diff options
Diffstat (limited to 'wqflask/tests/unit')
-rw-r--r-- | wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py | 33 | ||||
-rw-r--r-- | wqflask/tests/unit/wqflask/wgcna/__init__.py | 0 | ||||
-rw-r--r-- | wqflask/tests/unit/wqflask/wgcna/test_wgcna.py | 50 |
3 files changed, 66 insertions, 17 deletions
diff --git a/wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py b/wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py index 3747aeb8..868b0b0b 100644 --- a/wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py +++ b/wqflask/tests/unit/wqflask/marker_regression/test_run_mapping.py @@ -43,7 +43,7 @@ class TestRunMapping(unittest.TestCase): }) } self.dataset = AttributeSetter( - {"fullname": "dataser_1", "group": self.group, "type": "ProbeSet"}) + {"fullname": "dataset_1", "group": self.group, "type": "ProbeSet"}) self.chromosomes = AttributeSetter({"chromosomes": chromosomes}) self.trait = AttributeSetter( @@ -180,37 +180,36 @@ class TestRunMapping(unittest.TestCase): with mock.patch("wqflask.marker_regression.run_mapping.datetime.datetime", new=datetime_mock): export_mapping_results(dataset=self.dataset, trait=self.trait, markers=markers, - results_path="~/results", mapping_scale="physic", score_type="-log(p)", - transform="qnorm", covariates="Dataset1:Trait1,Dataset2:Trait2", n_samples="100", - vals_hash="") + results_path="~/results", mapping_method="gemma", mapping_scale="physic", + score_type="-logP", transform="qnorm", + covariates="Dataset1:Trait1,Dataset2:Trait2", + n_samples="100", vals_hash="") write_calls = [ mock.call('Time/Date: 09/01/19 / 10:12:12\n'), mock.call('Population: Human GP1_\n'), mock.call( - 'Data Set: dataser_1\n'), + 'Data Set: dataset_1\n'), mock.call('Trait: Test Name\n'), mock.call('Trait Hash: \n'), - mock.call('N Samples: 100\n'), mock.call( - 'Transform - Quantile Normalized\n'), + mock.call('N Samples: 100\n'), + mock.call('Mapping Tool: gemma\n'), + mock.call('Transform - Quantile Normalized\n'), mock.call('Gene Symbol: IGFI\n'), mock.call( 'Location: X1 @ 123313 Mb\n'), mock.call('Cofactors (dataset - trait):\n'), mock.call('Trait1 - Dataset1\n'), mock.call('Trait2 - Dataset2\n'), mock.call('\n'), mock.call('Name,Chr,'), - mock.call('Mb,-log(p)'), mock.call('Cm,-log(p)'), + mock.call('Mb,-logP'), mock.call(',Additive'), mock.call(',Dominance'), mock.call('\n'), mock.call('MK1,C1,'), - mock.call('12000,'), mock.call('1,'), - mock.call('3'), mock.call(',VA'), - mock.call(',TT'), mock.call('\n'), - mock.call('MK2,C2,'), mock.call('10000,'), - mock.call('15,'), mock.call('7'), + mock.call('12000,'), mock.call('3'), + mock.call(',VA'), mock.call(',TT'), + mock.call('\n'), mock.call('MK2,C2,'), + mock.call('10000,'), mock.call('7'), mock.call('\n'), mock.call('MK1,C3,'), - mock.call('1,'), mock.call('45,'), - mock.call('7'), mock.call(',VE'), - mock.call(',Tt') - + mock.call('1,'), mock.call('7'), + mock.call(',VE'), mock.call(',Tt') ] mock_open.assert_called_once_with("~/results", "w+") filehandler = mock_open() diff --git a/wqflask/tests/unit/wqflask/wgcna/__init__.py b/wqflask/tests/unit/wqflask/wgcna/__init__.py new file mode 100644 index 00000000..e69de29b --- /dev/null +++ b/wqflask/tests/unit/wqflask/wgcna/__init__.py diff --git a/wqflask/tests/unit/wqflask/wgcna/test_wgcna.py b/wqflask/tests/unit/wqflask/wgcna/test_wgcna.py new file mode 100644 index 00000000..8e947e2f --- /dev/null +++ b/wqflask/tests/unit/wqflask/wgcna/test_wgcna.py @@ -0,0 +1,50 @@ + +"""module contains for processing gn3 wgcna data""" +from unittest import TestCase + +from wqflask.wgcna.gn3_wgcna import process_wgcna_data + + +class DataProcessingTests(TestCase): + """class contains data processing tests""" + + def test_data_processing(self): + """test for parsing data for datatable""" + output = { + "input": { + "sample_names": ["BXD1", "BXD2", "BXD3", "BXD4", "BXD5", "BXD6"], + + }, + "output": { + "ModEigens": { + "MEturquoise": [ + 0.0646677768085351, + 0.137200224277058, + 0.63451113720732, + -0.544002665501479, + -0.489487590361863, + 0.197111117570427 + ], + "MEgrey": [ + 0.213, + 0.214, + 0.3141, + -0.545, + -0.423, + 0.156, + ] + }}} + + row_data = [['BXD1', 0.065, 0.213], + ['BXD2', 0.137, 0.214], + ['BXD3', 0.635, 0.314], + ['BXD4', -0.544, -0.545], + ['BXD5', -0.489, -0.423], + ['BXD6', 0.197, 0.156]] + + expected_results = { + "col_names": ["sample_names", "MEturquoise", "MEgrey"], + "mod_dataset": row_data + } + + self.assertEqual(process_wgcna_data(output), expected_results) |