3.rgb(150, 150, 150)]; + } else if (nGroup <= 3) { + scatcolors = ["crimson", "green", "darkslateblue"]; + } else { + if (nGroup <= 10) { + colorScale = d3.scale.category10(); + } else { + colorScale = d3.scale.category20(); + } + scatcolors = (function() { + var _results; + _results = []; + for (i in d3.range(nGroup)) { + _results.push(colorScale(i)); + } + return _results; + })(); + } + } + scat_tip = d3.tip().attr('class', 'd3-tip').html(function(d, i) { + return data.indID[i]; + }).direction('e').offset([0, 10]); + scatterplot.call(scat_tip); + drawScatter = function(i, j) { + var xScale, xticks, yScale, yticks; + d3.selectAll("circle.points").remove(); + d3.selectAll("text.axes").remove(); + d3.selectAll("line.axes").remove(); + console.log("data.dat:", data.dat); + console.log("data.cols:", data.cols); + xScale = d3.scale.linear().domain(d3.extent(data.dat[data.cols[i]])).range([margin.inner, width - margin.inner]); + yScale = d3.scale.linear().domain(d3.extent(data.dat[data.rows[j]])).range([height - margin.inner, margin.inner]); + scatterplot.append("text").attr("id", "xaxis").attr("class", "axes").attr("x", width / 2).attr("y", height + margin.bottom * 0.7).text(data["var"][data.cols[i]]).attr("dominant-baseline", "middle").attr("text-anchor", "middle").attr("fill", "slateblue"); + scatterplot.append("text").attr("id", "yaxis").attr("class", "axes").attr("x", -margin.left * 0.8).attr("y", height / 2).text(data["var"][data.rows[j]]).attr("dominant-baseline", "middle").attr("text-anchor", "middle").attr("transform", "rotate(270," + (-margin.left * 0.8) + "," + (height / 2) + ")").attr("fill", "slateblue"); + xticks = xScale.ticks(5); + yticks = yScale.ticks(5); + scatterplot.selectAll("empty").data(xticks).enter().append("text").attr("class", "axes").text(function(d) { + return formatAxis(xticks)(d); + }).attr("x", function(d) { + return xScale(d); + }).attr("y", height + margin.bottom * 0.3).attr("dominant-baseline", "middle").attr("text-anchor", "middle"); + scatterplot.selectAll("empty").data(yticks).enter().append("text").attr("class", "axes").text(function(d) { + return formatAxis(yticks)(d); + }).attr("x", -margin.left * 0.1).attr("y", function(d) { + return yScale(d); + }).attr("dominant-baseline", "middle").attr("text-anchor", "end"); + scatterplot.selectAll("empty").data(xticks).enter().append("line").attr("class", "axes").attr("x1", function(d) { + return xScale(d); + }).attr("x2", function(d) { + return xScale(d); + }).attr("y1", 0).attr("y2", height).attr("stroke", "white").attr("stroke-width", 1); + scatterplot.selectAll("empty").data(yticks).enter().append("line").attr("class", "axes").attr("y1", function(d) { + return yScale(d); + }).attr("y2", function(d) { + return yScale(d); + }).attr("x1", 0).attr("x2", width).attr("stroke", "white").attr("stroke-width", 1); + return scatterplot.selectAll("empty").data(d3.range(nind)).enter().append("circle").attr("class", "points").attr("cx", function(d) { + return xScale(data.dat[data.cols[i]][d]); + }).attr("cy", function(d) { + return yScale(data.dat[data.rows[j]][d]); + }).attr("r", function(d) { + var x, y; + x = data.dat[data.cols[i]][d]; + y = data.dat[data.rows[j]][d]; + if ((x != null) && (y != null)) { + return 3; + } else { + return null; + } + }).attr("stroke", "black").attr("stroke-width", 1).attr("fill", function(d) { + return scatcolors[data.group[d] - 1]; + }).on("mouseover", scat_tip.show).on("mouseout", scat_tip.hide); + }; + corrplot.append("rect").attr("height", height).attr("width", width).attr("fill", "none").attr("stroke", "black").attr("stroke-width", 1).attr("pointer-events", "none"); + scatterplot.append("rect").attr("height", height).attr("width", width).attr("fill", "none").attr("stroke", "black").attr("stroke-width", 1).attr("pointer-events", "none"); + corrplot.append("text").text(cortitle).attr("id", "corrtitle").attr("x", width / 2).attr("y", -margin.top / 2).attr("dominant-baseline", "middle").attr("text-anchor", "middle"); + scatterplot.append("text").text(scattitle).attr("id", "scattitle").attr("x", width / 2).attr("y", -margin.top / 2).attr("dominant-baseline", "middle").attr("text-anchor", "middle"); + return d3.select("div#caption").style("opacity", 1); + }; + + root.corr_matrix = iplotCorr; + +}).call(this); diff --git a/wqflask/wqflask/static/new/javascript/create_corr_matrix.coffee b/wqflask/wqflask/static/new/javascript/create_corr_matrix.coffee new file mode 100644 index 00000000..88b392d0 --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/create_corr_matrix.coffee @@ -0,0 +1,42 @@ +root = exports ? this + +$ -> + console.log("js_data:", js_data) + + chartOpts = get_options() + data = get_data() + console.log(data) + + mychart = corr_matrix(data, chartOpts) + + +get_options = -> + #h = 450 + #w = 450 + #margin = {left:70, top:40, right:5, bottom: 70, inner:5} + # + chartOpts = + cortitle: "Correlation Matrix" + scattitle: "Scatterplot" + h: 450 + w: 450 + margin: {left:100, top:40, right:5, bottom: 70, inner:5} + + return chartOpts + +get_data = -> + data = {} + data.var = js_data.traits + data.group = js_data.groups + data.indID = js_data.samples + data.dat = js_data.sample_data + data.corr = js_data.corr_results + data.cols = js_data.cols + data.rows = js_data.rows + + + return data + + + + \ No newline at end of file diff --git a/wqflask/wqflask/static/new/javascript/create_corr_matrix.js b/wqflask/wqflask/static/new/javascript/create_corr_matrix.js new file mode 100644 index 00000000..64dc834d --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/create_corr_matrix.js @@ -0,0 +1,47 @@ +// Generated by CoffeeScript 1.6.1 +(function() { + var get_data, get_options, root; + + root = typeof exports !== "undefined" && exports !== null ? exports : this; + + $(function() { + var chartOpts, data, mychart; + console.log("js_data:", js_data); + chartOpts = get_options(); + data = get_data(); + console.log(data); + return mychart = corr_matrix(data, chartOpts); + }); + + get_options = function() { + var chartOpts; + chartOpts = { + cortitle: "Correlation Matrix", + scattitle: "Scatterplot", + h: 450, + w: 450, + margin: { + left: 100, + top: 40, + right: 5, + bottom: 70, + inner: 5 + } + }; + return chartOpts; + }; + + get_data = function() { + var data; + data = {}; + data["var"] = js_data.traits; + data.group = js_data.groups; + data.indID = js_data.samples; + data.dat = js_data.sample_data; + data.corr = js_data.corr_results; + data.cols = js_data.cols; + data.rows = js_data.rows; + return data; + }; + +}).call(this); diff --git a/wqflask/wqflask/static/new/javascript/dataset_menu_structure.json b/wqflask/wqflask/static/new/javascript/dataset_menu_structure.json index 43575a18..fabf3998 100755 --- a/wqflask/wqflask/static/new/javascript/dataset_menu_structure.json +++ b/wqflask/wqflask/static/new/javascript/dataset_menu_structure.json @@ -63,14 +63,14 @@ ] ], "Leaf mRNA": [ - [ - "B1LI0809M5", - "Barley1 Leaf INOC TTKS (Aug09) MAS5" - ], [ "B1LI0809R", "Barley1 Leaf INOC TTKS (Aug09) RMA" ], + [ + "B1LI0809M5", + "Barley1 Leaf INOC TTKS (Aug09) MAS5" + ], [ "B1MI0809M5", "Barley1 Leaf MOCK TTKS (Aug09) MAS5" @@ -113,13 +113,13 @@ "B30_K_1206_M", "Barley1 Leaf MAS 5.0 SCRI (Dec06)" ], - [ - "B30_K_1206_R", - "Barley1 Leaf gcRMA SCRI (Dec06)" - ], [ "B30_K_1206_Rn", "Barley1 Leaf gcRMAn SCRI (Dec06)" + ], + [ + "B30_K_1206_R", + "Barley1 Leaf gcRMA SCRI (Dec06)" ] ], "Phenotypes": [ @@ -211,6 +211,10 @@ }, "AD-cases-controls-Myers": { "Brain mRNA": [ + [ + "GSE15222_F_RI_0409", + "GSE15222 Human Brain All Cases Myers (Apr09) RankInv" + ], [ "GSE15222_F_N_RI_0409", "GSE15222 Human Brain Normal Myers (Apr09) RankInv" @@ -218,10 +222,6 @@ [ "GSE15222_F_A_RI_0409", "GSE15222 Human Brain Alzheimer Myers (Apr09) RankInv" - ], - [ - "GSE15222_F_RI_0409", - "GSE15222 Human Brain Myers (Apr09) RankInv" ] ], "Genotypes": [ @@ -237,6 +237,82 @@ ] ] }, + "Aging-Brain-UCI": { + "Entorhinal Cortex mRNA": [ + [ + "UCI_EC_0913", + "GSE11882 UCI Human Entorhinal Cortex Affy U133 Plus2 (Sep13) RMA" + ] + ], + "Genotypes": [ + [ + "Aging-Brain-UCIGeno", + "Aging-Brain-UCI Genotypes" + ] + ], + "Hippocampus mRNA": [ + [ + "UCI_HC_0913", + "GSE11882 UCI Human Hippocampus Affy U133 Plus2 (Sep13) RMA" + ] + ], + "Phenotypes": [ + [ + "Aging-Brain-UCIPublish", + "Aging-Brain-UCI Published Phenotypes" + ] + ], + "Postcentral Gyrus mRNA": [ + [ + "UCI_PCG_0913", + "GSE11882 UCI Human Postcentral Gyrus Affy U133 Plus2 (Sep13) RMA" + ] + ], + "Superior Frontal Gyrus mRNA": [ + [ + "UCI_SG_0913", + "GSE11882 UCI Human Superior Frontal Gyrus Affy U133 Plus2 (Sep13) RMA" + ] + ] + }, + "Brain-Normal-NIH-Gibbs": { + "Cerebellum mRNA": [ + [ + "GSE15745-GPL6104_Cer0510", + "GSE15745 NIH Human Brain Cerebellum ILM humanRef-8 v2.0 (May10) RankInv" + ] + ], + "Genotypes": [ + [ + "Brain-Normal-NIH-GibbsGeno", + "Brain-Normal-NIH-Gibbs Genotypes" + ] + ], + "Phenotypes": [ + [ + "Brain-Normal-NIH-GibbsPublish", + "Brain-Normal-NIH-Gibbs Published Phenotypes" + ] + ], + "Pons mRNA": [ + [ + "GSE15745-GPL6104_Po0510", + "GSE15745 NIH Human Brain Pons ILM humanRef-8 v2.0 (May10) RankInv" + ] + ], + "Prefrontal Cortex mRNA": [ + [ + "GSE15745-GPL6104_PFC0510", + "GSE15745 NIH Human Brain Prefrontal Cortex ILM humanRef-8 v2.0 (May10) RankInv" + ] + ], + "Temporal Cerebral Wall mRNA": [ + [ + "GSE15745-GPL6104_TC0510", + "GSE15745 NIH Human Brain Temporal Cerebral ILM humanRef-8 v2.0 (May10) RankInv" + ] + ] + }, "CANDLE": { "Genotypes": [ [ @@ -291,6 +367,490 @@ ] ] }, + "GTEx": { + "Adrenal Gland mRNA": [ + [ + "GTEx_log2_Adren_0314", + "GTEx Human Adrenal Gland (Mar14) RPKM Log2" + ], + [ + "GTEx_Adren_0414", + "GTEx Human Adrenal Gland (Apr14) RPKM" + ] + ], + "Amygdala mRNA": [ + [ + "GTEx_log2_AMY_0314", + "GTEx Human Amygdala (Mar14) RPKM Log2" + ], + [ + "GTEx_AMY_0314", + "GTEx Human Amygdala (Mar14) RPKM" + ] + ], + "Anterior Cingulate Cortex mRNA": [ + [ + "GTEx_log2_Anter_0314", + "GTEx Human Anterior Cingulate Cortex (Mar14) RPKM Log2" + ], + [ + "GTEx_Anter_0414", + "GTEx Human Anterior Cingulate Cortex (Apr14) RPKM" + ] + ], + "Aorta mRNA": [ + [ + "GTEx_log2_Aorta_0314", + "GTEx Human Aorta (Mar14) RPKM Log2" + ], + [ + "GTEx_Aorta_0414", + "GTEx Human Aorta (Apr14) RPKM" + ] + ], + "Blood, Cells - EBV-Transformed Lymphocytes mRNA": [ + [ + "GTEx_log2_Blood_0314", + "GTEx Human Blood, Cells - EBV-Transformed Lymphocytes (Mar14) RPKM Log2" + ], + [ + "GTEx_Blood_0414", + "GTEx Human Blood, Cells - EBV-Transformed Lymphocytes (Apr14) RPKM" + ] + ], + "Breast - Mammary Tissue mRNA": [ + [ + "GTEx_log2_Breas_0314", + "GTEx Human Breast - Mammary Tissue (Mar14) RPKM Log2" + ], + [ + "GTEx_Breas_0414", + "GTEx Human Breast - Mammary Tissue (Apr14) RPKM" + ] + ], + "Caudate mRNA": [ + [ + "GTEx_log2_Cauda_0314", + "GTEx Human Caudate (Mar14) RPKM Log2" + ], + [ + "GTEx_Cauda_0414", + "GTEx Human Caudate (Apr14) RPKM" + ] + ], + "Cells - EBV-Transformed Lymphocytes mRNA": [ + [ + "GTEx_log2_CellsEBV_0314", + "GTEx Human Cells - EBV-Transformed Lymphocytes (Mar14) RPKM Log2" + ], + [ + "GTEx_CellsEBV_0414", + "GTEx Human Cells - EBV-Transformed Lymphocytes (Apr14) RPKM" + ] + ], + "Cells - Leukemia Cell Line (CML) mRNA": [ + [ + "GTEx_log2_CellsLe_0314", + "GTEx Human Cells - Leukemia Cell Line (CML) (Mar14) RPKM Log2" + ], + [ + "GTEx_CellsLe_0414", + "GTEx Human Cells - Leukemia Cell Line (CML) (Apr14) RPKM" + ] + ], + "Cells - Transformed Fibroblasts mRNA": [ + [ + "GTEx_log2_CellsTr_0314", + "GTEx Human Cells - Transformed Fibroblasts (Mar14) RPKM Log2" + ], + [ + "GTEx_CellsTr_0414", + "GTEx Human Cells - Transformed Fibroblasts (Apr14) RPKM" + ] + ], + "Cerebellar Cortex mRNA": [ + [ + "GTEx_log2_CerebC_0314", + "GTEx Human Cerebellar Cortex (Mar14) RPKM Log2" + ], + [ + "GTEx_CerebC_0414", + "GTEx Human Cerebellar Cortex (Apr14) RPKM" + ] + ], + "Cerebellar Hemisphere mRNA": [ + [ + "GTEx_log2_CerebH_0314", + "GTEx Human Cerebellar Hemisphere (Mar14) RPKM Log2" + ], + [ + "GTEx_CerebH_0414", + "GTEx Human Cerebellar Hemisphere (Apr14) RPKM" + ] + ], + "Cerebellum mRNA": [ + [ + "GTEx_log2_CER_0314", + "GTEx Human Cerebellum (Mar14) RPKM Log2" + ], + [ + "GTEx_CER_0314", + "GTEx Human Cerebellum (Mar14) RPKM" + ] + ], + "Colon - Transverse mRNA": [ + [ + "GTEx_log2_Colon_0314", + "GTEx Human Colon - Transverse (Mar14) RPKM Log2" + ], + [ + "GTEx_Colon_0414", + "GTEx Human Colon - Transverse (Apr14) RPKM" + ] + ], + "Coronary mRNA": [ + [ + "GTEx_log2_Coron_0314", + "GTEx Human Coronary (Mar14) RPKM Log2" + ], + [ + "GTEx_Coron_0414", + "GTEx Human Coronary (Apr14) RPKM" + ] + ], + "Esophagus - Mucosa mRNA": [ + [ + "GTEx_log2_EsophMuc_0314", + "GTEx Human Esophagus - Mucosa (Mar14) RPKM Log2" + ], + [ + "GTEx_EsophMuc_0414", + "GTEx Human Esophagus - Mucosa (Apr14) RPKM" + ] + ], + "Esophagus - Muscularis mRNA": [ + [ + "GTEx_log2_EsophMus_0314", + "GTEx Human Esophagus - Muscularis (Mar14) RPKM Log2" + ], + [ + "GTEx_EsophMus_0414", + "GTEx Human Esophagus - Muscularis (Apr14) RPKM" + ] + ], + "Fallopian Tube mRNA": [ + [ + "GTEx_log2_Fallo_0314", + "GTEx Human Fallopian Tube (Mar14) RPKM Log2" + ], + [ + "GTEx_Fallo_0414", + "GTEx Human Fallopian Tube (Apr14) RPKM" + ] + ], + "Frontal Cortex mRNA": [ + [ + "GTEx_log2_Front_0314", + "GTEx Human Frontal Cortex (Mar14) RPKM Log2" + ], + [ + "GTEx_Front_0414", + "GTEx Human Frontal Cortex (Apr14) RPKM" + ] + ], + "Genotypes": [ + [ + "GTExGeno", + "GTEx Genotypes" + ] + ], + "Heart - Atrial Appendage mRNA": [ + [ + "GTEx_log2_HeartAt_0314", + "GTEx Human Heart - Atrial Appendage (Mar14) RPKM Log2" + ], + [ + "GTEx_HeartAt_0414", + "GTEx Human Heart - Atrial Appendage (Apr14) RPKM" + ] + ], + "Heart - Left Ventricle mRNA": [ + [ + "GTEx_log2_HeartLV_0314", + "GTEx Human Heart - Left Ventricle (Mar14) RPKM Log2" + ], + [ + "GTEx_HeartLV_0414", + "GTEx Human Heart - Left Ventricle (Apr14) RPKM" + ] + ], + "Hippocampus mRNA": [ + [ + "GTEx_log2_HIP_0314", + "GTEx Human Hippocampus (Mar14) RPKM Log2" + ], + [ + "GTEx_HIP_0314", + "GTEx Human Hippocampus (Mar14) RPKM" + ] + ], + "Hypothalamus mRNA": [ + [ + "GTEx_log2_Hypot_0314", + "GTEx Human Hypothalamus (Mar14) RPKM Log2" + ], + [ + "GTEx_Hypot_0414", + "GTEx Human Hypothalamus (Apr14) RPKM" + ] + ], + "Kidney mRNA": [ + [ + "GTEx_log2_Kidne_0314", + "GTEx Human Kidney (Mar14) RPKM Log2" + ], + [ + "GTEx_Kidne_0414", + "GTEx Human Kidney (Apr14) RPKM" + ] + ], + "Liver mRNA": [ + [ + "GTEx_log2_Liver_0314", + "GTEx Human Liver (Mar14) RPKM Log2" + ], + [ + "GTEx_Liver_0414", + "GTEx Human Liver (Apr14) RPKM" + ] + ], + "Lung mRNA": [ + [ + "GTEx_log2_Lung_0314", + "GTEx Human Lung (Mar14) RPKM Log2" + ], + [ + "GTEx_Lung _0414", + "GTEx Human Lung (Apr14) RPKM" + ] + ], + "Muscle mRNA": [ + [ + "GTEx_log2_Muscle_0314", + "GTEx Human Muscle (Mar14) RPKM Log2" + ], + [ + "GTEx_Muscl_0414", + "GTEx Human Muscle (Apr14) RPKM" + ] + ], + "Nerve - Tibial mRNA": [ + [ + "GTEx_log2_Nerve_0314", + "GTEx Human Nerve - Tibial (Mar14) RPKM Log2" + ], + [ + "GTEx_Nerve_0414", + "GTEx Human Nerve - Tibial (Apr14) RPKM" + ] + ], + "Nucleus Accumbens mRNA": [ + [ + "GTEx_log2_Nucle_0314", + "GTEx Human Nucleus Accumbens (Mar14) RPKM Log2" + ], + [ + "GTEx_Nucle_0414", + "GTEx Human Nucleus Accumbens (Apr14) RPKM" + ] + ], + "Ovary mRNA": [ + [ + "GTEx_log2_Ovary_0314", + "GTEx Human Ovary (Mar14) RPKM Log2" + ], + [ + "GTEx_Ovary_0414", + "GTEx Human Ovary (Apr14) RPKM" + ] + ], + "Pancreas mRNA": [ + [ + "GTEx_log2_Pancr_0314", + "GTEx Human Pancreas (Mar14) RPKM Log2" + ], + [ + "GTEx_Pancr_0414", + "GTEx Human Pancreas (Apr14) RPKM" + ] + ], + "Phenotypes": [ + [ + "GTExPublish", + "GTEx Published Phenotypes" + ] + ], + "Pituitary Gland mRNA": [ + [ + "GTEx_log2_Pitui_0314", + "GTEx Human Pituitary (Mar14) RPKM Log2" + ], + [ + "GTEx_Pitui_0414", + "GTEx Human Pituitary (Apr14) RPKM" + ] + ], + "Prostate mRNA": [ + [ + "GTEx_log2_Prost_0314", + "GTEx Human Prostate (Mar14) RPKM Log2" + ], + [ + "GTEx_Prost_0414", + "GTEx Human Prostate (Apr14) RPKM" + ] + ], + "Putamen mRNA": [ + [ + "GTEx_log2_Putam_0314", + "GTEx Human Putamen (Mar14) RPKM Log2" + ], + [ + "GTEx_Putam_0414", + "GTEx Human Putamen (Apr14) RPKM" + ] + ], + "Skin - Not Sun Exposed (Suprapubic) mRNA": [ + [ + "GTEx_log2_SkinN_0314", + "GTEx Human Skin-Not Sun Exposed (Suprapubic) (Mar14) RPKM Log2" + ], + [ + "GTEx_SkinN_0414", + "GTEx Human Skin-Not Sun Exposed (Suprapubic) (Apr14) RPKM" + ] + ], + "Skin - Sun Exposed (Lower leg) mRNA": [ + [ + "GTEx_log2_SkinE_0314", + "GTEx Human Skin-Sun Exposed (Lower leg) (Mar14) RPKM Log2" + ], + [ + "GTEx_SkinE_0414", + "GTEx Human Skin-Sun Exposed (Lower leg) (Apr14) RPKM" + ] + ], + "Spinal Cord mRNA": [ + [ + "GTEx_log2_Spina_0314", + "GTEx Human Spinal Cord (Mar14) RPKM Log2" + ], + [ + "GTEx_Spina_0414", + "GTEx Human Spinal Cord (Apr14) RPKM" + ] + ], + "Stomach mRNA": [ + [ + "GTEx_log2_Stoma_0314", + "GTEx Human Stomach (Mar14) RPKM Log2" + ], + [ + "GTEx_Stoma_0414", + "GTEx Human Stomach (Apr14) RPKM" + ] + ], + "Subcutaneous mRNA": [ + [ + "GTEx_log2_Subcu_0314", + "GTEx Human Subcutaneous (Mar14) RPKM Log2" + ], + [ + "GTEx_Subcu_0414", + "GTEx Human Subcutaneous (Apr14) RPKM" + ] + ], + "Substantia Nigra mRNA": [ + [ + "GTEx_log2_Subst_0314", + "GTEx Human Substantia Nigra (Mar14) RPKM Log2" + ], + [ + "GTEx_Subst_0414", + "GTEx Human Substantia Nigra (Apr14) RPKM" + ] + ], + "Testis mRNA": [ + [ + "GTEx_log2_Testi_0314", + "GTEx Human Testis (Mar14) RPKM Log2" + ], + [ + "GTEx_Testi_0414", + "GTEx Human Testis (Apr14) RPKM" + ] + ], + "Thyroid mRNA": [ + [ + "GTEx_log2_Thyro_0314", + "GTEx Human Thyroid (Mar14) RPKM Log2" + ], + [ + "GTEx_Thyro_0414", + "GTEx Human Thyroid (Apr14) RPKM" + ] + ], + "Tibial mRNA": [ + [ + "GTEx_log2_Tibial_0314", + "GTEx Human Tibial (Mar14) RPKM Log2" + ], + [ + "GTEx_Tibia_0414", + "GTEx Human Tibial (Apr14) RPKM" + ] + ], + "Uterus mRNA": [ + [ + "GTEx_log2_Uterus_0314", + "GTEx Human Uterus (Mar14) RPKM Log2" + ], + [ + "GTEx_Uteru_0414", + "GTEx Human Uterus (Apr14) RPKM" + ] + ], + "Vagina mRNA": [ + [ + "GTEx_log2_Vagin_0314", + "GTEx Human Vagina (Mar14) RPKM Log2" + ], + [ + "GTEx_Vagin_0414", + "GTEx Human Vagina (Apr14) RPKM" + ] + ], + "Visceral mRNA": [ + [ + "GTEx_log2_Visce_0314", + "GTEx Human Visceral (Mar14) RPKM Log2" + ], + [ + "GTEx_Visce_0414", + "GTEx Human Visceral (Apr14) RPKM" + ] + ], + "Whole Blood mRNA": [ + [ + "GTEx_log2_WholeB_0314", + "GTEx Human Whole Blood (Mar14) RPKM Log2" + ], + [ + "GTEx_Whole_0414", + "GTEx Human Whole Blood (Apr14) RPKM" + ] + ] + }, "HB": { "Cerebellum mRNA": [ [ @@ -354,8 +914,22 @@ "HBTRC-MLC Human Visual Cortex Agilent AD (Jun11) mlratio" ], [ - "HBTRC-MLVC_HD_0611", - "HBTRC-MLC Human Visual Cortex Agilent HD (Jun11) mlratio" + "HBTRC-MLVC_HD_0611", + "HBTRC-MLC Human Visual Cortex Agilent HD (Jun11) mlratio" + ] + ] + }, + "HCP": { + "Genotypes": [ + [ + "HCPGeno", + "HCP Genotypes" + ] + ], + "Phenotypes": [ + [ + "HCPPublish", + "HCP Published Phenotypes" ] ] }, @@ -589,13 +1163,13 @@ "NCI_Agil_Mam_Tum_RMA_0409", "NCI Mammary LMT miRNA v2 (Apr09) RMA" ], - [ - "MA_M_0704_M", - "NCI Mammary mRNA M430 (July04) MAS5" - ], [ "MA_M_0704_R", "NCI Mammary mRNA M430 (July04) RMA" + ], + [ + "MA_M_0704_M", + "NCI Mammary mRNA M430 (July04) MAS5" ] ], "Phenotypes": [ @@ -651,13 +1225,13 @@ ] ], "Liver mRNA": [ - [ - "LVF2_M_0704_M", - "(B6 x BTBR)F2-ob/ob Liver mRNA M430 (Jul04) MAS5" - ], [ "LVF2_M_0704_R", "(B6 x BTBR)F2-ob/ob Liver mRNA M430 (Jul04) RMA" + ], + [ + "LVF2_M_0704_M", + "(B6 x BTBR)F2-ob/ob Liver mRNA M430 (Jul04) MAS5" ] ], "Phenotypes": [ @@ -669,6 +1243,10 @@ }, "B6D2F2": { "Brain mRNA": [ + [ + "BRF2_M_0805_M", + "OHSU/VA B6D2F2 Brain mRNA M430 (Aug05) MAS5" + ], [ "BRF2_M_0805_P", "OHSU/VA B6D2F2 Brain mRNA M430 (Aug05) PDNN" @@ -677,21 +1255,17 @@ "BRF2_M_0805_R", "OHSU/VA B6D2F2 Brain mRNA M430 (Aug05) RMA" ], - [ - "BRF2_M_0805_M", - "OHSU/VA B6D2F2 Brain mRNA M430 (Aug05) MAS5" - ], [ "BRF2_M_0304_P", "OHSU/VA B6D2F2 Brain mRNA M430A (Mar04) PDNN" ], - [ - "BRF2_M_0304_M", - "OHSU/VA B6D2F2 Brain mRNA M430A (Mar04) MAS5" - ], [ "BRF2_M_0304_R", "OHSU/VA B6D2F2 Brain mRNA M430A (Mar04) RMA" + ], + [ + "BRF2_M_0304_M", + "OHSU/VA B6D2F2 Brain mRNA M430A (Mar04) MAS5" ] ], "Genotypes": [ @@ -793,6 +1367,10 @@ ] ], "Striatum mRNA": [ + [ + "SA_M2_0905_R", + "OHSU/VA B6D2F2 Striatum M430v2 (Sep05) RMA" + ], [ "SA_M2_0905_M", "OHSU/VA B6D2F2 Striatum M430v2 (Sep05) MAS5" @@ -800,37 +1378,33 @@ [ "SA_M2_0905_P", "OHSU/VA B6D2F2 Striatum M430v2 (Sep05) PDNN" - ], - [ - "SA_M2_0905_R", - "OHSU/VA B6D2F2 Striatum M430v2 (Sep05) RMA" ] ] }, "BHF2": { "Adipose mRNA": [ - [ - "UCLA_BHF2_ADIPOSE_FEMALE", - "UCLA BHF2 Adipose Female mlratio" - ], [ "UCLA_BHF2_ADIPOSE_MALE", "UCLA BHF2 Adipose Male mlratio" ], + [ + "UCLA_BHF2_ADIPOSE_FEMALE", + "UCLA BHF2 Adipose Female mlratio" + ], [ "UCLA_BHF2_ADIPOSE_0605", "UCLA BHF2 Adipose (June05) mlratio" ] ], "Brain mRNA": [ - [ - "UCLA_BHF2_BRAIN_FEMALE", - "UCLA BHF2 Brain Female mlratio" - ], [ "UCLA_BHF2_BRAIN_MALE", "UCLA BHF2 Brain Male mlratio" ], + [ + "UCLA_BHF2_BRAIN_FEMALE", + "UCLA BHF2 Brain Female mlratio" + ], [ "UCLA_BHF2_BRAIN_0605", "UCLA BHF2 Brain (June05) mlratio" @@ -843,28 +1417,28 @@ ] ], "Liver mRNA": [ - [ - "UCLA_BHF2_LIVER_FEMALE", - "UCLA BHF2 Liver Female mlratio" - ], [ "UCLA_BHF2_LIVER_MALE", "UCLA BHF2 Liver Male mlratio" ], + [ + "UCLA_BHF2_LIVER_FEMALE", + "UCLA BHF2 Liver Female mlratio" + ], [ "UCLA_BHF2_LIVER_0605", "UCLA BHF2 Liver (June05) mlratio" ] ], "Muscle mRNA": [ - [ - "UCLA_BHF2_MUSCLE_FEMALE", - "UCLA BHF2 Muscle Female mlratio **" - ], [ "UCLA_BHF2_MUSCLE_MALE", "UCLA BHF2 Muscle Male mlratio **" ], + [ + "UCLA_BHF2_MUSCLE_FEMALE", + "UCLA BHF2 Muscle Female mlratio **" + ], [ "UCLA_BHF2_MUSCLE_0605", "UCLA BHF2 Muscle (June05) mlratio **" @@ -948,6 +1522,16 @@ ] }, "BXD": { + "Adipose mRNA": [ + [ + "EPFLADGL1013", + "EPFL/LISP BXD CD Brown Adipose Affy Mouse Gene 2.0 ST Gene Level (Oct13) RMA" + ], + [ + "EPFLADEL1013", + "EPFL/LISP BXD CD Brown Adipose Affy Mouse Gene 2.0 ST Exon Level (Oct13) RMA" + ] + ], "Adrenal Gland mRNA": [ [ "INIA_Adrenal_RMA_0612", @@ -996,16 +1580,40 @@ [ "UCLA_BXD-on_Femur_0113_RSN", "UCLA GSE27483 BXD Only Bone Femur ILM Mouse WG-6 v2.0 (Jan13) RSN" + ], + [ + "UTHSCWGU88BFMG1013", + "UTHSC WGU88 Male Bone Femur AFFY Mouse Gene ST 2.0 Gene Level (Oct13) RMA **" + ], + [ + "UTHSCWGU88BFMEx1013", + "UTHSC WGU88 Male Bone Femur AFFY Mouse Gene ST 2.0 Exon Level (Oct13) RMA **" + ], + [ + "UTHSCWGU88BFFG1013", + "UTHSC WGU88 Female Bone Femur AFFY Mouse Gene ST 2.0 Gene Level (Oct13) RMA **" + ], + [ + "UTHSCWGU88BFFEx1013", + "UTHSC WGU88 Female Bone Femur AFFY Mouse Gene ST 2.0 Exon Level (Oct13) RMA **" ] ], "Brain mRNA": [ [ - "UTHSC_BXD_WB_RNASeqEx1112", - "UTHSC Mouse BXD Whole Brain RNA Sequence Exon Level (Nov12) RPKM" + "UTHSC_BXD_WB_RNASeqtrim1112", + "UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Trimmed 2.0" ], [ "UTHSC_BXD_WB_RNASeq1112", - "UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM" + "UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Untrimmed" + ], + [ + "UTHSC_BXD_WB_RNASeqtrim1_1112", + "UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Trimmed 1.0" + ], + [ + "UTHSC_BXD_WB_RNASeqEx1112", + "UTHSC Mouse BXD Whole Brain RNA Sequence Exon Level (Nov12) RPKM" ], [ "BR_M2_1106_R", @@ -1015,10 +1623,6 @@ "BR_U_1105_P", "UTHSC Brain mRNA U74Av2 (Nov05) PDNN" ], - [ - "BR_U_0805_P", - "UTHSC Brain mRNA U74Av2 (Aug05) PDNN" - ], [ "BR_U_0805_M", "UTHSC Brain mRNA U74Av2 (Aug05) MAS5" @@ -1027,6 +1631,10 @@ "BR_U_0805_R", "UTHSC Brain mRNA U74Av2 (Aug05) RMA" ], + [ + "BR_U_0805_P", + "UTHSC Brain mRNA U74Av2 (Aug05) PDNN" + ], [ "CB_M_0204_P", "INIA Brain mRNA M430 (Feb04) PDNN" @@ -1137,6 +1745,10 @@ "Eye_M2_0908_R_ND", "Eye M430v2 WT Gpnmb (Sep08) RMA **" ], + [ + "Eye_M2_0908_R_MT", + "Eye M430v2 Mutant Tyrp1 (Sep08) RMA **" + ], [ "Eye_M2_0908_WTWT", "Eye M430v2 WT WT (Sep08) RMA **" @@ -1147,15 +1759,17 @@ ], [ "DBA2J-ONH-1212", - "ONH BXD Glaucoma Affy M430 2.0 Trial (Dec12) RMA **" - ], - [ - "Eye_M2_0908_R_MT", - "Eye M430v2 Mutant Tyrp1 (Sep08) RMA **" + "Howell et al. 2011, DBA/2J Glaucoma Optic Nerve Head M430 2.0 (Dec12) RMA" ], [ "BXD_GLA_0911", - "BXD Glaucoma Affy M430 2.0 Trial (Sep11) RMA **" + "Howell et al. 2011, DBA/2J Glaucoma Retina M430 2.0 (Sep11) RMA" + ] + ], + "Gastrointestinal mRNA": [ + [ + "UTHSC_GutGL_0414", + "UTHSC Mouse BXD Gastrointestinal Affy MoGene 1.0 ST Gene Level (Apr14) RMA **" ] ], "Genotypes": [ @@ -1164,6 +1778,24 @@ "BXD Genotypes" ] ], + "Heart mRNA": [ + [ + "EPFL-LISPBXDHeCD0114", + "EPFL/LISP BXD CD Heart Affy Mouse Gene 2.0 ST Gene Level (Jan14) RMA **" + ], + [ + "EPFL-LISPBXDHeHFD0114", + "EPFL/LISP BXD HFD Heart Affy Mouse Gene 2.0 ST Gene Level (Jan14) RMA **" + ], + [ + "EPFL-LISPBXDHeCDEx0114", + "EPFL/LISP BXD CD Heart Affy Mouse Gene 2.0 ST Exon Level (Jan14) RMA **" + ], + [ + "EPFL-LISPBXDHeHFDEx0114", + "EPFL/LISP BXD HFD Heart Affy Mouse Gene 2.0 ST Exon Level (Jan14) RMA **" + ] + ], "Hematopoietic Cells mRNA": [ [ "UMCG_0907_HemaStem_ori", @@ -1217,7 +1849,7 @@ ], [ "UT_ILM_BXD_hipp_5T_1112", - "UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv" + "UTHSC Hippocampus Illumina v6.1 All Combined (Nov12) RankInv" ], [ "UT_ILM_BXD_hipp_NON_1112", @@ -1272,6 +1904,12 @@ "UTHSC BXD Aged Hippocampus Affy Mouse Gene 1.0 ST (Sep12) RMA Exon Level **" ] ], + "Hippocampus microRNA": [ + [ + "UTHSC_BXD_Hip_miRNASeq0214", + "UTHSC BXD Hippocampus Ion Torrent microRNA (Feb14) RPKM **" + ] + ], "Hypothalamus mRNA": [ [ "INIA_Hyp_RMA_1110", @@ -1285,6 +1923,22 @@ "INIA_Hyp_F_RMA_1110", "INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) Female" ], + [ + "INIA_Hyp_PCA_0813_v4", + "INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) PCA Test v080913" + ], + [ + "INIA_Hyp_PCA_0813_v3", + "INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) PCA Test v080813" + ], + [ + "INIA_Hyp_PCA_0813_v2", + "INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) PCA Test v080513" + ], + [ + "INIA_Hyp_PCA_0813", + "INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) PCA Test v080213" + ], [ "INIA_Hyp_RMA_Ex-1110", "INIA Hypothalamus Exon Affy MoGene 1.0 ST (Nov10)" @@ -1307,13 +1961,13 @@ "MA_M2_0806_P", "Mouse Kidney M430v2 Sex Balanced (Aug06) PDNN" ], - [ - "MA_M2_0706_R", - "Mouse Kidney M430v2 (Jul06) RMA" - ], [ "MA_M2_0706_P", "Mouse Kidney M430v2 (Jul06) PDNN" + ], + [ + "MA_M2_0706_R", + "Mouse Kidney M430v2 (Jul06) RMA" ] ], "Leucocytes mRNA": [ @@ -1322,30 +1976,32 @@ "UWA Illumina PBL (Nov08) RSN **" ] ], - "Liver Proteome": [ + "Liver Metabolome": [ [ - "EPFLBXDprotRPN0513", - "EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (May13) RPN **" + "EPFL-LISP_LivPMetHFD1213", + "EPFL/LISP BXD Liver Polar Metabolites HFD (Jun14) **" ], [ - "EPFLBXDprotHFDRPN0513", - "EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins HFD (May13) RPN **" - ], + "EPFL-LISP_LivPMetCD1213", + "EPFL/LISP BXD Liver Polar Metabolites CD (Jun14) **" + ] + ], + "Liver Proteome": [ [ - "EPFLBXDprotCDRPN0513", - "EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD (May13) RPN **" + "EPFLETHZBXDprotHFD0514", + "EPFL/ETHZ BXD Liver, Soluble Proteins HFD (May14) SWATH **" ], [ - "EPFLBXDprot0513", - "EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (May13) **" + "EPFLETHZBXDprotCD0514", + "EPFL/ETHZ BXD Liver, Soluble Proteins CD (May14) SWATH **" ], [ - "EPFLBXDprotHFD0513", - "EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins HFD (May13) **" + "EPFLBXDprotHFDRPN0214", + "EPFL/LISP BXD Liver, Soluble Proteins HFD (Feb14) SRM **" ], [ - "EPFLBXDprotCD0513", - "EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD (May13) **" + "EPFLBXDprotCDRPN0214", + "EPFL/LISP BXD Liver, Soluble Proteins CD (Feb14) SRM **" ] ], "Liver mRNA": [ @@ -1353,17 +2009,21 @@ "GSE16780_UCLA_ML0911", "GSE16780 UCLA Hybrid MDP Liver Affy HT M430A (Sep11) RMA" ], + [ + "SUH_Liv_RMA_0611", + "SUH BXD Liver CCl4-treated Affy Mouse Gene 1.0 ST (Jun11) RMA" + ], [ "EPFLMouseLiverRMA0413", - "EPFL/LISP BXD CD+HFD Liver Affy Mouse Gene 1.0 ST (Apr13) RMA **" + "EPFL/LISP BXD CD+HFD Liver Affy Mouse Gene 1.0 ST (Apr13) RMA" ], [ "EPFLMouseLiverHFDRMA0413", - "EPFL/LISP BXD HFD Liver Affy Mouse Gene 1.0 ST (Apr13) RMA **" + "EPFL/LISP BXD HFD Liver Affy Mouse Gene 1.0 ST (Apr13) RMA" ], [ "EPFLMouseLiverCDRMA0413", - "EPFL/LISP BXD CD Liver Affy Mouse Gene 1.0 ST (Apr13) RMA **" + "EPFL/LISP BXD CD Liver Affy Mouse Gene 1.0 ST (Apr13) RMA" ], [ "EPFLMouseLiverBothExRMA0413", @@ -1404,10 +2064,6 @@ [ "GenEx_BXD_liverSal_RMA_F_0211", "GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females **" - ], - [ - "SUH_Liv_RMA_0611", - "SUH BXD Liver Affy Mouse Gene 1.0 ST (Jun11) RMA **" ] ], "Lung mRNA": [ @@ -1420,55 +2076,69 @@ "HZI Lung M430v2 (Apr08) MAS5" ], [ - "HZI_LTCF_0313", - "HZI Lung Time Course Flu PR8M (Mar13) Schughart **" + "HZI_PR8M-F_1113", + "HZI PR8M-Infected Lungs Females RNAseq (Nov13) RPKM **" ], [ "HZI_PR8M_Q_0612", "HZI PR8M-Infected Lungs Agilent4x44 (Apr12) Quantile Females **" + ], + [ + "HZI_LTCF_0313", + "HZI Lung Time Course Flu PR8M (Mar13) Schughart **" ] ], "Midbrain mRNA": [ [ "VUBXDMouseMidBrainQ0512", - "VU BXD Midbrain Agilent SurePrint G3 Mouse GE (May12) Quantile **" + "VU BXD Midbrain Agilent SurePrint G3 Mouse GE (May12) Quantile" + ] + ], + "Muscle Metabolome": [ + [ + "EPFL-LISP_MusPMetHFD1213", + "EPFL/LISP BXD Muscle Polar Metabolites HFD (Jun14) **" + ], + [ + "EPFL-LISP_MusPMetCD1213", + "EPFL/LISP BXD Muscle Polar Metabolites CD (Jun14) **" ] ], "Muscle mRNA": [ [ "EPFLMouseMuscleRMA_Ex1112", - "EPFL/LISP BXD CD+HFD Muscle Affy Mouse Gene 1.0 ST (Nov12) RMA Exon Level **" + "EPFL/LISP BXD CD+HFD Muscle Affy Mouse Gene 1.0 ST (Nov12) RMA Exon Level" ], [ "EPFLMouseMuscleHFDRMAEx1112", - "EPFL/LISP BXD HFD Muscle Affy Mouse Gene 1.0 ST (Nov12) RMA Exon Level **" + "EPFL/LISP BXD HFD Muscle Affy Mouse Gene 1.0 ST (Nov12) RMA Exon Level" ], [ "EPFLMouseMuscleCDRMAEx1112", - "EPFL/LISP BXD CD Muscle Affy Mouse Gene 1.0 ST (Nov12) RMA Exon Level **" + "EPFL/LISP BXD CD Muscle Affy Mouse Gene 1.0 ST (Nov12) RMA Exon Level" ], [ "EPFLMouseMuscleRMA1211", - "EPFL/LISP BXD CD+HFD Muscle Affy Mouse Gene 1.0 ST (Dec11) RMA **" + "EPFL/LISP BXD CD+HFD Muscle Affy Mouse Gene 1.0 ST (Dec11) RMA" ], [ "EPFLMouseMuscleHFDRMA1211", - "EPFL/LISP BXD HFD Muscle Affy Mouse Gene 1.0 ST (Dec11) RMA **" + "EPFL/LISP BXD HFD Muscle Affy Mouse Gene 1.0 ST (Dec11) RMA" ], [ "EPFLMouseMuscleCDRMA1211", - "EPFL/LISP BXD CD Muscle Affy Mouse Gene 1.0 ST (Dec11) RMA **" + "EPFL/LISP BXD CD Muscle Affy Mouse Gene 1.0 ST (Dec11) RMA" ] ], "Neocortex mRNA": [ - [ - "DevNeocortex_ILM6.2P3RInv_1111", - "BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov11) RankInv" - ], [ "DevNeocortex_ILM6.2P14RInv_1111", "BIDMC/UTHSC Dev Neocortex P14 ILMv6.2 (Nov11) RankInv" ], + [ + "DevNeocortex_ILM6.2P3RInv_1111", + "BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov11) RankInv" + ], [ "HQFNeoc_1210v2_RankInv", "HQF BXD Neocortex ILM6v1.1 (Dec10v2) RankInv" @@ -1481,39 +2151,39 @@ "HQFNeoc_0208_RankInv", "HQF BXD Neocortex ILM6v1.1 (Feb08) RankInv" ], - [ - "DevNeocortex_ILM6.2P14RInv_1110", - "BIDMC/UTHSC Dev Neocortex P14 ILMv6.2 (Nov10) RankInv" - ], [ "DevNeocortex_ILM6.2P3RInv_1110", "BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv" + ], + [ + "DevNeocortex_ILM6.2P14RInv_1110", + "BIDMC/UTHSC Dev Neocortex P14 ILMv6.2 (Nov10) RankInv" ] ], "Nucleus Accumbens mRNA": [ [ "VCUSalo_1007_R", - "VCU BXD NA Sal M430 2.0 (Oct07) RMA" + "VCU BXD NAc Sal M430 2.0 (Oct07) RMA" ], [ - "VCU_NAc_AvE_0113_Ss", - "VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13) Sscore **" + "VCUEtOH_1007_R", + "VCU BXD NAc EtOH M430 2.0 (Oct07) RMA **" ], [ - "VCU_NAc_Et_0113_R", - "VCU BXD NAc CIE EtOH M430 2.0 (Jan13) RMA **" + "VCUSal_1007_R", + "VCU BXD NAc EtOH vs Sal M430 2.0 (Oct07) Sscore **" ], [ "VCU_NAc_Air_0113_R", "VCU BXD NAc CIE Air M430 2.0 (Jan13) RMA **" ], [ - "VCUEtOH_1007_R", - "VCU BXD NA EtOH M430 2.0 (Oct07) RMA **" + "VCU_NAc_Et_0113_R", + "VCU BXD NAc CIE EtOH M430 2.0 (Jan13) RMA **" ], [ - "VCUSal_1007_R", - "VCU BXD NA Et vs Sal M430 2.0 (Oct07) Sscore **" + "VCU_NAc_AvE_0113_Ss", + "VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13) Sscore **" ] ], "Phenotypes": [ @@ -1585,25 +2255,41 @@ "ONCRetILM6_0412", "ONC HEI Retina (April 2012) RankInv" ], + [ + "DoDTATRCRetMoGene2_1313", + "DoD TATRC Retina Affy MoGene 2.0 ST (Dec13) RMA" + ], + [ + "DoDTATRCRetExMoGene2_1313", + "DoD TATRC Retina Affy MoGene 2.0 ST (Dec13) RMA Exon Level" + ], [ "ONCRetMoGene2_0413", - "DoD TATRC Retina Affy MoGene 2.0 ST (Apr13) RMA **" + "DoD TATRC Retina Affy MoGene 2.0 ST (Oct13) RMA **" ], [ "ONCRetExMoGene2_0413", - "DoD TATRC Retina Affy MoGene 2.0 ST (Apr13) RMA Exon Level **" + "DoD TATRC Retina Affy MoGene 2.0 ST (Oct13) RMA Exon Level **" ], [ - "B6D2ONCILM_0412", - "B6D2 ONC Retina (April 2012) RankInv **" + "DoDTATRCRetBLMoGene2_1213", + "DoD TATRC Retina Blast Affy MoGene 2.0 ST (Dec13) RMA **" ], [ - "G2HEIONCRetILM6_0911", - "G2 HEI ONC Retina Illumina V6.2 (Sep11) RankInv **" + "DoDTATRCRetBLExMoGene2_1213", + "DoD TATRC Retina Blast Affy MoGene 2.0 ST (Dec13) RMA Exon Level **" + ], + [ + "B6D2ONCILM_0412", + "B6D2 ONC Retina (April 2012) RankInv **" ], [ "HEIONCvsCRetILM6_0911", "HEI ONC vs Control Retina Illumina V6.2 (Sep11) RankInv **" + ], + [ + "G2HEIONCRetILM6_0911", + "G2 HEI ONC Retina Illumina V6.2 (Sep11) RankInv **" ] ], "Spleen mRNA": [ @@ -1689,13 +2375,13 @@ "DevStriatum_ILM6.2P14RInv_1111", "BIDMC/UTHSC Dev Striatum P14 ILMv6.2 (Nov11) RankInv **" ], - [ - "DevStriatum_ILM6.2P3RInv_1110", - "BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv **" - ], [ "DevStriatum_ILM6.2P14RInv_1110", "BIDMC/UTHSC Dev Striatum P14 ILMv6.2 (Nov10) RankInv **" + ], + [ + "DevStriatum_ILM6.2P3RInv_1110", + "BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv **" ] ], "T Cell (helper) mRNA": [ @@ -1717,6 +2403,10 @@ ] ], "Ventral Tegmental Area mRNA": [ + [ + "VCUEtOH_0609_R", + "VCU BXD VTA EtOH M430 2.0 (Jun09) RMA **" + ], [ "VCUSal_0609_R", "VCU BXD VTA Sal M430 2.0 (Jun09) RMA **" @@ -1724,10 +2414,6 @@ [ "VCUEtvsSal_0609_R", "VCU BXD VTA Et vs Sal M430 2.0 (Jun09) Sscore **" - ], - [ - "VCUEtOH_0609_R", - "VCU BXD VTA EtOH M430 2.0 (Jun09) RMA **" ] ] }, @@ -1806,12 +2492,12 @@ "UCLA CTB6/B6CTF2 Brain (2005) mlratio" ], [ - "UCLA_CTB6B6CTF2_BRAIN_FEMALE", - "UCLA CTB6B6CTF2 Brain Female mlratio **" + "UCLA_CTB6B6CTF2_BRAIN_MALE", + "UCLA CTB6/B6CTF2 Brain Males (2005) mlratio" ], [ - "UCLA_CTB6B6CTF2_BRAIN_MALE", - "UCLA CTB6B6CTF2 Brain Male mlratio **" + "UCLA_CTB6B6CTF2_BRAIN_FEMALE", + "UCLA CTB6/B6CTF2 Brain Females (2005) mlratio" ] ], "Genotypes": [ @@ -1863,13 +2549,13 @@ ] ], "Hippocampus mRNA": [ - [ - "HC_M2CB_1205_P", - "Hippocampus Consortium M430v2 CXB (Dec05) PDNN" - ], [ "HC_M2CB_1205_R", "Hippocampus Consortium M430v2 CXB (Dec05) RMA" + ], + [ + "HC_M2CB_1205_P", + "Hippocampus Consortium M430v2 CXB (Dec05) PDNN" ] ], "Phenotypes": [ @@ -1973,6 +2659,14 @@ "Hipp_Illumina_RankInv_0507", "Hippocampus Illumina (May07) RankInv" ], + [ + "Illum_LXS_Hipp_NON_1008", + "Hippocampus Illumina NON (Oct08) RankInv beta" + ], + [ + "Illum_LXS_Hipp_RSE_1008", + "Hippocampus Illumina RSE (Oct08) RankInv beta" + ], [ "Illum_LXS_Hipp_NOE_1008", "Hippocampus Illumina NOE (Oct08) RankInv beta" @@ -1984,14 +2678,6 @@ [ "Illum_LXS_Hipp_NOS_1008", "Hippocampus Illumina NOS (Oct08) RankInv beta" - ], - [ - "Illum_LXS_Hipp_NON_1008", - "Hippocampus Illumina NON (Oct08) RankInv beta" - ], - [ - "Illum_LXS_Hipp_RSE_1008", - "Hippocampus Illumina RSE (Oct08) RankInv beta" ] ], "Phenotypes": [ @@ -2001,6 +2687,10 @@ ] ], "Prefrontal Cortex mRNA": [ + [ + "VCUEtOH_0806_R", + "VCU LXS PFC EtOH M430A 2.0 (Aug06) RMA **" + ], [ "VCUSal_0806_R", "VCU LXS PFC Sal M430A 2.0 (Aug06) RMA" @@ -2008,10 +2698,20 @@ [ "VCUEt_vs_Sal_0806_R", "VCU LXS PFC Et vs Sal M430A 2.0 (Aug06) Sscore **" - ], + ] + ] + }, + "Linsenbardt-Boehm": { + "Genotypes": [ [ - "VCUEtOH_0806_R", - "VCU LXS PFC EtOH M430A 2.0 (Aug06) RMA **" + "Linsenbardt-BoehmGeno", + "Linsenbardt-Boehm Genotypes" + ] + ], + "Phenotypes": [ + [ + "Linsenbardt-BoehmPublish", + "Linsenbardt-Boehm Published Phenotypes" ] ] }, @@ -2025,7 +2725,7 @@ "Dorsal Root Ganglia mRNA": [ [ "TSRI-DRG-AffyMOE430_0113-MDP", - "TSRI DRG Affy Mouse Genome 430 2.0 (Jan13) RMA MDP **" + "TSRI DRG Affy Mouse Genome 430 2.0 (Jan13) RMA MDP" ] ], "Genotypes": [ @@ -2035,13 +2735,13 @@ ] ], "Hippocampus mRNA": [ - [ - "HC_M2_0606_MDP", - "Hippocampus Consortium M430v2 (Jun06) RMA MDP" - ], [ "UMUTAffyExon_0209_RMA_MDP", "UMUTAffy Hippocampus Exon (Feb09) RMA MDP" + ], + [ + "HC_M2_0606_MDP", + "Hippocampus Consortium M430v2 (Jun06) RMA MDP" ] ], "Liver mRNA": [ @@ -2231,6 +2931,20 @@ } }, "soybean": { + "J12XJ58F11": { + "Genotypes": [ + [ + "J12XJ58F11Geno", + "J12XJ58F11 Genotypes" + ] + ], + "Phenotypes": [ + [ + "J12XJ58F11Publish", + "J12XJ58F11 Published Phenotypes" + ] + ] + }, "J12XJ58F2": { "Genotypes": [ [ @@ -2307,35 +3021,51 @@ "human": [ [ "AD-cases-controls", - "Alzheimer's Disease Brain (Liang)" + "Brain, Aging: AD, Normal Gene Expression (Liang)" ], [ "AD-cases-controls-Myers", - "Alzheimer's Disease Brain (Myers)" + "Brain, Aging: AD, Normal Gene Expression with Genotypes (Myers)" + ], + [ + "Aging-Brain-UCI", + "Brain, Aging: Normal Gene Expression (UCI/Cotman)" + ], + [ + "Brain-Normal-NIH-Gibbs", + "Brain: Normal Gene Expression (NIH/Gibbs)" ], [ "CANDLE", - "CANDLE Cognitive Development (TUCI)" + "Child Development: CANDLE Cohort with Genotypes (TUCI/UTHSC)" ], [ "CEPH-2004", - "CEPH Families Cell Lines" + "Lymphoblastoid Cells: Gene Expression (CEPH, Williams)" + ], + [ + "GTEx", + "All Tissues, RNA-Seq GTEx v3" ], [ "HB", - "Harvard Brain Tissue Resource Center" + "Brain, Aging: AD, HD, Normal Gene Expression (Harvard/Merck)" + ], + [ + "HCP", + "Brain, Cognition, Human Connectome Project" ], [ "HLC", - "Human Liver Cohort (Merck)" + "Liver: Normal Gene Expression with Genotypes (Merck)" ], [ "HLT", - "Human Lung Transcriptome (Rosetta/Merck)" + "Lung: Normal Gene Expression (Merck)" ], [ "HSB", - "Human Brain Transcriptome (Yale/Kavli)" + "Brain, Development: Normal Gene Expression (Yale/Sestan)" ] ], "macaque monkey": [ @@ -2395,7 +3125,7 @@ ], [ "C57BL-6JxC57BL-6NJF2", - "C57BL/6JxC57BL/6NJ F2 Cross" + "Reduced Complexity Cross (B6JxB6N F2)" ], [ "CTB6F2", @@ -2413,6 +3143,10 @@ "HS-CC", "Heterogeneous Stock Collaborative Cross" ], + [ + "Linsenbardt-Boehm", + "B6D2 EtOH Selected Advanced Intercross" + ], [ "LXS", "LXS" @@ -2449,6 +3183,10 @@ ] ], "soybean": [ + [ + "J12XJ58F11", + "J12XJ58F11" + ], [ "J12XJ58F2", "J12XJ58F2" @@ -2637,6 +3375,58 @@ "Brain mRNA" ] ], + "Aging-Brain-UCI": [ + [ + "Phenotypes", + "Phenotypes" + ], + [ + "Genotypes", + "Genotypes" + ], + [ + "Entorhinal Cortex mRNA", + "Entorhinal Cortex mRNA" + ], + [ + "Hippocampus mRNA", + "Hippocampus mRNA" + ], + [ + "Postcentral Gyrus mRNA", + "Postcentral Gyrus mRNA" + ], + [ + "Superior Frontal Gyrus mRNA", + "Superior Frontal Gyrus mRNA" + ] + ], + "Brain-Normal-NIH-Gibbs": [ + [ + "Phenotypes", + "Phenotypes" + ], + [ + "Genotypes", + "Genotypes" + ], + [ + "Cerebellum mRNA", + "Cerebellum mRNA" + ], + [ + "Pons mRNA", + "Pons mRNA" + ], + [ + "Prefrontal Cortex mRNA", + "Prefrontal Cortex mRNA" + ], + [ + "Temporal Cerebral Wall mRNA", + "Temporal Cerebral Wall mRNA" + ] + ], "CANDLE": [ [ "Phenotypes", @@ -2669,6 +3459,204 @@ "Lymphoblast B-cell mRNA" ] ], + "GTEx": [ + [ + "Phenotypes", + "Phenotypes" + ], + [ + "Genotypes", + "Genotypes" + ], + [ + "Adrenal Gland mRNA", + "Adrenal Gland mRNA" + ], + [ + "Amygdala mRNA", + "Amygdala mRNA" + ], + [ + "Anterior Cingulate Cortex mRNA", + "Anterior Cingulate Cortex mRNA" + ], + [ + "Aorta mRNA", + "Aorta mRNA" + ], + [ + "Blood, Cells - EBV-Transformed Lymphocytes mRNA", + "Blood, Cells - EBV-Transformed Lymphocytes mRNA" + ], + [ + "Breast - Mammary Tissue mRNA", + "Breast - Mammary Tissue mRNA" + ], + [ + "Caudate mRNA", + "Caudate mRNA" + ], + [ + "Cells - EBV-Transformed Lymphocytes mRNA", + "Cells - EBV-Transformed Lymphocytes mRNA" + ], + [ + "Cells - Leukemia Cell Line (CML) mRNA", + "Cells - Leukemia Cell Line (CML) mRNA" + ], + [ + "Cells - Transformed Fibroblasts mRNA", + "Cells - Transformed Fibroblasts mRNA" + ], + [ + "Cerebellar Cortex mRNA", + "Cerebellar Cortex mRNA" + ], + [ + "Cerebellar Hemisphere mRNA", + "Cerebellar Hemisphere mRNA" + ], + [ + "Cerebellum mRNA", + "Cerebellum mRNA" + ], + [ + "Colon - Transverse mRNA", + "Colon - Transverse mRNA" + ], + [ + "Coronary mRNA", + "Coronary mRNA" + ], + [ + "Esophagus - Mucosa mRNA", + "Esophagus - Mucosa mRNA" + ], + [ + "Esophagus - Muscularis mRNA", + "Esophagus - Muscularis mRNA" + ], + [ + "Fallopian Tube