def test_put_one_file1_in_dir(self):
"""
Test that one file is put in the dir correctly
"""
file1 = self.mkstemp(prefix="1.")
self.input = {
"output_directory_name": "foo",
"files": [
{
"class": "File",
"path": file1
},
]
}
output_json, output_dir = self.run_cwl()
expected_output = {
"directory":
ODir(name='foo',
dir=output_dir,
items=[
OFile(name=os.path.basename(file1),
size=0,
hash='da39a3ee5e6b4b0d3255bfef95601890afd80709')
])
}
self.assertCWLDictEqual(output_json, expected_output)
def test_run_worflow_one_maf(self):
"""
Test that the workflow works correctly when run with a single maf
"""
self.input = {
"is_impact": True,
"argos_version_string": "2.x",
"analysis_gene_cna_filename": "Proj_08390_G.gene.cna.txt",
"analysis_mutations_filename": "Proj_08390_G.muts.maf",
"analysis_mutations_share_filename": "Proj_08390_G.muts.share.maf",
"analysis_segment_cna_filename": "Proj_08390_G.seg.cna.txt",
"analysis_sv_filename": "Proj_08390_G.svs.maf",
"helix_filter_version": "20.06.1",
"IMPACT_gene_list": {
"class": "File",
"path": IMPACT_FILE
},
"targets_list": {
"path": DATA_SETS['Proj_08390_G']["targets_list"],
"class": "File"
},
"mutation_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample1.Sample2.muts.maf"),
"class": "File"
}
],
"mutation_svs_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample1.Sample2.svs.pass.vep.maf"),
"class": "File"
}
],
"facets_hisens_cncf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
}
],
"facets_hisens_seg_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.seg"),
"class": "File"
}
],
}
output_json, output_dir = self.run_cwl()
expected_output = {
'analysis_dir': ODir(name='analysis', items=[
OFile(name='Proj_08390_G.gene.cna.txt', size=87905, hash='7cc89d24556de93b9a409812317581e67e5df494'),
OFile(name='Proj_08390_G.muts.maf', size=33243, hash='2c8904927a917d6e935ef207582d995680574d16'),
OFile(name='Proj_08390_G.muts.share.maf', size=7462, hash='b5af4e0fcd89fecabf8095aa3d7690e5edb8dca1'),
OFile(name='Proj_08390_G.seg.cna.txt', size=1632, hash='f0ebb82c34b6530447fa1e70b6dedcc039840d61'),
OFile(name='Proj_08390_G.svs.maf', size=23603, hash='df420706bb5b772a79317843c0a01a3c88a9571d')], dir=output_dir)
}
self.assertCWLDictEqual(output_json, expected_output)
self.assertNumMutations(os.path.join(output_dir, 'analysis', 'Proj_08390_G.muts.maf'), 22)
def test_put_two_files_in_dir(self):
"""
Test that two files are put in the dir correctly
"""
file1 = self.mkstemp(prefix="1.")
file2 = self.mkstemp(prefix="2.")
# create input data
self.input = {
"output_directory_name":
"foo",
"files": [{
"class": "File",
"path": file1
}, {
"class": "File",
"path": file2
}]
}
output_json, output_dir = self.run_cwl()
expected_output = {
"directory":
ODir(name="foo",
dir=output_dir,
items=[
OFile(name=os.path.basename(file1),
size=0,
hash='da39a3ee5e6b4b0d3255bfef95601890afd80709'),
OFile(name=os.path.basename(file2),
size=0,
hash='da39a3ee5e6b4b0d3255bfef95601890afd80709'),
])
}
self.assertCWLDictEqual(output_json, expected_output)
def test_medium_workflow(self):
"""
...
---------
Ran 1 test in 8698.861s
"""
input_json = WORKFLOW_MEDIUM_JSON
output_json, output_dir = self.run_cwl(input = input_json, input_is_file = True)
expected_output = {
'analysis_dir': ODir(name='analysis', items=[
OFile(name='11089_G.gene.cna.txt', size=6547460, hash='72c2eb26e69f8dcb53cb0ff2d90997f2ae69f308'),
OFile(name='11089_G.muts.maf', size=416363, hash='16ee2715491a5f61810cfd7233163905fb497361'),
OFile(name='11089_G.muts.share.maf', size=66088, hash='8b3e0924733421535a3fc5a5d174eef4d5d92a28'),
OFile(name='11089_G.seg.cna.txt', size=69171, hash='7d13e1422b9d7112e60f9ab748d524d7446d1dde'),
OFile(name='11089_G.svs.maf', size=706820, hash='a4a799461650e4cc832e54de2df50a9e1b28a41c')], dir=output_dir),
'facets_dir': ODir(name='facets', items=[
ODir(name='Sample21.s_C_Patient21_N001_d', items=[
OFile(name='Sample21.s_C_Patient21_N001_d_hisens.ccf.portal.maf', size=108887494, hash='f4f5d6e0dae3c8ad89279910a4e083dc8471bcc2'),
OFile(name='Sample21.arm_level.txt', size=1900, hash='8af0ec2771d47ecb9c17727755094474d32a9f8b'),
OFile(name='Sample21.txt', size=591, hash='4350cbbdf4151b1f6a26b5269d4a227faed40f06'),
OFile(name='Sample21.gene_level.txt', size=569488, hash='6e663d203f0b17b52021c93e1b10cdcef6bf88b6'),
OFile(name='Sample21_hisens.cncf.txt', size=3642, hash='0ea89011191860974a6e98bc0fc8a55752979856'),
OFile(name='Sample21_hisens.rds', size=616659, hash='696afa887ffe3ea56de3824ab2d9483a8878186a'),
OFile(name='Sample21_hisens.seg', size=1361, hash='e62dd226d7d14884146ca263a7bf689108ebea7b'),
OFile(name='Sample21_purity.rds', size=616544, hash='bd51898f1d0d04bd761cc9e7ada7533c04f8cc7c'),
OFile(name='Sample21_purity.seg', size=1258, hash='b4fb384eb9dd63a938fe8b38001ad6b4a38fc8c5'),
OFile(name='Sample21.qc.txt', size=1283, hash='cfe0031e6ca74c700f7970839252376dda907deb')]),
ODir(name='Sample5.s_C_Patient5_N001_d', items=[
OFile(name='Sample5.s_C_Patient5_N001_d_hisens.ccf.portal.maf', size=51378563, hash='1886433b354d192591424faba968c975e880421b'),
OFile(name='Sample5.arm_level.txt', size=1504, hash='ce1d534e85fe61b72d7d732f0c5b94b9be4cd5bc'),
OFile(name='Sample5.txt', size=594, hash='df5143e3ef42c3546dd3a53ddd7c69679c94ece8'),
OFile(name='Sample5.gene_level.txt', size=701138, hash='107f1665e94907ca8ac507852b7031458a1524af'),
OFile(name='Sample5_hisens.cncf.txt', size=11955, hash='0e3745e5c13545ac9e179fc18b093f2197f095f0'),
OFile(name='Sample5_hisens.rds', size=768703, hash='1508ccc6b3334e14dcc25439668689fd8416c590'),
OFile(name='Sample5_hisens.seg', size=4206, hash='81d558ac13df8f87edb02759b5aa01a6a8065904'),
OFile(name='Sample5_purity.rds', size=766511, hash='5adc9fb028bcb7752a7550cc3c2e180a032179c7'),
OFile(name='Sample5_purity.seg', size=2285, hash='a1a35082d279dbc8cb06ad1a6f0b42a1d5601f1e'),
OFile(name='Sample5.qc.txt', size=1386, hash='540eb51045962627fe6c17e47b0f69e3cb35e081')]),
ODir(name='Sample1.s_C_Patient1_N001_d', items=[
OFile(name='Sample1.s_C_Patient1_N001_d_hisens.ccf.portal.maf', size=174888292, hash='0f9f3acc5b9bfeedc35713635eba030adf15e690'),
OFile(name='Sample1.arm_level.txt', size=1629, hash='07f5b70585370c5926f2849995f5d74af223e0db'),
OFile(name='Sample1.txt', size=590, hash='02018eabc346542db0589162f9a3a073726a3dd6'),
OFile(name='Sample1.gene_level.txt', size=901681, hash='a62c291ff0bc23c12cb1939a545925b3192ed2ea'),
OFile(name='Sample1_hisens.cncf.txt', size=17029, hash='0dc6f9ccb68f24ee50ff7cbe26ec37b537898625'),
OFile(name='Sample1_hisens.rds', size=728644, hash='5f64eb5770316eba7d1df10db097b2ee7ba609d9'),
OFile(name='Sample1_hisens.seg', size=5691, hash='64d2d15fc606b52f78d724eaa16aef05783bbf32'),