mRNA", + "Fallopian Tube mRNA" + ], + [ + "Frontal Cortex mRNA", + "Frontal Cortex mRNA" + ], + [ + "Heart - Atrial Appendage mRNA", + "Heart - Atrial Appendage mRNA" + ], + [ + "Heart - Left Ventricle mRNA", + "Heart - Left Ventricle mRNA" + ], + [ + "Hippocampus mRNA", + "Hippocampus mRNA" + ], + [ + "Hypothalamus mRNA", + "Hypothalamus mRNA" + ], + [ + "Kidney mRNA", + "Kidney mRNA" + ], + [ + "Liver mRNA", + "Liver mRNA" + ], + [ + "Lung mRNA", + "Lung mRNA" + ], + [ + "Muscle mRNA", + "Muscle mRNA" + ], + [ + "Nerve - Tibial mRNA", + "Nerve - Tibial mRNA" + ], + [ + "Nucleus Accumbens mRNA", + "Nucleus Accumbens mRNA" + ], + [ + "Ovary mRNA", + "Ovary mRNA" + ], + [ + "Pancreas mRNA", + "Pancreas mRNA" + ], + [ + "Pituitary Gland mRNA", + "Pituitary Gland mRNA" + ], + [ + "Prostate mRNA", + "Prostate mRNA" + ], + [ + "Putamen mRNA", + "Putamen mRNA" + ], + [ + "Skin - Not Sun Exposed (Suprapubic) mRNA", + "Skin - Not Sun Exposed (Suprapubic) mRNA" + ], + [ + "Skin - Sun Exposed (Lower leg) mRNA", + "Skin - Sun Exposed (Lower leg) mRNA" + ], + [ + "Spinal Cord mRNA", + "Spinal Cord mRNA" + ], + [ + "Stomach mRNA", + "Stomach mRNA" + ], + [ + "Subcutaneous mRNA", + "Subcutaneous mRNA" + ], + [ + "Substantia Nigra mRNA", + "Substantia Nigra mRNA" + ], + [ + "Testis mRNA", + "Testis mRNA" + ], + [ + "Thyroid mRNA", + "Thyroid mRNA" + ], + [ + "Tibial mRNA", + "Tibial mRNA" + ], + [ + "Uterus mRNA", + "Uterus mRNA" + ], + [ + "Vagina mRNA", + "Vagina mRNA" + ], + [ + "Visceral mRNA", + "Visceral mRNA" + ], + [ + "Whole Blood mRNA", + "Whole Blood mRNA" + ] + ], "HB": [ [ "Phenotypes", @@ -2691,6 +3679,16 @@ "Primary Visual Cortex mRNA" ] ], + "HCP": [ + [ + "Phenotypes", + "Phenotypes" + ], + [ + "Genotypes", + "Genotypes" + ] + ], "HLC": [ [ "Phenotypes", @@ -3012,6 +4010,10 @@ "Genotypes", "Genotypes" ], + [ + "Adipose mRNA", + "Adipose mRNA" + ], [ "Adrenal Gland mRNA", "Adrenal Gland mRNA" @@ -3040,10 +4042,22 @@ "Eye mRNA", "Eye mRNA" ], + [ + "Gastrointestinal mRNA", + "Gastrointestinal mRNA" + ], + [ + "Heart mRNA", + "Heart mRNA" + ], [ "Hematopoietic Cells mRNA", "Hematopoietic Cells mRNA" ], + [ + "Hippocampus microRNA", + "Hippocampus microRNA" + ], [ "Hippocampus mRNA", "Hippocampus mRNA" @@ -3060,6 +4074,10 @@ "Leucocytes mRNA", "Leucocytes mRNA" ], + [ + "Liver Metabolome", + "Liver Metabolome" + ], [ "Liver mRNA", "Liver mRNA" @@ -3076,6 +4094,10 @@ "Midbrain mRNA", "Midbrain mRNA" ], + [ + "Muscle Metabolome", + "Muscle Metabolome" + ], [ "Muscle mRNA", "Muscle mRNA" @@ -3259,6 +4281,16 @@ "Prefrontal Cortex mRNA" ] ], + "Linsenbardt-Boehm": [ + [ + "Phenotypes", + "Phenotypes" + ], + [ + "Genotypes", + "Genotypes" + ] + ], "MDP": [ [ "Phenotypes", @@ -3385,6 +4417,16 @@ ] }, "soybean": { + "J12XJ58F11": [ + [ + "Phenotypes", + "Phenotypes" + ], + [ + "Genotypes", + "Genotypes" + ] + ], "J12XJ58F2": [ [ "Phenotypes", diff --git a/wqflask/wqflask/static/new/javascript/get_traits_from_collection.coffee b/wqflask/wqflask/static/new/javascript/get_traits_from_collection.coffee index 691eb798..78d69f7a 100755 --- a/wqflask/wqflask/static/new/javascript/get_traits_from_collection.coffee +++ b/wqflask/wqflask/static/new/javascript/get_traits_from_collection.coffee @@ -5,6 +5,8 @@ console.log("before get_traits_from_collection") collection_list = null this_trait_data = null +selected_traits = {} + collection_click = () -> console.log("Clicking on:", $(this)) this_collection_url = $(this).find('.collection_name').prop("href") @@ -17,10 +19,52 @@ collection_click = () -> success: process_traits ) +submit_click = () -> + + selected_traits = {} + + traits = [] + $('#collections_holder').find('input[type=checkbox]:checked').each -> + this_trait = $(@).parents('tr').find('.trait').text() + console.log("this_trait is:", this_trait) + this_dataset = $(@).parents('tr').find('.dataset').text() + console.log("this_dataset is:", this_dataset) + this_trait_url = "/trait/get_sample_data?trait="+this_trait+"&dataset="+this_dataset + $.ajax( + dataType: "json", + url: this_trait_url, + async: false, + success: add_trait_data + ) + + console.log("SELECTED_TRAITS IS:", selected_traits) + + trait_names = [] + samples = $('input[name=allsamples]').val().split(" ") + all_vals = [] + + this_trait_vals = get_this_trait_vals(samples) + all_vals.push(this_trait_vals) + + for trait in Object.keys(selected_traits) + trait_names.push(trait) + + this_trait_vals = [] + for sample in samples + if sample in Object.keys(selected_traits[trait]) + this_trait_vals.push(parseFloat(selected_traits[trait][sample])) + else + this_trait_vals.push(null) + all_vals.push(this_trait_vals) + + create_scatterplots(trait_names, samples, all_vals) + + $.colorbox.close() + trait_click = () -> console.log("Clicking on:", $(this)) - trait = $(this).find('.trait').text() - dataset = $(this).find('.dataset').text() + trait = $(this).parent().find('.trait').text() + dataset = $(this).parent().find('.dataset').text() this_trait_url = "/trait/get_sample_data?trait="+trait+"&dataset="+dataset console.log("this_trait_url", this_trait_url) $.ajax( @@ -29,10 +73,18 @@ trait_click = () -> success: get_trait_data ) $.colorbox.close() - -get_trait_data = (trait_sample_data, textStatus, jqXHR) -> - trait_list = $('input[name=compare_traits]') - console.log("trait_list:", trait_list.val()) + +add_trait_data = (trait_data, textStatus, jqXHR) -> + trait_name = trait_data[0] + trait_sample_data = trait_data[1] + selected_traits[trait_name] = trait_sample_data + console.log("selected_traits:", selected_traits) + +get_trait_data = (trait_data, textStatus, jqXHR) -> + #trait_list = $('input[name=compare_traits]') + #console.log("trait_list:", trait_list.val()) + console.log("trait:", trait_data[0]) + trait_sample_data = trait_data[1] console.log("trait_sample_data:", trait_sample_data) samples = $('input[name=allsamples]').val().split(" ") vals = [] @@ -59,7 +111,6 @@ get_trait_data = (trait_sample_data, textStatus, jqXHR) -> console.log("THE LENGTH IS:", $('input[name=vals]').length) if $('input[name=vals]').length == 1 create_scatterplot(samples, [this_trait_vals, vals]) - get_this_trait_vals = (samples) -> @@ -99,12 +150,15 @@ process_traits = (trait_data, textStatus, jqXHR) -> the_html = "" + the_html += " " the_html += "" - the_html += "" + the_html += "" the_html += "" for trait in trait_data - the_html += "" + the_html += "" + the_html += "" + the_html += "" the_html += "" the_html += "" the_html += "" @@ -125,6 +179,7 @@ $ -> console.log("inside get_traits_from_collection") $(document).on("click", ".collection_line", collection_click) - $(document).on("click", ".trait_line", trait_click) + $(document).on("click", "#submit", submit_click) + $(document).on("click", ".trait", trait_click) $(document).on("click", "#back_to_collections", back_to_collections) diff --git a/wqflask/wqflask/static/new/javascript/get_traits_from_collection.js b/wqflask/wqflask/static/new/javascript/get_traits_from_collection.js index 146c2619..df3eacf3 100755 --- a/wqflask/wqflask/static/new/javascript/get_traits_from_collection.js +++ b/wqflask/wqflask/static/new/javascript/get_traits_from_collection.js @@ -1,6 +1,6 @@ // Generated by CoffeeScript 1.6.1 (function() { - var assemble_into_json, back_to_collections, collection_click, collection_list, color_by_trait, get_this_trait_vals, get_trait_data, process_traits, this_trait_data, trait_click, + var add_trait_data, assemble_into_json, back_to_collections, collection_click, collection_list, color_by_trait, get_this_trait_vals, get_trait_data, process_traits, selected_traits, submit_click, this_trait_data, trait_click, __indexOf = [].indexOf || function(item) { for (var i = 0, l = this.length; i < l; i++) { if (i in this && this[i] === item) return i; } return -1; }; console.log("before get_traits_from_collection"); @@ -9,6 +9,8 @@ this_trait_data = null; + selected_traits = {}; + collection_click = function() { var this_collection_url; console.log("Clicking on:", $(this)); @@ -23,11 +25,54 @@ }); }; + submit_click = function() { + var all_vals, sample, samples, this_trait_vals, trait, trait_names, traits, _i, _j, _len, _len1, _ref; + selected_traits = {}; + traits = []; + $('#collections_holder').find('input[type=checkbox]:checked').each(function() { + var this_dataset, this_trait, this_trait_url; + this_trait = $(this).parents('tr').find('.trait').text(); + console.log("this_trait is:", this_trait); + this_dataset = $(this).parents('tr').find('.dataset').text(); + console.log("this_dataset is:", this_dataset); + this_trait_url = "/trait/get_sample_data?trait=" + this_trait + "&dataset=" + this_dataset; + return $.ajax({ + dataType: "json", + url: this_trait_url, + async: false, + success: add_trait_data + }); + }); + console.log("SELECTED_TRAITS IS:", selected_traits); + trait_names = []; + samples = $('input[name=allsamples]').val().split(" "); + all_vals = []; + this_trait_vals = get_this_trait_vals(samples); + all_vals.push(this_trait_vals); + _ref = Object.keys(selected_traits); + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + trait = _ref[_i]; + trait_names.push(trait); + this_trait_vals = []; + for (_j = 0, _len1 = samples.length; _j < _len1; _j++) { + sample = samples[_j]; + if (__indexOf.call(Object.keys(selected_traits[trait]), sample) >= 0) { + this_trait_vals.push(parseFloat(selected_traits[trait][sample])); + } else { + this_trait_vals.push(null); + } + } + all_vals.push(this_trait_vals); + } + create_scatterplots(trait_names, samples, all_vals); + return $.colorbox.close(); + }; + trait_click = function() { var dataset, this_trait_url, trait; console.log("Clicking on:", $(this)); - trait = $(this).find('.trait').text(); - dataset = $(this).find('.dataset').text(); + trait = $(this).parent().find('.trait').text(); + dataset = $(this).parent().find('.dataset').text(); this_trait_url = "/trait/get_sample_data?trait=" + trait + "&dataset=" + dataset; console.log("this_trait_url", this_trait_url); return $.ajax({ @@ -39,10 +84,18 @@ $.colorbox.close(); - get_trait_data = function(trait_sample_data, textStatus, jqXHR) { - var sample, samples, this_trait_vals, trait_list, vals, _i, _len; - trait_list = $('input[name=compare_traits]'); - console.log("trait_list:", trait_list.val()); + add_trait_data = function(trait_data, textStatus, jqXHR) { + var trait_name, trait_sample_data; + trait_name = trait_data[0]; + trait_sample_data = trait_data[1]; + selected_traits[trait_name] = trait_sample_data; + return console.log("selected_traits:", selected_traits); + }; + + get_trait_data = function(trait_data, textStatus, jqXHR) { + var sample, samples, this_trait_vals, trait_sample_data, vals, _i, _len; + console.log("trait:", trait_data[0]); + trait_sample_data = trait_data[1]; console.log("trait_sample_data:", trait_sample_data); samples = $('input[name=allsamples]').val().split(" "); vals = []; @@ -105,12 +158,15 @@ console.log('in process_traits with trait_data:', trait_data); the_html = ""; + the_html += " "; the_html += "