OFile(name='Sample1_purity.rds', size=725530, hash='26acecdeaa02189b43cb4ef8f747dca04d97f21b'),
OFile(name='Sample1_purity.seg', size=2967, hash='5f28d741b409e7dc92f9a2b4d502e657c56f8f9e'),
OFile(name='Sample1.qc.txt', size=1361, hash='fd3593a93588eb43ed78b74978704a5de3e56768')]),
ODir(name='Sample12.s_C_Patient12_N001_d',items=[
OFile(name='Sample12.s_C_Patient12_N001_d_hisens.ccf.portal.maf', size=33858338, hash='1bc7c99356930074ee412383a8798fec0ddea103'),
OFile(name='Sample12.arm_level.txt', size=1515, hash='47f866d25f6f2b2d226b64c76fc6b6d08ea46658'),
OFile(name='Sample12.txt', size=762, hash='07d1ea16f4ba78e59afc73c519cc95235053c502'),
OFile(name='Sample12.gene_level.txt', size=939824, hash='b6b7b1b792519139ad889b654e0fc4ac96486ae0'),
OFile(name='Sample12_hisens.cncf.txt', size=14938, hash='5e12530c6e9baebfbcaccecf55bd3cd34efd73ba'),
OFile(name='Sample12_hisens.rds', size=905882, hash='5b188c566a89510c3c5d2901fec48973226be27e'),
OFile(name='Sample12_hisens.seg', size=4805, hash='ead3884d2ac67dc7f58299d69f3c79df2a34b942'),
OFile(name='Sample12_purity.rds', size=903732, hash='7f1b31c5c4bb33e08b20d293852b7b90232c213f'),
OFile(name='Sample12_purity.seg', size=2697, hash='fe306a606d349eba7116d3d9c8bc053f765c40f0'),
OFile(name='Sample12.qc.txt', size=1368, hash='225589806bd1418b69f6e6b126f7854bc587c93f')]),
ODir(name='Sample17.s_C_Patient17_N001_d', items=[
OFile(name='Sample17.s_C_Patient17_N001_d_hisens.ccf.portal.maf', size=61845296, hash='8cdd2bc33f12565429c4d550dd23b871f628b380'),
OFile(name='Sample17.arm_level.txt', size=1451, hash='b040ff1705a708b9c3532f68af9b7ddce9c2e1af'),
OFile(name='Sample17.txt', size=711, hash='30c3a6df33fda7a4660e479ec83922b00a6f36dc'),
OFile(name='Sample17.gene_level.txt', size=674625, hash='36f45049e0a4f09e84477fb013cce104229fbe67'),
OFile(name='Sample17_hisens.cncf.txt', size=13569, hash='3a9e2d666c3dcd9ec9f6958f9e55b53a028e206b'),
OFile(name='Sample17_hisens.rds', size=718061, hash='621e576c38bb376b79e46fa2a327aede80933e5d'),
OFile(name='Sample17_hisens.seg', size=4397, hash='b085804e5608e5577623ec8fe9d233b781d3b644'),
OFile(name='Sample17_purity.rds', size=716807, hash='dbff46198bea8c4cdad0f1a65391e94eb37be0ff'),
OFile(name='Sample17_purity.seg', size=3066, hash='eff585106b1ff3e857ed074c241885af3844859b'),
OFile(name='Sample17.qc.txt', size=1353, hash='8bde8eb16eb3eb59d2a8b03d5f129ab649149f65')]),
ODir(name='Sample28.s_C_Patient28_N001_d', items=[
OFile(name='Sample28.s_C_Patient28_N001_d_hisens.ccf.portal.maf', size=120654677, hash='0c4ac1ca2c450fc16213a9aa1515b594c24814d0'),
OFile(name='Sample28.arm_level.txt', size=1909, hash='f9f9f8880538fd7833781f0a472d06c2e68cfc6c'),
OFile(name='Sample28.txt', size=597, hash='f553ef7868018ff066eae92fec5db08a19a4f197'),
OFile(name='Sample28.gene_level.txt', size=509340, hash='8d198a5658804849c9d99b210a6e0615eda23a67'),
OFile(name='Sample28_hisens.cncf.txt', size=4623, hash='8b4e4339705616a2eb9a611d26668ff259e0ea93'),
OFile(name='Sample28_hisens.rds', size=581539, hash='71b21ab0abf91eb2a31a19b1c36ca4ff4fe0ab82'),
OFile(name='Sample28_hisens.seg', size=1712, hash='870a4e66276768736191a622523b5664dfd5823b'),
OFile(name='Sample28_purity.rds', size=581286, hash='06d334d5ab287d12aef798cfad5d87f56084ce54'),
OFile(name='Sample28_purity.seg', size=1413, hash='1f4df7ff87caa5b2c39922d795a109f4374b5a34'),
OFile(name='Sample28.qc.txt', size=1329, hash='c9f96b6e74ad2aad0aaebef8a2f9fb0c1df8cbd7')]),
ODir(name='Sample16.s_C_Patient16_N001_d', items=[
OFile(name='Sample16.s_C_Patient16_N001_d_hisens.ccf.portal.maf', size=46188384, hash='542851d8d78ae2022d2d319298f2fca7fa1d94cb'),
OFile(name='Sample16.arm_level.txt', size=1709, hash='e5bd70471da5aceaf545be6405c5ab44da91064f'),
OFile(name='Sample16.txt', size=601, hash='8002c18881cecff90e3762d013974fb6981ea75b'),
OFile(name='Sample16.gene_level.txt', size=600614, hash='d4881c3f65a84e73195e8b56de325dfcf4e4e01a'),
OFile(name='Sample16_hisens.cncf.txt', size=8976, hash='147e638a415fc1c904d02431b2874efe33d0b342'),
OFile(name='Sample16_hisens.rds', size=773030, hash='59bab59e78318eb267d9589aa6f650959b47bc6a'),
OFile(name='Sample16_hisens.seg', size=3334, hash='1bb1490d894699925fc1f5ab89e4cbcb568f82b9'),
OFile(name='Sample16_purity.rds', size=771948, hash='f1b173c8507ad3b2a5dbf4cc9a95902bf408abd4'),
OFile(name='Sample16_purity.seg', size=2191, hash='b4065c5603c21724e5e74c8d49e2a0c97f712f2c'),
OFile(name='Sample16.qc.txt', size=1358, hash='5c982742449b705c0224c0656fcfea17baf46ee1')]),
ODir(name='Sample11.s_C_Patient11_N001_d', items=[
OFile(name='Sample11.s_C_Patient11_N001_d_hisens.ccf.portal.maf', size=36352097, hash='675e67d7ddc6ed75a41c458481bee8aa5bae857d'),
OFile(name='Sample11.arm_level.txt', size=1525, hash='13a74ad441b2c24a4affb855f8a79483846bfad5'),
OFile(name='Sample11.txt', size=639, hash='20a56017fd43021a02312fba1762420f40dc6c85'),
OFile(name='Sample11.gene_level.txt', size=671056, hash='bff64a96cf49f180086edf916e6c6bdf603b5ef3'),
OFile(name='Sample11_hisens.cncf.txt', size=10363, hash='3827502368c7347a3924a716b6fe60544cb3cc2f'),
OFile(name='Sample11_hisens.rds', size=720072, hash='bbd4d3725cee4707c957ef4aff8ea5ef811c189f'),
OFile(name='Sample11_hisens.seg', size=3638, hash='75f2c0c83b1ac1cc8cc9bf819c71ac504fa9bee2'),
OFile(name='Sample11_purity.rds', size=719069, hash='17bcd89e06710f4086f87f023c6a182e493e3cc3'),
OFile(name='Sample11_purity.seg', size=2744, hash='ce3a31c4906a962ee2b43976132ef538168a697e'),
OFile(name='Sample11.qc.txt', size=1352, hash='43f0294dfb40a0421e56ea35926bfda484d43d23')]),
ODir(name='Sample13.s_C_Patient13_N001_d', items=[
OFile(name='Sample13.s_C_Patient13_N001_d_hisens.ccf.portal.maf', size=27544622, hash='f9785eee1574f6e85df67b80f6b60879fb7a1a61'),
OFile(name='Sample13.arm_level.txt', size=1619, hash='2c1211c420b4da7f336bd2fe99156e3b9b0e7c32'),
OFile(name='Sample13.txt', size=672, hash='b182fc5f96d497cdfced581afd409ab78e34eba8'),
OFile(name='Sample13.gene_level.txt', size=882343, hash='c8f71dfcd5244f344c1a481864f924eeb84ede65'),
OFile(name='Sample13_hisens.cncf.txt', size=9876, hash='3a9b5c3ada3eb41562781093ccdd211f43ddee96'),
OFile(name='Sample13_hisens.rds', size=923512, hash='f2db4d71b1d9a1b8da90603a81bbf514337869e2'),
OFile(name='Sample13_hisens.seg', size=3501, hash='05aef3b06f91eac0bc8a2034ffa75a2b585c5eeb'),
OFile(name='Sample13_purity.rds', size=921728, hash='3bf8506d3d77ad2a2cce4e39bbbbaed2bb5e3343'),
OFile(name='Sample13_purity.seg', size=1872, hash='27e67ba4902078d903b2317933bbbb0e36f16736'),
OFile(name='Sample13.qc.txt', size=1351, hash='71f68324b72f77e5d494c51791e08bccb6541467')]),
ODir(name='Sample3.s_C_Patient3_N001_d', items=[