RecordData SetDescriptionMean
RecordData SetDescriptionMean
#{ trait.name }
#{ trait.name }#{ trait.dataset }#{ trait.description }#{ trait.mean or ' ' }
"; - the_html += ""; + the_html += ""; the_html += ""; for (_i = 0, _len = trait_data.length; _i < _len; _i++) { trait = trait_data[_i]; - the_html += ""; + the_html += ""; + the_html += ""; + the_html += ""; the_html += ""; the_html += ""; the_html += ""; @@ -131,7 +187,8 @@ $(function() { console.log("inside get_traits_from_collection"); $(document).on("click", ".collection_line", collection_click); - $(document).on("click", ".trait_line", trait_click); + $(document).on("click", "#submit", submit_click); + $(document).on("click", ".trait", trait_click); return $(document).on("click", "#back_to_collections", back_to_collections); }); diff --git a/wqflask/wqflask/static/new/javascript/lod_chart.coffee b/wqflask/wqflask/static/new/javascript/lod_chart.coffee index 41e9c311..38325e60 100644 --- a/wqflask/wqflask/static/new/javascript/lod_chart.coffee +++ b/wqflask/wqflask/static/new/javascript/lod_chart.coffee @@ -156,7 +156,7 @@ lodchart = () -> .attr("transform", if rotate_ylab then "rotate(270,#{margin.left-axispos.ytitle},#{margin.top+height/2})" else "") if data['additive'].length > 0 - rotate_additive_ylab = rotate_additive_ylab ? (additive_ylab.length > 1) + rotate_additive_ylab = rotate_additive_ylab ? (additive_ylab.length > 1) additive_yaxis = g.append("g").attr("class", "y axis") additive_yaxis.selectAll("empty") .data(additive_yticks) @@ -343,11 +343,11 @@ lodchart = () -> ylim = value chart - if data['additive'].length > 0 - chart.additive_ylim = (value) -> - return additive_ylim unless arguments.length - additive_ylim = value - chart + #if data['additive'].length > 0 + chart.additive_ylim = (value) -> + return additive_ylim unless arguments.length + additive_ylim = value + chart chart.nyticks = (value) -> return nyticks unless arguments.length @@ -437,9 +437,9 @@ lodchart = () -> chart.yscale = () -> return yscale - if data['additive'].length > 0 - chart.additive_yscale = () -> - return additive_yscale + #if data['additive'].length > 0 + chart.additive_yscale = () -> + return additive_yscale chart.xscale = () -> return xscale @@ -447,9 +447,9 @@ lodchart = () -> chart.lodcurve = () -> return lodcurve - if data['additive'].length > 0 - chart.additivecurve = () -> - return additivecurve + #if data['additive'].length > 0 + chart.additivecurve = () -> + return additivecurve chart.markerSelect = () -> return markerSelect diff --git a/wqflask/wqflask/static/new/javascript/lod_chart.js b/wqflask/wqflask/static/new/javascript/lod_chart.js index 14aff1a7..0938cf06 100644 --- a/wqflask/wqflask/static/new/javascript/lod_chart.js +++ b/wqflask/wqflask/static/new/javascript/lod_chart.js @@ -77,7 +77,9 @@ return _results; })(); ylim = ylim != null ? ylim : [0, d3.max(data[lodvarname])]; - additive_ylim = additive_ylim != null ? additive_ylim : [0, d3.max(data['additive'])]; + if (data['additive'].length > 0) { + additive_ylim = additive_ylim != null ? additive_ylim : [0, d3.max(data['additive'])]; + } lodvarnum = data.lodnames.indexOf(lodvarname); svg = d3.select(this).selectAll("svg").data([data]); gEnter = svg.enter().append("svg").append("g"); @@ -85,9 +87,13 @@ g = svg.select("g"); g.append("rect").attr("x", margin.left).attr("y", margin.top).attr("height", height).attr("width", width).attr("fill", darkrect).attr("stroke", "none"); yscale.domain(ylim).range([height + margin.top, margin.top + margin.inner]); - additive_yscale.domain(additive_ylim).range([height + margin.top, margin.top + margin.inner + height / 2]); + if (data['additive'].length > 0) { + additive_yscale.domain(additive_ylim).range([height + margin.top, margin.top + margin.inner + height / 2]); + } yticks = yticks != null ? yticks : yscale.ticks(nyticks); - additive_yticks = additive_yticks != null ? additive_yticks : additive_yscale.ticks(nyticks); + if (data['additive'].length > 0) { + additive_yticks = additive_yticks != null ? additive_yticks : additive_yscale.ticks(nyticks); + } data = reorgLodData(data, lodvarname); data = chrscales(data, width, chrGap, margin.left, pad4heatmap); xscale = data.xscale; @@ -129,21 +135,23 @@ return formatAxis(yticks)(d); }); yaxis.append("text").attr("class", "title").attr("y", margin.top + height / 2).attr("x", margin.left - axispos.ytitle).text(ylab).attr("transform", rotate_ylab ? "rotate(270," + (margin.left - axispos.ytitle) + "," + (margin.top + height / 2) + ")" : ""); - rotate_additive_ylab = rotate_additive_ylab != null ? rotate_additive_ylab : additive_ylab.length > 1; - additive_yaxis = g.append("g").attr("class", "y axis"); - additive_yaxis.selectAll("empty").data(additive_yticks).enter().append("line").attr("y1", function(d) { - return additive_yscale(d); - }).attr("y2", function(d) { - return additive_yscale(d); - }).attr("x1", margin.left + width).attr("x2", margin.left + width - 7).attr("fill", "none").attr("stroke", "white").attr("stroke-width", 1).style("pointer-events", "none"); - additive_yaxis.selectAll("empty").data(additive_yticks).enter().append("text").attr("y", function(d) { - return additive_yscale(d); - }).attr("x", function(d) { - return margin.left + width + axispos.ylabel + 20; - }).attr("fill", "green").text(function(d) { - return formatAxis(additive_yticks)(d); - }); - additive_yaxis.append("text").attr("class", "title").attr("y", margin.top + 1.5 * height).attr("x", margin.left + width + axispos.ytitle).text(additive_ylab).attr("transform", rotate_additive_ylab ? "rotate(270," + (margin.left + width + axispos.ytitle) + ", " + (margin.top + height * 1.5) + ")" : ""); + if (data['additive'].length > 0) { + rotate_additive_ylab = rotate_additive_ylab != null ? rotate_additive_ylab : additive_ylab.length > 1; + additive_yaxis = g.append("g").attr("class", "y axis"); + additive_yaxis.selectAll("empty").data(additive_yticks).enter().append("line").attr("y1", function(d) { + return additive_yscale(d); + }).attr("y2", function(d) { + return additive_yscale(d); + }).attr("x1", margin.left + width).attr("x2", margin.left + width - 7).attr("fill", "none").attr("stroke", "white").attr("stroke-width", 1).style("pointer-events", "none"); + additive_yaxis.selectAll("empty").data(additive_yticks).enter().append("text").attr("y", function(d) { + return additive_yscale(d); + }).attr("x", function(d) { + return margin.left + width + axispos.ylabel + 20; + }).attr("fill", "green").text(function(d) { + return formatAxis(additive_yticks)(d); + }); + additive_yaxis.append("text").attr("class", "title").attr("y", margin.top + 1.5 * height).attr("x", margin.left + width + axispos.ytitle).text(additive_ylab).attr("transform", rotate_additive_ylab ? "rotate(270," + (margin.left + width + axispos.ytitle) + ", " + (margin.top + height * 1.5) + ")" : ""); + } suggestive_bar = g.append("g").attr("class", "suggestive"); suggestive_bar.selectAll("empty").data([data.suggestive]).enter().append("line").attr("y1", function(d) { return yscale(d); @@ -163,13 +171,15 @@ return yscale(data.lodByChr[chr][i][lodcolumn]); }); }; - additivecurve = function(chr, lodcolumn) { - return d3.svg.line().x(function(d) { - return xscale[chr](d); - }).y(function(d, i) { - return additive_yscale(data.additiveByChr[chr][i][lodcolumn]); - }); - }; + if (data['additive'].length > 0) { + additivecurve = function(chr, lodcolumn) { + return d3.svg.line().x(function(d) { + return xscale[chr](d); + }).y(function(d, i) { + return additive_yscale(data.additiveByChr[chr][i][lodcolumn]); + }); + }; + } curves = g.append("g").attr("id", "curves"); _ref = data.chrnames; for (_i = 0, _len = _ref.length; _i < _len; _i++) { @@ -434,16 +444,18 @@ if (!Array.isArray(data.lodnames)) { data.lodnames = [data.lodnames]; } - additiveval = (function() { - var _k, _len2, _ref2, _results; - _ref2 = data.lodnames; - _results = []; - for (_k = 0, _len2 = _ref2.length; _k < _len2; _k++) { - lodcolumn = _ref2[_k]; - _results.push(data['additive'][j]); - } - return _results; - })(); + if (data['additive'].length > 0) { + additiveval = (function() { + var _k, _len2, _ref2, _results; + _ref2 = data.lodnames; + _results = []; + for (_k = 0, _len2 = _ref2.length; _k < _len2; _k++) { + lodcolumn = _ref2[_k]; + _results.push(data['additive'][j]); + } + return _results; + })(); + } lodval = (function() { var _k, _len2, _ref2, _results; _ref2 = data.lodnames; diff --git a/wqflask/wqflask/static/new/javascript/marker_regression.coffee b/wqflask/wqflask/static/new/javascript/marker_regression.coffee index 8038ad9a..403ee52a 100755 --- a/wqflask/wqflask/static/new/javascript/marker_regression.coffee +++ b/wqflask/wqflask/static/new/javascript/marker_regression.coffee @@ -1,12 +1,17 @@ root = exports ? this class Manhattan_Plot - constructor: (@plot_height = 600, @plot_width = 1200) -> + constructor: (@height = 800, @width = 1200) -> @qtl_results = js_data.qtl_results console.log("qtl_results are:", @qtl_results) @chromosomes = js_data.chromosomes console.log("chromosomes are:", @chromosomes) - + + #For the description in the legend + @this_trait = js_data.this_trait + @data_set = js_data.data_set + @maf = js_data.maf #Minor allele frequency + @total_length = 0 @max_chr = @get_max_chr() @@ -23,8 +28,9 @@ class Manhattan_Plot [@chr_lengths, @cumulative_chr_lengths] = @get_chr_lengths() # Buffer to allow for the ticks/labels to be drawn - @x_buffer = @plot_width/30 - @y_buffer = @plot_height/20 + @x_buffer = @width/30 + @y_buffer = @height/20 + @legend_buffer = 30 #Height minus buffer for legend #@x_max = d3.max(@x_coords) @x_max = @total_length @@ -40,7 +46,7 @@ class Manhattan_Plot @plot_coordinates = _.zip(@x_coords, @y_coords, @marker_names) console.log("coordinates:", @plot_coordinates) - @plot_height -= @y_buffer + @height -= @y_buffer @create_scales() @@ -88,7 +94,7 @@ class Manhattan_Plot console.log("high_qtl_count:", high_qtl_count) #if high_qtl_count > 10000 - @y_axis_filter = 2 + @y_axis_filter = 0 #else if high_qtl_count > 1000 # @y_axis_filter = 1 #else @@ -132,8 +138,8 @@ class Manhattan_Plot svg = d3.select("#manhattan_plot") .append("svg") .attr("class", "manhattan_plot") - .attr("width", @plot_width+@x_buffer) - .attr("height", @plot_height+@y_buffer) + .attr("width", @width+@x_buffer) + .attr("height", @height+@y_buffer) .append("g") #.call(d3.behavior.zoom().x(@x_scale).y(@y_scale).scaleExtent([1,8]).on("zoom", () -> # @svg.selectAll("circle") @@ -149,7 +155,8 @@ class Manhattan_Plot #transform: (d) -> # return "translate(" + @x_scale(d[0]) + "," + @y_scale(d[1]) + ")" - create_graph: () -> + create_graph: () -> + @create_legend() @add_border() @add_x_axis() @add_y_axis() @@ -160,12 +167,36 @@ class Manhattan_Plot @add_plot_points() #@create_zoom_pane() + + create_legend: () -> + @svg.append("text") + .attr("class", "legend") + .text("Trait: " + @this_trait + " : " + @data_set) + .attr("x", @x_buffer) + .attr("y", 20) + .attr("dx", "0em") + .attr("text-anchor", "left") + .attr("font-family", "sans-serif") + .attr("font-size", "16px") + .attr("fill", "black") + + @svg.append("text") + .attr("class", "legend") + .text("MAF: " + @maf) + .attr("x", @x_buffer) + .attr("y", 38) + .attr("dx", "0em") + .attr("text-anchor", "left") + .attr("font-family", "sans-serif") + .attr("font-size", "16px") + .attr("fill", "black") + add_border: () -> - border_coords = [[@y_buffer, @plot_height, @x_buffer, @x_buffer], - [@y_buffer, @plot_height, @plot_width, @plot_width], - [@y_buffer, @y_buffer, @x_buffer, @plot_width], - [@plot_height, @plot_height, @x_buffer, @plot_width]] + border_coords = [[@y_buffer + @legend_buffer, @height, @x_buffer, @x_buffer], + [@y_buffer + @legend_buffer, @height, @width, @width], + [@y_buffer + @legend_buffer, @y_buffer + @legend_buffer, @x_buffer, @width], + [@height, @height, @x_buffer, @width]] @svg.selectAll("line") .data(border_coords) @@ -188,7 +219,7 @@ class Manhattan_Plot create_scales: () -> #@x_scale = d3.scale.linear() # .domain([0, d3.max(@x_coords)]) - # .range([@x_buffer, @plot_width]) + # .range([@x_buffer, @width]) console.log("y_axis_filter:", @y_axis_filter) if '24' of @chromosomes console.log("@chromosomes[24]:", @chromosomes['24']) @@ -197,14 +228,14 @@ class Manhattan_Plot console.log("d3.max(@xcoords):", d3.max(@x_coords)) @x_scale = d3.scale.linear() .domain([0, (@total_length + @chromosomes['24'])]) - .range([@x_buffer, @plot_width]) + .range([@x_buffer, @width]) else @x_scale = d3.scale.linear() .domain([0, (@total_length + @chromosomes['20'])]) - .range([@x_buffer, @plot_width]) + .range([@x_buffer, @width]) @y_scale = d3.scale.linear() .domain([@y_axis_filter, @y_max]) - .range([@plot_height, @y_buffer]) + .range([@height, @y_buffer + @legend_buffer]) create_x_axis_tick_values: () -> tick_vals = [] @@ -251,7 +282,7 @@ class Manhattan_Plot @svg.append("g") .attr("class", "x_axis") - .attr("transform", "translate(0," + @plot_height + ")") + .attr("transform", "translate(0," + @height + ")") .call(@xAxis) .selectAll("text") .attr("text-anchor", "right") @@ -275,7 +306,7 @@ class Manhattan_Plot add_axis_labels: () -> @svg.append("text") .attr("transform","rotate(-90)") - .attr("y", 0 - (@plot_height / 2)) + .attr("y", 0 - (@height / 2)) .attr("x", @x_buffer) .attr("dy", "1em") .style("text-anchor", "middle") @@ -290,8 +321,8 @@ class Manhattan_Plot .append("line") .attr("x1", @x_scale) .attr("x2", @x_scale) - .attr("y1", @y_buffer) - .attr("y2", @plot_height) + .attr("y1", @y_buffer + @legend_buffer) + .attr("y2", @height) .style("stroke", "#ccc") @@ -307,7 +338,7 @@ class Manhattan_Plot .attr("x", (d, i) => return @x_scale(d[1] - d[0]) ) - .attr("y", @y_buffer + 2) + .attr("y", @y_buffer + @legend_buffer + 2) .attr("width", (d, i) => starting = @x_scale(d[1] - d[0]) ending = @x_scale(@cumulative_chr_lengths[i]) @@ -315,7 +346,7 @@ class Manhattan_Plot console.log("width:", d[0]) return width ) - .attr("height", @plot_height-@y_buffer-3) + .attr("height", @height-@y_buffer - @legend_buffer-3) .attr("fill", (d, i) => if (i+1)%2 return "none" @@ -342,7 +373,7 @@ class Manhattan_Plot # .attr("width", (d) => # return @x_scale(d[0]) # ) - # .attr("height", @plot_height-@y_buffer) + # .attr("height", @height-@y_buffer) # .attr("fill", (d, i) => # return "whitesmoke" # #if i%2 @@ -380,7 +411,7 @@ class Manhattan_Plot .attr("x", (d) => return @x_scale(d[2] - d[1]/2) ) - .attr("y", @plot_height * 0.1) + .attr("y", @height * 0.1 + @legend_buffer) .attr("dx", "0em") .attr("text-anchor", "middle") .attr("font-family", "sans-serif") @@ -468,8 +499,8 @@ class Manhattan_Plot @svg.append("rect") .attr("class", "pane") - .attr("width", @plot_width) - .attr("height", @plot_height) + .attr("width", @width) + .attr("height", @height) .call(zoom) draw: () -> diff --git a/wqflask/wqflask/static/new/javascript/marker_regression.js b/wqflask/wqflask/static/new/javascript/marker_regression.js index e3c316dd..8c235189 100755 --- a/wqflask/wqflask/static/new/javascript/marker_regression.js +++ b/wqflask/wqflask/static/new/javascript/marker_regression.js @@ -7,14 +7,17 @@ Manhattan_Plot = (function() { - function Manhattan_Plot(plot_height, plot_width) { + function Manhattan_Plot(height, width) { var _ref; - this.plot_height = plot_height != null ? plot_height : 600; - this.plot_width = plot_width != null ? plot_width : 1200; + this.height = height != null ? height : 800; + this.width = width != null ? width : 1200; this.qtl_results = js_data.qtl_results; console.log("qtl_results are:", this.qtl_results); this.chromosomes = js_data.chromosomes; console.log("chromosomes are:", this.chromosomes); + this.this_trait = js_data.this_trait; + this.data_set = js_data.data_set; + this.maf = js_data.maf; this.total_length = 0; this.max_chr = this.get_max_chr(); this.x_coords = []; @@ -27,8 +30,9 @@ console.log("@y_coords: ", this.y_coords); console.timeEnd('Create coordinates'); _ref = this.get_chr_lengths(), this.chr_lengths = _ref[0], this.cumulative_chr_lengths = _ref[1]; - this.x_buffer = this.plot_width / 30; - this.y_buffer = this.plot_height / 20; + this.x_buffer = this.width / 30; + this.y_buffer = this.height / 20; + this.legend_buffer = 30; this.x_max = this.total_length; console.log("@x_max: ", this.x_max); console.log("@x_buffer: ", this.x_buffer); @@ -37,7 +41,7 @@ console.log("svg created"); this.plot_coordinates = _.zip(this.x_coords, this.y_coords, this.marker_names); console.log("coordinates:", this.plot_coordinates); - this.plot_height -= this.y_buffer; + this.height -= this.y_buffer; this.create_scales(); console.time('Create graph'); this.create_graph(); @@ -94,7 +98,7 @@ } } console.log("high_qtl_count:", high_qtl_count); - return this.y_axis_filter = 2; + return this.y_axis_filter = 0; }; Manhattan_Plot.prototype.create_coordinates = function() { @@ -143,11 +147,12 @@ Manhattan_Plot.prototype.create_svg = function() { var svg; - svg = d3.select("#manhattan_plot").append("svg").attr("class", "manhattan_plot").attr("width", this.plot_width + this.x_buffer).attr("height", this.plot_height + this.y_buffer).append("g"); + svg = d3.select("#manhattan_plot").append("svg").attr("class", "manhattan_plot").attr("width", this.width + this.x_buffer).attr("height", this.height + this.y_buffer).append("g"); return svg; }; Manhattan_Plot.prototype.create_graph = function() { + this.create_legend(); this.add_border(); this.add_x_axis(); this.add_y_axis(); @@ -158,10 +163,15 @@ return this.add_plot_points(); }; + Manhattan_Plot.prototype.create_legend = function() { + this.svg.append("text").attr("class", "legend").text("Trait: " + this.this_trait + " : " + this.data_set).attr("x", this.x_buffer).attr("y", 20).attr("dx", "0em").attr("text-anchor", "left").attr("font-family", "sans-serif").attr("font-size", "16px").attr("fill", "black"); + return this.svg.append("text").attr("class", "legend").text("MAF: " + this.maf).attr("x", this.x_buffer).attr("y", 38).attr("dx", "0em").attr("text-anchor", "left").attr("font-family", "sans-serif").attr("font-size", "16px").attr("fill", "black"); + }; + Manhattan_Plot.prototype.add_border = function() { var border_coords, _this = this; - border_coords = [[this.y_buffer, this.plot_height, this.x_buffer, this.x_buffer], [this.y_buffer, this.plot_height, this.plot_width, this.plot_width], [this.y_buffer, this.y_buffer, this.x_buffer, this.plot_width], [this.plot_height, this.plot_height, this.x_buffer, this.plot_width]]; + border_coords = [[this.y_buffer + this.legend_buffer, this.height, this.x_buffer, this.x_buffer], [this.y_buffer + this.legend_buffer, this.height, this.width, this.width], [this.y_buffer + this.legend_buffer, this.y_buffer + this.legend_buffer, this.x_buffer, this.width], [this.height, this.height, this.x_buffer, this.width]]; return this.svg.selectAll("line").data(border_coords).enter().append("line").attr("y1", function(d) { return d[0]; }).attr("y2", function(d) { @@ -180,11 +190,11 @@ console.log("@chromosomes[23]:", this.chromosomes['23']); console.log("@total_length:", this.total_length); console.log("d3.max(@xcoords):", d3.max(this.x_coords)); - this.x_scale = d3.scale.linear().domain([0, this.total_length + this.chromosomes['24']]).range([this.x_buffer, this.plot_width]); + this.x_scale = d3.scale.linear().domain([0, this.total_length + this.chromosomes['24']]).range([this.x_buffer, this.width]); } else { - this.x_scale = d3.scale.linear().domain([0, this.total_length + this.chromosomes['20']]).range([this.x_buffer, this.plot_width]); + this.x_scale = d3.scale.linear().domain([0, this.total_length + this.chromosomes['20']]).range([this.x_buffer, this.width]); } - return this.y_scale = d3.scale.linear().domain([this.y_axis_filter, this.y_max]).range([this.plot_height, this.y_buffer]); + return