OFile(name='Sample3.s_C_Patient3_N001_d_hisens.ccf.portal.maf', size=56270406, hash='d0115fa74a43e57498c11eb5148d8e7ef3c03fc9'),
OFile(name='Sample3.arm_level.txt', size=1865, hash='6ebe1352c2b63060f3dfc6ceb97a499dc04f318a'),
OFile(name='Sample3.txt', size=578, hash='270230a33f6571484d525b11214b1f2471b2dd56'),
OFile(name='Sample3.gene_level.txt', size=706751, hash='87320ad1d73e0a1e0ea52cf83ca1c24a18d94f40'),
OFile(name='Sample3_hisens.cncf.txt', size=3343, hash='38294c690440e183e8b4488a4452edd0ce60fab2'),
OFile(name='Sample3_hisens.rds', size=815782, hash='ec3e53d6131de9119ea20b59b32919574dff1679'),
OFile(name='Sample3_hisens.seg', size=1237, hash='8816010bda1aa473b55f972e5bf9302ab8877c87'),
OFile(name='Sample3_purity.rds', size=815832, hash='b47f2833cb6f00e5c144fa28249f69434e9a76ea'),
OFile(name='Sample3_purity.seg', size=1237, hash='8816010bda1aa473b55f972e5bf9302ab8877c87'),
OFile(name='Sample3.qc.txt', size=1254, hash='4981ecfa24438f1b7d622e745ba5020eaf60fa78')]),
ODir(name='Sample7.s_C_Patient7_N001_d', items=[
OFile(name='Sample7.s_C_Patient7_N001_d_hisens.ccf.portal.maf', size=45465885, hash='d6f82306ee11ec48d54656119ed1272d3ef25e3b'),
OFile(name='Sample7.arm_level.txt', size=1840, hash='c8a7436d18e42ed23011324ddfbe2df083b3ca79'),
OFile(name='Sample7.txt', size=710, hash='988de61c55ab77422f29d1341b2ef865dbea5f60'),
OFile(name='Sample7.gene_level.txt', size=553685, hash='bd0caff5b6612bbfc8bb8771965ccf9b631c8675'),
OFile(name='Sample7_hisens.cncf.txt', size=7995, hash='c520b7908d699e27f05e6e3c62dffa54aad369ff'),
OFile(name='Sample7_hisens.rds', size=622782, hash='038d4df531117a3f9d0113925d9b69df9b190c9c'),
OFile(name='Sample7_hisens.seg', size=2674, hash='6e7dbb031f046952400f0645b0fe93476e580c74'),
OFile(name='Sample7_purity.rds', size=622161, hash='05e660d9c69275f0984690b9e327782d3a92b7b9'),
OFile(name='Sample7_purity.seg', size=1913, hash='5df4463fe377d46e0b4d1714bae9a152ec094c86'),
OFile(name='Sample7.qc.txt', size=1337, hash='5b5b331eee7a5f05a1c8b997949087fba214d161')]),
ODir(name='Sample10.s_C_Patient10_N001_d', items=[
OFile(name='Sample10.s_C_Patient10_N001_d_hisens.ccf.portal.maf', size=63209220, hash='3600ec94d0321619b3294437b91a1b8beb79c97b'),
OFile(name='Sample10.arm_level.txt', size=1887, hash='637fa7259d0fa7e0d4c43ef6c68209c63c62b2dd'),
OFile(name='Sample10.txt', size=663, hash='b9ac85144c27a8d61d4042a20942d0df43152bb6'),
OFile(name='Sample10.gene_level.txt', size=1026175, hash='692a365e399f8c5636caeed38a8dcd9b1010905b'),
OFile(name='Sample10_hisens.cncf.txt', size=13605, hash='06520f90f7f38440d0e66bfe08874cbc97f2d0c9'),
OFile(name='Sample10_hisens.rds', size=891327, hash='f004ffd65e33e55bb0505dc898a32189d16c24ad'),
OFile(name='Sample10_hisens.seg', size=4591, hash='e6f9f208f8bae0a3080d221be79d422660eb0167'),
OFile(name='Sample10_purity.rds', size=889163, hash='35f953edbdca56e089874acf4217321b7cd94944'),
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OFile(name='Sample27.gene_level.txt', size=445227, hash='4792260db0f74a843aadd7578e1cc8753082ed3f'),
OFile(name='Sample27_hisens.cncf.txt', size=3406, hash='4a8df4aece8adbeaa043c060ed5ad952a0c95ef1'),
OFile(name='Sample27_hisens.rds', size=599275, hash='270aa7723ccf97cbc68e02010713b0dea8ccff6f'),
OFile(name='Sample27_hisens.seg', size=1257, hash='a9eef526748e2f1cb8a6cc634761c2b5bddca704'),
OFile(name='Sample27_purity.rds', size=599333, hash='ffb261d90559d1d656f5bd0711f487d6f427257c'),
OFile(name='Sample27_purity.seg', size=1257, hash='a9eef526748e2f1cb8a6cc634761c2b5bddca704'),
OFile(name='Sample27.qc.txt', size=1268, hash='d3f5a4522297d4dfa7503ecb9764aae05d8df418')]),
ODir(name='Sample2.s_C_Patient2_N001_d', items=[
OFile(name='Sample2.s_C_Patient2_N001_d_hisens.ccf.portal.maf', size=78410554, hash='854608265cb3f020a3000a54074cb15727dbe885'),
OFile(name='Sample2.arm_level.txt', size=1742, hash='050255a51a1476f211a71acbbb52f73c2541dae2'),
OFile(name='Sample2.txt', size=623, hash='128de962ad52ccbf06f975b3039f0b0c54d417d2'),
OFile(name='Sample2.gene_level.txt', size=655694, hash='45318af0025bfbd1a8cb97628f9729f44e0ccc85'),
OFile(name='Sample2_hisens.cncf.txt', size=7658, hash='a854b06c09f30966bc9137d6a14d0860c6138ccf'),
OFile(name='Sample2_hisens.rds', size=682739, hash='327ca88e5bfb7f135de4dfc60e06cf25b7967c26'),
OFile(name='Sample2_hisens.seg', size=2644, hash='6275921e635ec4044544d6c9343c67aa7dcd142c'),
OFile(name='Sample2_purity.rds', size=682025, hash='6261f146e6cad666f38862ed99ab0bbcbe1aab2a'),
OFile(name='Sample2_purity.seg', size=1928, hash='2e62b02dd63e4f1e6193480f3f741343ded1cb37'),
OFile(name='Sample2.qc.txt', size=1335, hash='fd593d3a1babf3903c95875114fba069812b907c')]),
ODir(name='Sample22.s_C_Patient22_N001_d', items=[
OFile(name='Sample22.s_C_Patient22_N001_d_hisens.ccf.portal.maf', size=232656074, hash='f9230b388b7688c257247b55a6d07e2a3cbe357b'),
OFile(name='Sample22.arm_level.txt', size=1877, hash='0d7680007e0c1d58efc39b6f3d1c4e907a09243e'),
OFile(name='Sample22.txt', size=600, hash='b43007c41f7810d5c0ab8cd3ccb05c204f3e6a76'),
OFile(name='Sample22.gene_level.txt', size=578835, hash='0cfbcd2c032aaf9ae8288c6c9c08b2dc9b9852d7'),
OFile(name='Sample22_hisens.cncf.txt', size=3398, hash='c4c838462fd1c806cab5d44a60a7f5f1f97c1e9d'),
OFile(name='Sample22_hisens.rds', size=616983, hash='8fadbe6da539a385d810036c7bf3f3d50b7cc071'),
OFile(name='Sample22_hisens.seg', size=1256, hash='673c77974d839ccc3464946cb52b5e8726b06a6f'),
OFile(name='Sample22_purity.rds', size=617039, hash='ebe499a84bd8f7425746ed4c17f29260b6a18718'),
OFile(name='Sample22_purity.seg', size=1256, hash='673c77974d839ccc3464946cb52b5e8726b06a6f'),
OFile(name='Sample22.qc.txt', size=1334, hash='9dffb6ce9b710bcd25f664e47af54b532644b00e')]),
ODir(name='Sample25.s_C_Patient25_N001_d', items=[
OFile(name='Sample25.s_C_Patient25_N001_d_hisens.ccf.portal.maf', size=89648628, hash='6006cc0fdc31821292d9dca5281128844ca4b58b'),
OFile(name='Sample25.arm_level.txt', size=1852, hash='9cb1c4584de1dfe10411a481bdea867db00d8582'),
OFile(name='Sample25.txt', size=597, hash='36c9957942bd99e25098c533cc09102c76000c60'),
OFile(name='Sample25.gene_level.txt', size=481755, hash='809c7796a101c0fb4e993a9b3c7d4f84ac8e8a15'),
OFile(name='Sample25_hisens.cncf.txt', size=3852, hash='120dbd0b92153c30abdd46ae5ef353c8c1306a77'),
OFile(name='Sample25_hisens.rds', size=583358, hash='b56336324db262f72cdbb5968ef272da68392df3'),
OFile(name='Sample25_hisens.seg', size=1403, hash='184f5c5f23600a2ed7d999609cac8b333a9a0587'),
OFile(name='Sample25_purity.rds', size=583275, hash='7bb7b780313cf1fe7126f3246c2f51c998e224f0'),
OFile(name='Sample25_purity.seg', size=1302, hash='6b6d5c266e47c84cab638f4c8345fe9c78ec5825'),
OFile(name='Sample25.qc.txt', size=1328, hash='0613673c776fc4ede4a63e33c9e5193e1c603fa7')])],
dir=output_dir),
'facets_failed_pairs': [],
'portal_dir': ODir(name='portal', items=[
OFile(name='meta_clinical_sample.txt', size=135, hash='eab82493f207bd3b7ae6a71bec253ede9371e160'),
OFile(name='data_clinical_patient.txt', size=492, hash='056fe0afc68169191c0981faa9c103a73d0cd2c8'),
OFile(name='data_clinical_sample.txt', size=6397, hash='99309416dfb2aa14818e9dbda138d2c4a035c829'),
OFile(name='meta_study.txt', size=138, hash='3103ac7f24c557ec35ef3692e3cdb166427a1590'),
OFile(name='meta_clinical_patient.txt', size=137, hash='7c7ba5be461f46f9b4728025717beb4b4ceb9482'),
OFile(name='meta_CNA.txt', size=265, hash='53963142b01fb5e1ae2c92feeff39e0027559fb1'),
OFile(name='meta_fusions.txt', size=222, hash='fec37f17f5adc2a5861b3c382f5f01d810c67145'),
OFile(name='meta_mutations_extended.txt', size=265, hash='cbd9bf1d92c587887f9f823ad799de00ce28b152'),
OFile(name='11089_G_meta_cna_hg19_seg.txt', size=190, hash='03acd909d48042090e5e941335b4756b30133841'),
OFile(name='data_CNA.txt', size=140732, hash='5b0f504d0fe9117841407864e3167008f5713e7e'),
OFile(name='data_CNA.ascna.txt', size=227182, hash='61b435a25a2df0e47b65709e197757da1662f67d'),
OFile(name='data_mutations_extended.txt', size=49008, hash='6cffa32a45655147c86de5aacd95a4f9f807cbc0'),
OFile(name='11089_G_data_cna_hg19.seg', size=69171, hash='7d13e1422b9d7112e60f9ab748d524d7446d1dde'),
OFile(name='data_fusions.txt', size=406, hash='4c9e29ead2ddd262dc3877dcc563c6c1d5c624ad'),
ODir(name='case_lists', items=[
OFile(name='cases_all.txt', size=448, hash='da1d6dce1a3d9694bfb74bb99b1cda1766531164'),
OFile(name='cases_cnaseq.txt', size=528, hash='0bf89afc7d8409185288c8bdee45ffb07daa4b08'),
OFile(name='cases_cna.txt', size=460, hash='dfc9325922ceef49a427a61362366507b6331948'),
OFile(name='cases_sequenced.txt', size=473, hash='6aa2ba1b519020ada95acb77b0900be172f306ff')]),
OFile(name='report.html', size=1026290, hash='8c70ab473d323df777c86d330d6e064eaf580cd6')],
dir=output_dir)
}
self.maxDiff = None
self.assertCWLDictEqual(output_json, expected_output)
self.assertNumMutations(os.path.join(output_dir, 'analysis', '11089_G.muts.maf'), 34)
self.assertNumMutations(os.path.join(output_dir, 'portal', 'data_mutations_extended.txt'), 27)
self.assertSampleValues(
os.path.join(output_dir, 'portal/data_clinical_sample.txt'),
value_fieldname = "CMO_TMB_SCORE",
expected_values = {
'Sample46': 'NA', 'Sample44': 'NA', 'Sample80': 'NA', 'Sample20': 'NA', 'Sample38': 'NA', 'Sample26': 'NA', 'Sample94': 'NA', 'Sample48': 'NA', 'Sample68': 'NA', 'Sample90': 'NA', 'Sample18': 'NA', 'Sample54': 'NA', 'Sample52': 'NA', 'Sample86': 'NA', 'Sample30': 'NA', 'Sample78': 'NA', 'Sample84': 'NA', 'Sample82': 'NA', 'Sample6': 'NA', 'Sample96': 'NA', 'Sample72': 'NA', 'Sample56': 'NA', 'Sample64': 'NA', 'Sample58': 'NA', 'Sample92': 'NA', 'Sample62': 'NA', 'Sample8': 'NA', 'Sample24': 'NA', 'Sample12': 'NA', 'Sample16': 'NA', 'Sample88': 'NA', 'Sample22': 'NA', 'Sample42': 'NA', 'Sample76': 'NA', 'Sample28': 'NA', 'Sample74': 'NA', 'Sample50': 'NA', 'Sample60': 'NA', 'Sample10': 'NA', 'Sample36': 'NA', 'Sample34': 'NA', 'Sample40': 'NA', 'Sample66': 'NA', 'Sample14': 'NA', 'Sample32': 'NA', 'Sample70': 'NA', 'Sample4': '5.5', 'Sample1': '47.5'
})
def test_with_mixed_mafs(self):
"""
Test that the workflow produces expected output when both Argos maf files and Facets Suite maf files are used in the workflow
"""
# use reduced file for only these sample pairs
# Sample45 Sample46
# Sample43 Sample44
data_clinical_file = os.path.join(DATA_SETS['Proj_1']['INPUTS_DIR'], "Proj_1_sample_data_clinical.2.txt")
maf_file1 = os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample46.Sample45.muts.maf")
maf_file2 = os.path.join(DATA_SETS['Proj_1']['FACETS_SUITE_DIR'], "Sample44.Sample43_hisens.ccf.portal.maf")
self.input = {
"project_id": "Proj_1",
"project_name": "Proj_1",
"project_short_name": "Proj_1",
"project_description": "project",
"project_pi": "Dr. Jones",
"request_pi": "Dr. Franklin",
"is_impact": True,
"argos_version_string": "2.x",
"cancer_type": "MEL",
"cancer_study_identifier": 'Proj_1',
"cbio_meta_cna_segments_filename": "Proj_1_meta_cna_hg19_seg.txt",
"cbio_segment_data_filename": "Proj_1_data_cna_hg19.seg",
"helix_filter_version": "20.06.1",
"data_clinical_file": {
"path": data_clinical_file,
"class": "File"
},
"targets_list": {
"path": DATA_SETS['Proj_1']["targets_list"],
"class": "File"
},
"known_fusions_file": {
"path": KNOWN_FUSIONS_FILE,
"class": "File"
},
"mutation_maf_files": [
{
"path": maf_file1,
"class": "File"
},
{
"path": maf_file2,
"class": "File"
}
],
"mutation_svs_txt_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample46.Sample45.svs.pass.vep.portal.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample44.Sample43.svs.pass.vep.portal.txt"),
"class": "File"
}
],
"facets_hisens_cncf_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample45.rg.md.abra.printreads__Sample46.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample43.rg.md.abra.printreads__Sample44.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
}
],
"facets_hisens_seg_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample45.rg.md.abra.printreads__Sample46.rg.md.abra.printreads_hisens.seg"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample43.rg.md.abra.printreads__Sample44.rg.md.abra.printreads_hisens.seg"),
"class": "File"
}
]
}
output_json, output_dir = self.run_cwl()
expected_output = {
'portal_case_list_dir': ODir(name='case_lists', items=[
OFile(name='cases_all.txt', size=194, hash='7586b2c5b17984e51c03c7f813f09871348baf75'),
OFile(name='cases_cnaseq.txt', size=274, hash='8f9e091b826c682d6ab3dbf5577ac8af10e52ed8'),
OFile(name='cases_cna.txt', size=206, hash='6a7ad5b8c570f5e0c8d38ce5ad222ea945ad0066'),
OFile(name='cases_sequenced.txt', size=219, hash='12639bb3d01e7e4aa0f94f53a3b8d757e3e6d98f')], dir=output_dir),
'portal_clinical_patient_meta_file': OFile(
name='meta_clinical_patient.txt', size=136, hash='bbfd617bded72d6e9f2071285ac5a7867b0ec6fb', dir=output_dir),
'portal_cna_ascna_file': OFile(
name='data_CNA.ascna.txt', size=8593, hash='b322943e957285327f68c7d6033032af07a47c65', dir=output_dir),
'portal_cna_data_file': OFile(
name='data_CNA.txt', size=6398, hash='b25e5d8ed7cf067448e96db712de542df8d564cd', dir=output_dir),
'portal_data_clinical_patient_file': OFile(
name='data_clinical_patient.txt', size=91, hash='e45f9904b4de2c75fd148798075af9f05848aa27', dir=output_dir),
'portal_data_clinical_sample_file': OFile(