this.y_scale = d3.scale.linear().domain([this.y_axis_filter, this.y_max]).range([this.height, this.y_buffer + this.legend_buffer]); }; Manhattan_Plot.prototype.create_x_axis_tick_values = function() { @@ -237,7 +247,7 @@ } return tick_val; }); - return this.svg.append("g").attr("class", "x_axis").attr("transform", "translate(0," + this.plot_height + ")").call(this.xAxis).selectAll("text").attr("text-anchor", "right").attr("dx", "-1.6em").attr("transform", function(d) { + return this.svg.append("g").attr("class", "x_axis").attr("transform", "translate(0," + this.height + ")").call(this.xAxis).selectAll("text").attr("text-anchor", "right").attr("dx", "-1.6em").attr("transform", function(d) { return "translate(-12,0) rotate(-90)"; }); }; @@ -248,14 +258,14 @@ }; Manhattan_Plot.prototype.add_axis_labels = function() { - return this.svg.append("text").attr("transform", "rotate(-90)").attr("y", 0 - (this.plot_height / 2)).attr("x", this.x_buffer).attr("dy", "1em").style("text-anchor", "middle").text("LOD Score"); + return this.svg.append("text").attr("transform", "rotate(-90)").attr("y", 0 - (this.height / 2)).attr("x", this.x_buffer).attr("dy", "1em").style("text-anchor", "middle").text("LOD Score"); }; Manhattan_Plot.prototype.add_chr_lines = function() { var _this = this; return this.svg.selectAll("line").data(this.cumulative_chr_lengths, function(d) { return d; - }).enter().append("line").attr("x1", this.x_scale).attr("x2", this.x_scale).attr("y1", this.y_buffer).attr("y2", this.plot_height).style("stroke", "#ccc"); + }).enter().append("line").attr("x1", this.x_scale).attr("x2", this.x_scale).attr("y1", this.y_buffer + this.legend_buffer).attr("y2", this.height).style("stroke", "#ccc"); }; Manhattan_Plot.prototype.fill_chr_areas = function() { @@ -266,14 +276,14 @@ return d; }).enter().append("rect").attr("x", function(d, i) { return _this.x_scale(d[1] - d[0]); - }).attr("y", this.y_buffer + 2).attr("width", function(d, i) { + }).attr("y", this.y_buffer + this.legend_buffer + 2).attr("width", function(d, i) { var ending, starting, width; starting = _this.x_scale(d[1] - d[0]); ending = _this.x_scale(_this.cumulative_chr_lengths[i]); width = ending - starting; console.log("width:", d[0]); return width; - }).attr("height", this.plot_height - this.y_buffer - 3).attr("fill", function(d, i) { + }).attr("height", this.height - this.y_buffer - this.legend_buffer - 3).attr("fill", function(d, i) { if ((i + 1) % 2) { return "none"; } else { @@ -310,7 +320,7 @@ } }).attr("x", function(d) { return _this.x_scale(d[2] - d[1] / 2); - }).attr("y", this.plot_height * 0.1).attr("dx", "0em").attr("text-anchor", "middle").attr("font-family", "sans-serif").attr("font-size", "18px").attr("cursor", "pointer").attr("fill", "black").on("click", function(d) { + }).attr("y", this.height * 0.1 + this.legend_buffer).attr("dx", "0em").attr("text-anchor", "middle").attr("font-family", "sans-serif").attr("font-size", "18px").attr("cursor", "pointer").attr("fill", "black").on("click", function(d) { var this_chr; this_chr = d; return _this.redraw_plot(d); @@ -359,7 +369,7 @@ Manhattan_Plot.prototype.create_zoom_pane = function() { var zoom; zoom = d3.behavior.zoom().on("zoom", draw); - return this.svg.append("rect").attr("class", "pane").attr("width", this.plot_width).attr("height", this.plot_height).call(zoom); + return this.svg.append("rect").attr("class", "pane").attr("width", this.width).attr("height", this.height).call(zoom); }; Manhattan_Plot.prototype.draw = function() { diff --git a/wqflask/wqflask/static/new/javascript/show_trait.coffee b/wqflask/wqflask/static/new/javascript/show_trait.coffee index 6b31124c..1a7f6a0b 100755 --- a/wqflask/wqflask/static/new/javascript/show_trait.coffee +++ b/wqflask/wqflask/static/new/javascript/show_trait.coffee @@ -94,11 +94,15 @@ $ -> all_samples = sample_lists[0].concat sample_lists[1] new Box_Plot(all_samples) - d3.select("#select_compare_trait").on("click", => + $('.qtlcharts').empty() open_trait_selection() ) + d3.select("#clear_compare_trait").on("click", => + $('.qtlcharts').empty() + ) + open_trait_selection = () -> $('#collections_holder').load('/collections/list?color_by_trait #collections_list', => $.colorbox( diff --git a/wqflask/wqflask/static/new/javascript/show_trait.js b/wqflask/wqflask/static/new/javascript/show_trait.js index 2f7dcf78..e1dc9e76 100755 --- a/wqflask/wqflask/static/new/javascript/show_trait.js +++ b/wqflask/wqflask/static/new/javascript/show_trait.js @@ -94,8 +94,12 @@ } }); d3.select("#select_compare_trait").on("click", function() { + $('.qtlcharts').empty(); return open_trait_selection(); }); + d3.select("#clear_compare_trait").on("click", function() { + return $('.qtlcharts').empty(); + }); open_trait_selection = function() { var _this = this; return $('#collections_holder').load('/collections/list?color_by_trait #collections_list', function() { diff --git a/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.coffee b/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.coffee index 6118eae8..b37cfe09 100755 --- a/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.coffee +++ b/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.coffee @@ -123,9 +123,9 @@ $ -> $("#static_progress_bar_container").modal() url = "/marker_regression" $('input[name=method]').val("plink") - $('input[name=mapping_display_all]').val($('input[name=display_all_plink]')) - $('input[name=suggestive]').val($('input[name=suggestive_plink]')) - $('input[name=maf]').val($('input[name=maf_plink]')) + $('input[name=mapping_display_all]').val($('input[name=display_all_plink]').val()) + $('input[name=suggestive]').val($('input[name=suggestive_plink]').val()) + $('input[name=maf]').val($('input[name=maf_plink]').val()) form_data = $('#trait_data_form').serialize() console.log("form_data is:", form_data) $.ajax( @@ -153,9 +153,9 @@ $ -> $("#static_progress_bar_container").modal() url = "/marker_regression" $('input[name=method]').val("gemma") - $('input[name=mapping_display_all]').val($('input[name=display_all_gemma]')) - $('input[name=suggestive]').val($('input[name=suggestive_gemma]')) - $('input[name=maf]').val($('input[name=maf_gemma]')) + $('input[name=mapping_display_all]').val($('input[name=display_all_gemma]').val()) + $('input[name=suggestive]').val($('input[name=suggestive_gemma]').val()) + $('input[name=maf]').val($('input[name=maf_gemma]').val()) form_data = $('#trait_data_form').serialize() console.log("form_data is:", form_data) $.ajax( diff --git a/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.js b/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.js index ee930c80..9b9070ba 100755 --- a/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.js +++ b/wqflask/wqflask/static/new/javascript/show_trait_mapping_tools.js @@ -135,9 +135,9 @@ $("#static_progress_bar_container").modal(); url = "/marker_regression"; $('input[name=method]').val("plink"); - $('input[name=mapping_display_all]').val($('input[name=display_all_plink]')); - $('input[name=suggestive]').val($('input[name=suggestive_plink]')); - $('input[name=maf]').val($('input[name=maf_plink]')); + $('input[name=mapping_display_all]').val($('input[name=display_all_plink]').val()); + $('input[name=suggestive]').val($('input[name=suggestive_plink]').val()); + $('input[name=maf]').val($('input[name=maf_plink]').val()); form_data = $('#trait_data_form').serialize(); console.log("form_data is:", form_data); $.ajax({ @@ -166,9 +166,9 @@ $("#static_progress_bar_container").modal(); url = "/marker_regression"; $('input[name=method]').val("gemma"); - $('input[name=mapping_display_all]').val($('input[name=display_all_gemma]')); - $('input[name=suggestive]').val($('input[name=suggestive_gemma]')); - $('input[name=maf]').val($('input[name=maf_gemma]')); + $('input[name=mapping_display_all]').val($('input[name=display_all_gemma]').val()); + $('input[name=suggestive]').val($('input[name=suggestive_gemma]').val()); + $('input[name=maf]').val($('input[name=maf_gemma]').val()); form_data = $('#trait_data_form').serialize(); console.log("form_data is:", form_data); $.ajax({ diff --git a/wqflask/wqflask/templates/correlation_matrix.html b/wqflask/wqflask/templates/correlation_matrix.html index b67ecb78..403d2a98 100755 --- a/wqflask/wqflask/templates/correlation_matrix.html +++ b/wqflask/wqflask/templates/correlation_matrix.html @@ -5,13 +5,16 @@ + + {% endblock %} {% block content %} {{ header("Correlation Matrix") }}
-
+
+
{% endblock %} -{% block js %} +{% block js %} + + + + + + + + {% endblock %} diff --git a/wqflask/wqflask/templates/interval_mapping.html b/wqflask/wqflask/templates/interval_mapping.html index e3c164ea..ad174b7b 100755 --- a/wqflask/wqflask/templates/interval_mapping.html +++ b/wqflask/wqflask/templates/interval_mapping.html @@ -1,12 +1,12 @@ {% extends "base.html" %} {% block title %}Interval Mapping{% endblock %} {% block css %} - + - + {% endblock %} {% block content %} @@ -19,7 +19,7 @@ Whole Genome Mapping
-
+
diff --git a/wqflask/wqflask/templates/show_trait_statistics_new.html b/wqflask/wqflask/templates/show_trait_statistics_new.html index 9b6b37a4..a9f5dd43 100755 --- a/wqflask/wqflask/templates/show_trait_statistics_new.html +++ b/wqflask/wqflask/templates/show_trait_statistics_new.html @@ -87,7 +87,10 @@
+
diff --git a/wqflask/wqflask/views.py b/wqflask/wqflask/views.py index aa33700f..7a484898 100755 --- a/wqflask/wqflask/views.py +++ b/wqflask/wqflask/views.py @@ -208,7 +208,8 @@ def marker_regression_page(): 'trait_id', 'dataset', 'method', - 'suggestive' + 'suggestive', + 'maf' ) start_vars = {} @@ -323,6 +324,10 @@ def corr_compute_page(): def corr_matrix_page(): print("In corr_matrix, request.form is:", pf(request.form)) template_vars = show_corr_matrix.CorrelationMatrix(request.form) + template_vars.js_data = json.dumps(template_vars.js_data, + default=json_default_handler, + indent=" ") + return render_template("correlation_matrix.html", **template_vars.__dict__) @app.route("/corr_scatter_plot") -- cgit v1.2.3
RecordData SetDescriptionMean
RecordData SetDescriptionMean
" + trait.name + "
" + trait.name + "" + trait.dataset + "" + trait.description + "" + (trait.mean || ' ') + "