name='data_clinical_sample.txt', size=1015, hash='a53eac2ae9b8861019bc69d40fdef611db83498a', dir=output_dir),
'portal_fusions_data_file': OFile(
name='data_fusions.txt', size=99, hash='c16f763b248813fcdde76f7486f1ddc4e9856038', dir=output_dir),
'portal_hisens_segs': OFile(
name='Proj_1_data_cna_hg19.seg', size=3321, hash='c591f3c35dd53df525c2e31b14942b2e5748e7d3', dir=output_dir),
'portal_meta_clinical_sample_file': OFile(
name='meta_clinical_sample.txt', size=134, hash='29d7eda8ae439aaaa531b2d10fa5c03f943edf11', dir=output_dir),
'portal_meta_cna_file': OFile(
name='meta_CNA.txt', size=264, hash='1123609f24529c407b04b5dbd22efd6a453b3965', dir=output_dir),
'portal_meta_cna_segments_file': OFile(
name='Proj_1_meta_cna_hg19_seg.txt', size=188, hash='c100c7c6cfb7f67f991d356725abea6204e99d6b', dir=output_dir),
'portal_meta_fusions_file': OFile(
name='meta_fusions.txt', size=221, hash='5417138de92de1c35aa123c1e8800d710bb1f7cb', dir=output_dir),
'portal_meta_mutations_extended_file': OFile(
name='meta_mutations_extended.txt', size=264, hash='c1e0524b9ee612710b1921053bdb3f32120831ec', dir=output_dir),
'portal_meta_study_file': OFile(
name='meta_study.txt', size=134, hash='182c7c39315d7ce91cbb8d96f98134d676324cf6', dir=output_dir),
'portal_meta_sv_file': OFile(
name='meta_SV.txt', size=251, hash='8a27777491a88698fba0163e3439206b8cb7db8c', dir=output_dir),
'portal_muts_file': OFile(
name='data_mutations_extended.txt', size=5654, hash='618d3967a262c427a8d6250e5b026d25a4fe04ed', dir=output_dir),
'portal_report': OFile(
name='report.html', size=1012222, hash='e973fac6d2763fe3d2d7eafebaf0856638015d8b', dir=output_dir),
'portal_sv_data_file': OFile(
name='data_SV.txt', size=170, hash='276634dab72db8e7f6a49537345311183986c5fa', dir=output_dir)
}
self.maxDiff = None
strip_related_keys = [
('basename', 'report.html', ['size', 'checksum'])
]
self.assertCWLDictEqual(output_json, expected_output, related_keys = strip_related_keys)
self.assertNumMutations(os.path.join(output_dir, 'data_mutations_extended.txt'), 18)
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.txt'), ['Hugo_Symbol', 'Sample44', 'Sample46'])
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.ascna.txt'), ['Hugo_Symbol', 'Sample44', 'Sample46'])
some_required_colnames = [
"ASCN.TOTAL_COPY_NUMBER",
"ASCN.MINOR_COPY_NUMBER",
"ASCN.EXPECTED_ALT_COPIES",
"ASCN.CCF_EXPECTED_COPIES",
"ASCN.CCF_EXPECTED_COPIES_LOWER",
"ASCN.CCF_EXPECTED_COPIES_UPPER",
"ASCN.ASCN_METHOD",
"ASCN.ASCN_INTEGER_COPY_NUMBER"
]
self.assertMutHeadersContain(os.path.join(output_dir, 'data_mutations_extended.txt'), some_required_colnames)
def test_with_facets_txt_and_facets_mafs(self):
"""
Test that the workflow produces expected output when Facets Suite .txt files are added and annotated .maf files from the Facets Suite workflow are used
Also test that merged CNA files work correctly
"""
lines1 = [
['Hugo_Symbol', 'Sample1', 'Sample2'],
["TAP1", "0", "0"],
["ERRFI1", "0", "0"],
["STK19", "", "0"],
]
cna_file1 = self.write_table(self.tmpdir, filename = "cna1.txt", lines = lines1)
# use reduced file for only these sample pairs
# Sample45 Sample46
# Sample43 Sample44
data_clinical_file = os.path.join(DATA_SETS['Proj_1']['INPUTS_DIR'], "Proj_1_sample_data_clinical.2.txt")
sample_summary_file = os.path.join(DATA_SETS['Proj_1']['QC_DIR'], "Proj_1_SampleSummary.txt")
facets_txt_file1 = os.path.join(DATA_SETS['Proj_1']['FACETS_SUITE_DIR'], 'Sample46.txt')
facets_txt_file1 = os.path.join(DATA_SETS['Proj_1']['FACETS_SUITE_DIR'], 'Sample44.txt')
maf_file1 = os.path.join(DATA_SETS['Proj_1']['FACETS_SUITE_DIR'], "Sample46.Sample45_hisens.ccf.portal.maf")
maf_file2 = os.path.join(DATA_SETS['Proj_1']['FACETS_SUITE_DIR'], "Sample44.Sample43_hisens.ccf.portal.maf")
self.input = {
"project_id": "Proj_1",
"project_name": "Proj_1",
"project_short_name": "Proj_1",
"project_description": "project",
"project_pi": "Dr. Jones",
"request_pi": "Dr. Franklin",
"is_impact": True,
"argos_version_string": "2.x",
"cancer_type": "MEL",
"cancer_study_identifier": 'Proj_1',
"cbio_meta_cna_segments_filename": "Proj_1_meta_cna_hg19_seg.txt",
"cbio_segment_data_filename": "Proj_1_data_cna_hg19.seg",
"helix_filter_version": "20.06.1",
"data_clinical_file": {
"path": data_clinical_file,
"class": "File"
},
"sample_summary_file": {
"path": sample_summary_file,
"class": "File"
},
"targets_list": {
"path": DATA_SETS['Proj_1']["targets_list"],
"class": "File"
},
"known_fusions_file": {
"path": KNOWN_FUSIONS_FILE,
"class": "File"
},
"mutation_maf_files": [
{
"path": maf_file1,
"class": "File"
},
{
"path": maf_file2,
"class": "File"
}
],
"mutation_svs_txt_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample46.Sample45.svs.pass.vep.portal.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample44.Sample43.svs.pass.vep.portal.txt"),
"class": "File"
}
],
"facets_hisens_cncf_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample45.rg.md.abra.printreads__Sample46.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample43.rg.md.abra.printreads__Sample44.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
}
],
"facets_hisens_seg_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample45.rg.md.abra.printreads__Sample46.rg.md.abra.printreads_hisens.seg"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample43.rg.md.abra.printreads__Sample44.rg.md.abra.printreads_hisens.seg"),
"class": "File"
}
],
"facets_suite_txt_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_SUITE_DIR'], "Sample46.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_SUITE_DIR'], "Sample44.txt"),
"class": "File"
},
],
"extra_cna_files": [{"class": "File", "path": cna_file1}]
}
output_json, output_dir = self.run_cwl()
expected_output = {
'portal_case_list_dir': ODir(name='case_lists', items=[
OFile(name='cases_all.txt', size=194, hash='7586b2c5b17984e51c03c7f813f09871348baf75'),
OFile(name='cases_cnaseq.txt', size=274, hash='8f9e091b826c682d6ab3dbf5577ac8af10e52ed8'),
OFile(name='cases_cna.txt', size=206, hash='6a7ad5b8c570f5e0c8d38ce5ad222ea945ad0066'),
OFile(name='cases_sequenced.txt', size=219, hash='12639bb3d01e7e4aa0f94f53a3b8d757e3e6d98f')], dir=output_dir),
'portal_clinical_patient_meta_file': OFile(
name='meta_clinical_patient.txt', size=136, hash='bbfd617bded72d6e9f2071285ac5a7867b0ec6fb', dir=output_dir),
'portal_cna_ascna_file': OFile(
name='data_CNA.ascna.txt', size=8593, hash='b322943e957285327f68c7d6033032af07a47c65', dir=output_dir),
'portal_cna_data_file': OFile(
name='data_CNA.txt', size=9919, hash='ca32a20d522a1ab38816a800608a44b836ca96bf', dir=output_dir),
'portal_data_clinical_patient_file': OFile(
name='data_clinical_patient.txt', size=91, hash='e45f9904b4de2c75fd148798075af9f05848aa27', dir=output_dir),
'portal_data_clinical_sample_file': OFile(
name='data_clinical_sample.txt', size=1366, hash='b8d4e3c53b6bf9407a5d2b1f192fea3d51c020ae', dir=output_dir),
'portal_fusions_data_file': OFile(
name='data_fusions.txt', size=99, hash='c16f763b248813fcdde76f7486f1ddc4e9856038', dir=output_dir),
'portal_hisens_segs': OFile(
name='Proj_1_data_cna_hg19.seg', size=3321, hash='c591f3c35dd53df525c2e31b14942b2e5748e7d3', dir=output_dir),
'portal_meta_clinical_sample_file': OFile(
name='meta_clinical_sample.txt', size=134, hash='29d7eda8ae439aaaa531b2d10fa5c03f943edf11', dir=output_dir),
'portal_meta_cna_file': OFile(
name='meta_CNA.txt', size=264, hash='1123609f24529c407b04b5dbd22efd6a453b3965', dir=output_dir),
'portal_meta_cna_segments_file': OFile(
name='Proj_1_meta_cna_hg19_seg.txt', size=188, hash='c100c7c6cfb7f67f991d356725abea6204e99d6b', dir=output_dir),
'portal_meta_fusions_file': OFile(
name='meta_fusions.txt', size=221, hash='5417138de92de1c35aa123c1e8800d710bb1f7cb', dir=output_dir),
'portal_meta_mutations_extended_file': OFile(
name='meta_mutations_extended.txt', size=264, hash='c1e0524b9ee612710b1921053bdb3f32120831ec', dir=output_dir),
'portal_meta_study_file': OFile(
name='meta_study.txt', size=134, hash='182c7c39315d7ce91cbb8d96f98134d676324cf6', dir=output_dir),
'portal_meta_sv_file': OFile(
name='meta_SV.txt', size=251, hash='8a27777491a88698fba0163e3439206b8cb7db8c', dir=output_dir),
'portal_muts_file': OFile(
name='data_mutations_extended.txt', size=5524, hash='2f79d8c7a7692ef85a677035124f83a78a3f9a42', dir=output_dir),
'portal_report': OFile(
name='report.html', size=1012302, hash='55da8083f3a82aac9f5fe0e90d8a7e7c9800ffe5', dir=output_dir),
'portal_sv_data_file': OFile(
name='data_SV.txt', size=170, hash='276634dab72db8e7f6a49537345311183986c5fa', dir=output_dir)
}
self.maxDiff = None
strip_related_keys = [
('basename', 'report.html', ['size', 'checksum'])
]
self.assertCWLDictEqual(output_json, expected_output, related_keys = strip_related_keys)
self.assertNumMutations(os.path.join(output_dir, 'data_mutations_extended.txt'), 18)
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.txt'), ['Hugo_Symbol', 'Sample44', 'Sample46', 'Sample1', 'Sample2'])
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.ascna.txt'), ['Hugo_Symbol', 'Sample44', 'Sample46'])
with open(os.path.join(output_dir, 'data_clinical_sample.txt')) as fin:
lines = [ line.strip().split('\t') for line in fin ]
expected_lines = [
['#SAMPLE_ID', 'IGO_ID', 'PATIENT_ID', 'COLLAB_ID', 'SAMPLE_TYPE', 'SAMPLE_CLASS', 'GENE_PANEL', 'ONCOTREE_CODE', 'SPECIMEN_PRESERVATION_TYPE', 'TISSUE_SITE', 'REQUEST_ID', 'PROJECT_ID', 'PIPELINE', 'PIPELINE_VERSION', 'SAMPLE_COVERAGE', 'PROJECT_PI', 'REQUEST_PI', 'genome_doubled', 'ASCN_PURITY', 'ASCN_PLOIDY', 'ASCN_VERSION', 'ASCN_WGD'],
['#SAMPLE_ID', 'IGO_ID', 'PATIENT_ID', 'COLLAB_ID', 'SAMPLE_TYPE', 'SAMPLE_CLASS', 'GENE_PANEL', 'ONCOTREE_CODE', 'SPECIMEN_PRESERVATION_TYPE', 'TISSUE_SITE', 'REQUEST_ID', 'PROJECT_ID', 'PIPELINE', 'PIPELINE_VERSION', 'SAMPLE_COVERAGE', 'PROJECT_PI', 'REQUEST_PI', 'genome_doubled', 'ASCN_PURITY', 'ASCN_PLOIDY', 'ASCN_VERSION', 'ASCN_WGD'],
['#STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'STRING', 'NUMBER', 'STRING', 'STRING', 'STRING', 'NUMBER', 'NUMBER', 'STRING', 'STRING'],
['#1', '1', '1', '0', '1', '1', '1', '1', '1', '1', '1', '1', '1', '1', '1', '1', '1', '0', '1', '1', '0', '1'],
['SAMPLE_ID', 'IGO_ID', 'PATIENT_ID', 'COLLAB_ID', 'SAMPLE_TYPE', 'SAMPLE_CLASS', 'GENE_PANEL', 'ONCOTREE_CODE', 'SPECIMEN_PRESERVATION_TYPE', 'TISSUE_SITE', 'REQUEST_ID', 'PROJECT_ID', 'PIPELINE', 'PIPELINE_VERSION', 'SAMPLE_COVERAGE', 'PROJECT_PI', 'REQUEST_PI', 'genome_doubled', 'ASCN_PURITY', 'ASCN_PLOIDY', 'ASCN_VERSION', 'ASCN_WGD'],
['Sample46', '08390_G_95', 'p_C_00001', 'COLLAB-01-T', 'Primary', 'Biopsy', 'IMPACT468+08390_Hg19', 'MEL', 'FFPE', '', '08390_G', '08390', 'roslin', '2.5.7', '108', 'Dr. Jones', 'Dr. Franklin', 'FALSE', '0.36', '2.6', '0.5.14', 'no WGD'],
['Sample44', '08390_G_93', 'p_C_00002', 'COLLAB-01-T', 'Primary', 'Biopsy', 'IMPACT468+08390_Hg19', 'MEL', 'FFPE', '', '08390_G', '08390', 'roslin', '2.5.7', '502', 'Dr. Jones', 'Dr. Franklin', 'FALSE', '0.51', '1.6', '0.5.14', 'no WGD']
]
self.assertEqual(lines, expected_lines)
some_required_colnames = [
"ASCN.TOTAL_COPY_NUMBER",
"ASCN.MINOR_COPY_NUMBER",
"ASCN.EXPECTED_ALT_COPIES",
"ASCN.CCF_EXPECTED_COPIES",
"ASCN.CCF_EXPECTED_COPIES_LOWER",
"ASCN.CCF_EXPECTED_COPIES_UPPER",
"ASCN.ASCN_METHOD",
"ASCN.ASCN_INTEGER_COPY_NUMBER"
]
self.assertMutHeadersContain(os.path.join(output_dir, 'data_mutations_extended.txt'), some_required_colnames)
def test_run_worflow_two_mafs(self):
"""
Test that the workflow works correctly when run with two maf files
"""
data_clinical_file = os.path.join(DATA_SETS['Proj_1']['INPUTS_DIR'], "Proj_1_sample_data_clinical.txt")
sample_summary_file = os.path.join(DATA_SETS['Proj_1']['QC_DIR'], "Proj_1_SampleSummary.txt")
self.input = {
"project_id": "Proj_1",
"project_name": "Proj_1",
"project_short_name": "Proj_1",
"project_description": "project",
"project_pi": "Dr. Jones",
"request_pi": "Dr. Franklin",
"is_impact": True,
"argos_version_string": "2.x",
"cancer_type": "MEL",
"cancer_study_identifier": 'Proj_1',
"cbio_meta_cna_segments_filename": "Proj_1_meta_cna_hg19_seg.txt",
"cbio_segment_data_filename": "Proj_1_data_cna_hg19.seg",
"helix_filter_version": "20.06.1",
"data_clinical_file": {
"path": data_clinical_file,
"class": "File"
},
"sample_summary_file": {
"path": sample_summary_file,
"class": "File"
},
"targets_list": {
"path": DATA_SETS['Proj_1']["targets_list"],
"class": "File"
},
"known_fusions_file": {
"path": KNOWN_FUSIONS_FILE,
"class": "File"
},
"mutation_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample1.Sample2.muts.maf"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample4.Sample3.muts.maf"),
"class": "File"
}
],
"mutation_svs_txt_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample1.Sample2.svs.pass.vep.portal.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample4.Sample3.svs.pass.vep.portal.txt"),
"class": "File"
}
],
"facets_hisens_cncf_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
}
],
"facets_hisens_seg_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.seg"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.seg"),
"class": "File"
}
]
}
output_json, output_dir = self.run_cwl()
expected_output = {
'portal_case_list_dir': ODir(name='case_lists', items=[
OFile(name='cases_all.txt', size=604, hash='ea3652e9b46e60fc2f9851664d22cc69cf3da088'),
OFile(name='cases_cnaseq.txt', size=684, hash='ead904e8ab6753499f2980b09a0187ef3a55d0cc'),
OFile(name='cases_cna.txt', size=616, hash='063f74e183e039854a86814be666ea4f74d3ce6d'),
OFile(name='cases_sequenced.txt', size=629, hash='a7bad4f55be39c46549a0cec4a1c5b73db3ae0d5')], dir=output_dir),
'portal_clinical_patient_meta_file': OFile(
name='meta_clinical_patient.txt', size=136, hash='bbfd617bded72d6e9f2071285ac5a7867b0ec6fb', dir=output_dir),
'portal_cna_ascna_file': OFile(
name='data_CNA.ascna.txt', size=8769, hash='a6e509cd86a412ba398e3b756f468907dc92ae34', dir=output_dir),
'portal_cna_data_file': OFile(
name='data_CNA.txt', size=6764, hash='dd0e1181f412ddb30b4de4738f5b737e18a552be', dir=output_dir),
'portal_data_clinical_patient_file': OFile(
name='data_clinical_patient.txt', size=643, hash='9417dcabddd6ab2cbe98167bccd9b9e4fa182562', dir=output_dir),
'portal_data_clinical_sample_file': OFile(
name='data_clinical_sample.txt', size=7592, hash='2a0c59593fa7726743b2fe46db9d955dbc625453', dir=output_dir),
'portal_fusions_data_file': OFile(
name='data_fusions.txt', size=99, hash='c16f763b248813fcdde76f7486f1ddc4e9856038', dir=output_dir),
'portal_hisens_segs': OFile(
name='Proj_1_data_cna_hg19.seg', size=2571, hash='d93de81ab61012dcfa4cd9af0e2696b63ed26928', dir=output_dir),
'portal_meta_clinical_sample_file': OFile(
name='meta_clinical_sample.txt', size=134, hash='29d7eda8ae439aaaa531b2d10fa5c03f943edf11', dir=output_dir),
'portal_meta_cna_file': OFile(
name='meta_CNA.txt', size=264, hash='1123609f24529c407b04b5dbd22efd6a453b3965', dir=output_dir),
'portal_meta_cna_segments_file': OFile(
name='Proj_1_meta_cna_hg19_seg.txt', size=188, hash='c100c7c6cfb7f67f991d356725abea6204e99d6b', dir=output_dir),
'portal_meta_fusions_file': OFile(
name='meta_fusions.txt', size=221, hash='5417138de92de1c35aa123c1e8800d710bb1f7cb', dir=output_dir),
'portal_meta_mutations_extended_file': OFile(
name='meta_mutations_extended.txt', size=264, hash='c1e0524b9ee612710b1921053bdb3f32120831ec', dir=output_dir),
'portal_meta_study_file': OFile(
name='meta_study.txt', size=134, hash='182c7c39315d7ce91cbb8d96f98134d676324cf6', dir=output_dir),
'portal_meta_sv_file': OFile(
name='meta_SV.txt', size=251, hash='8a27777491a88698fba0163e3439206b8cb7db8c', dir=output_dir),
'portal_muts_file': OFile(
name='data_mutations_extended.txt', size=6971, hash='3d96c94c3217272d65f40350202a2c1508d3a79b', dir=output_dir),
'portal_report': OFile(
name='report.html', size=1016698, hash='b71520700964c22eec0a0700bbe95018b2bf7bec', dir=output_dir),
'portal_sv_data_file': OFile(
name='data_SV.txt', size=170, hash='276634dab72db8e7f6a49537345311183986c5fa', dir=output_dir)
}
self.maxDiff = None
strip_related_keys = [
('basename', 'report.html', ['size', 'checksum'])
]
self.assertCWLDictEqual(output_json, expected_output, related_keys = strip_related_keys)
self.assertNumMutations(os.path.join(output_dir, 'data_mutations_extended.txt'), 27)
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.txt'), ['Hugo_Symbol', 'Sample1', 'Sample4'])
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.ascna.txt'), ['Hugo_Symbol', 'Sample1', 'Sample4'])
def test_run_worflow_one_maf(self):
"""
Test that the workflow works correctly when run with a single maf
"""
data_clinical_file = os.path.join(DATA_SETS['Proj_1']['INPUTS_DIR'], "Proj_1_sample_data_clinical.txt")
sample_summary_file = os.path.join(DATA_SETS['Proj_1']['QC_DIR'], "Proj_1_SampleSummary.txt")
self.input = {
"project_id": "Proj_1",
"project_name": "Proj_1",
"project_short_name": "Proj_1",
"project_description": "project",
"project_pi": "Dr. Jones",
"request_pi": "Dr. Franklin",
"is_impact": True,
"argos_version_string": "2.x",
"cancer_type": "MEL",
"cancer_study_identifier": 'Proj_1',
"cbio_meta_cna_segments_filename": "Proj_1_meta_cna_hg19_seg.txt",
"cbio_segment_data_filename": "Proj_1_data_cna_hg19.seg",
"helix_filter_version": "20.06.1",
"data_clinical_file": {
"path": data_clinical_file,
"class": "File"
},
"sample_summary_file": {
"path": sample_summary_file,
"class": "File"
},
"targets_list": {
"path": DATA_SETS['Proj_1']["targets_list"],
"class": "File"
},
"known_fusions_file": {
"path": KNOWN_FUSIONS_FILE,
"class": "File"
},
"mutation_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample1.Sample2.muts.maf"),
"class": "File"
}
],
"mutation_svs_txt_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['MAF_DIR'], "Sample1.Sample2.svs.pass.vep.portal.txt"),
"class": "File"
}
],
"facets_hisens_cncf_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
}
],
"facets_hisens_seg_files": [
{
"path": os.path.join(DATA_SETS['Proj_1']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.seg"),
"class": "File"
}
],
}
output_json, output_dir = self.run_cwl()
expected_output = {
'portal_case_list_dir': ODir(name='case_lists', items=[
OFile(name='cases_all.txt', size=604, hash='ea3652e9b46e60fc2f9851664d22cc69cf3da088'),
OFile(name='cases_cnaseq.txt', size=684, hash='ead904e8ab6753499f2980b09a0187ef3a55d0cc'),
OFile(name='cases_cna.txt', size=616, hash='063f74e183e039854a86814be666ea4f74d3ce6d'),
OFile(name='cases_sequenced.txt', size=629, hash='a7bad4f55be39c46549a0cec4a1c5b73db3ae0d5')], dir=output_dir),
'portal_clinical_patient_meta_file': OFile(
name='meta_clinical_patient.txt', size=136, hash='bbfd617bded72d6e9f2071285ac5a7867b0ec6fb', dir=output_dir),
'portal_cna_ascna_file': OFile(
name='data_CNA.ascna.txt', size=6154, hash='e06f41b3ad538740519cec581bcbd5cd812e5f00', dir=output_dir),
# NOTE: same as the merged_cna_file file in this case
'portal_cna_data_file': OFile(
name='data_CNA.txt', size=5355, hash='c1682f09406478fc404e40758b0c5e9c47dce5cb', dir=output_dir),
'portal_data_clinical_patient_file': OFile(
name='data_clinical_patient.txt', size=643, hash='9417dcabddd6ab2cbe98167bccd9b9e4fa182562', dir=output_dir),
'portal_data_clinical_sample_file': OFile(
name='data_clinical_sample.txt', size=7592, hash='2a0c59593fa7726743b2fe46db9d955dbc625453', dir=output_dir),
'portal_fusions_data_file': OFile(
name='data_fusions.txt', size=99, hash='c16f763b248813fcdde76f7486f1ddc4e9856038', dir=output_dir),
'portal_hisens_segs': OFile(
name='Proj_1_data_cna_hg19.seg', size=1322, hash='cae32a187d973441dd6e554e07ae81bebecb8980', dir=output_dir),
'portal_meta_clinical_sample_file': OFile(
name='meta_clinical_sample.txt', size=134, hash='29d7eda8ae439aaaa531b2d10fa5c03f943edf11', dir=output_dir),
'portal_meta_cna_file': OFile(
name='meta_CNA.txt', size=264, hash='1123609f24529c407b04b5dbd22efd6a453b3965', dir=output_dir),
'portal_meta_cna_segments_file': OFile(
name='Proj_1_meta_cna_hg19_seg.txt', size=188, hash='c100c7c6cfb7f67f991d356725abea6204e99d6b', dir=output_dir),
'portal_meta_fusions_file': OFile(
name='meta_fusions.txt', size=221, hash='5417138de92de1c35aa123c1e8800d710bb1f7cb', dir=output_dir),
'portal_meta_sv_file': OFile(
name='meta_SV.txt', size=251, hash='8a27777491a88698fba0163e3439206b8cb7db8c', dir=output_dir),
'portal_meta_mutations_extended_file': OFile(
name='meta_mutations_extended.txt', size=264, hash='c1e0524b9ee612710b1921053bdb3f32120831ec', dir=output_dir),
'portal_meta_study_file': OFile(
name='meta_study.txt', size=134, hash='182c7c39315d7ce91cbb8d96f98134d676324cf6', dir=output_dir),
'portal_muts_file': OFile(
name='data_mutations_extended.txt', size=4748, hash='42cf23ff6003692c0c5e00dd60b6741f3d5a4d4f', dir=output_dir),
'portal_report': OFile(
name='report.html', size=1016472, hash='4be1f9395bb83330dcffaecf76def4456db99a62', dir=output_dir),
'portal_sv_data_file': OFile(
name='data_SV.txt', size=170, hash='276634dab72db8e7f6a49537345311183986c5fa', dir=output_dir),
}
self.maxDiff = None
strip_related_keys = [
('basename', 'report.html', ['size', 'checksum'])
]
self.assertCWLDictEqual(output_json, expected_output, related_keys = strip_related_keys)
self.assertNumMutations(os.path.join(output_dir, 'data_mutations_extended.txt'), 17)
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.txt'), ['Hugo_Symbol', 'Sample1'])
self.assertHeaderEquals(os.path.join(output_dir, 'data_CNA.ascna.txt'), ['Hugo_Symbol', 'Sample1'])
self.assertNumMutations(os.path.join(output_dir, 'data_CNA.txt'), 586)
def test_run_worflow_two_mafs(self):
"""
Test that the workflow works correctly when run with two maf files
"""
self.skipTest("Fix jenkins error")
data_clinical_file = os.path.join(
DATA_SETS['Proj_08390_G']['INPUTS_DIR'],
"Proj_08390_G_sample_data_clinical.txt")
sample_summary_file = os.path.join(DATA_SETS['Proj_08390_G']['QC_DIR'],
"Proj_08390_G_SampleSummary.txt")
self.input = {
"project_id":
"Proj_08390_G",
"project_name":
"Proj_08390_G",
"project_short_name":
"Proj_08390_G",
"project_description":
"project",
"project_pi":
"Dr. Jones",
"request_pi":
"Dr. Franklin",
"is_impact":
True,
"argos_version_string":
"2.x",
"cancer_type":
"MEL",
"cancer_study_identifier":
'Proj_08390_G',
"analysis_gene_cna_filename":
"Proj_08390_G.gene.cna.txt",
"analysis_mutations_filename":
"Proj_08390_G.muts.maf",
"analysis_mutations_share_filename":
"Proj_08390_G.muts.share.maf",
"analysis_segment_cna_filename":
"Proj_08390_G.seg.cna.txt",
"analysis_sv_filename":
"Proj_08390_G.svs.maf",
"cbio_meta_cna_segments_filename":
"Proj_08390_G_meta_cna_hg19_seg.txt",
"cbio_segment_data_filename":
"Proj_08390_G_data_cna_hg19.seg",
"helix_filter_version":
"20.06.1",
'IMPACT_gene_list': {
"path": IMPACT_FILE,
"class": "File"
},
"data_clinical_file": {
"path": data_clinical_file,
"class": "File"
},
"sample_summary_file": {
"path": sample_summary_file,
"class": "File"
},
"targets_list": {
"path": DATA_SETS['Proj_08390_G']["targets_list"],
"class": "File"
},
"known_fusions_file": {
"path": KNOWN_FUSIONS_FILE,
"class": "File"
},
"mutation_maf_files": [{
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample1.Sample2.muts.maf"),
"class":
"File"
}, {
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample4.Sample3.muts.maf"),
"class":
"File"
}],
"mutation_svs_txt_files": [{
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample1.Sample2.svs.pass.vep.portal.txt"),
"class":
"File"
}, {
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample4.Sample3.svs.pass.vep.portal.txt"),
"class":
"File"
}],
"mutation_svs_maf_files": [{
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample1.Sample2.svs.pass.vep.maf"),
"class":
"File"
}, {
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample4.Sample3.svs.pass.vep.maf"),
"class":
"File"
}],
"facets_hisens_cncf_files": [{
"path":
os.path.join(
DATA_SETS['Proj_08390_G']['FACETS_DIR'],
"Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.cncf.txt"
),
"class":
"File"
}, {
"path":
os.path.join(
DATA_SETS['Proj_08390_G']['FACETS_DIR'],
"Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.cncf.txt"
),
"class":
"File"
}],
"facets_hisens_seg_files": [{
"path":
os.path.join(
DATA_SETS['Proj_08390_G']['FACETS_DIR'],
"Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.seg"
),
"class":
"File"
}, {
"path":
os.path.join(
DATA_SETS['Proj_08390_G']['FACETS_DIR'],
"Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.seg"
),
"class":
"File"
}]
}
output_json, output_dir = self.run_cwl()
self.maxDiff = None
expected_output = {
'analysis_dir':
ODir(name='analysis',
items=[
OFile(name='Proj_08390_G.gene.cna.txt',
size=173982,
hash='ab17d587ad5ae0a87fd6c6d4dd2d5d1701208ce9'),
OFile(name='Proj_08390_G.muts.maf',
size=54458,
hash='d4352ee2b702877b84db2b632972ccad2441f3e0'),
OFile(name='Proj_08390_G.muts.share.maf',
size=10956,
hash='086ce6517eae68e47160c8740c5f00d7c3454110'),
OFile(name='Proj_08390_G.seg.cna.txt',
size=3191,
hash='f6a77b280c047a7e2082e3a09e8138f861790d3a'),
OFile(name='Proj_08390_G.svs.maf',
size=35595,
hash='5c2a63fc01980550108e58079a8b689d53c97d8c')
],
dir=output_dir),
'portal_dir':
ODir(
name='portal',
items=[
OFile(name='meta_clinical_sample.txt',
size=140,
hash='4c567d81c3b17a76c324fd3e2f73793a6e804f65'),
OFile(name='data_clinical_patient.txt',
size=643,
hash='9417dcabddd6ab2cbe98167bccd9b9e4fa182562'),
OFile(name='data_clinical_sample.txt',
size=7592,
hash='2a0c59593fa7726743b2fe46db9d955dbc625453'),
OFile(name='meta_study.txt',
size=152,
hash='2b0a5fd1a97329adf7c3b1596c84cd6567059a95'),
OFile(name='meta_clinical_patient.txt',
size=142,
hash='9cdc9a7e44a230c012f48b0236bdcf0bbc7de67f'),
OFile(name='meta_CNA.txt',
size=270,
hash='a9bf16f6a0490b19e611e8814b85f7bf1d52417a'),
OFile(name='meta_fusions.txt',
size=227,
hash='77649e888bafc6a4ed61261d1c46d2f238e1c32b'),
OFile(name='meta_mutations_extended.txt',
size=253,
hash='fd04fcd0129b35bb8b8aaef57b2efa16b8f42e1d'),
OFile(name='Proj_08390_G_meta_cna_hg19_seg.txt',
size=200,
hash='59b54d3cd81acdd9fc21df1dc05a71cebfbfe11e'),
OFile(name='data_CNA.txt',
size=6784,
hash='09b4d944e50ea9d0e7567e04ce55b0f21d281255'),
OFile(name='data_CNA.ascna.txt',
size=8789,
hash='d93ffe83137d9a77e2420b40ab3a2e0a1a5ad069'),
OFile(name='data_mutations_extended.txt',
size=7539,
hash='43469aa0f9125d3dca6217ee02641638c3a92e24'),
OFile(name='Proj_08390_G_data_cna_hg19.seg',
size=3191,
hash='f6a77b280c047a7e2082e3a09e8138f861790d3a'),
OFile(name='data_fusions.txt',
size=99,
hash='c16f763b248813fcdde76f7486f1ddc4e9856038'),
ODir(
name='case_lists',
items=[
OFile(
name='cases_all.txt',
size=616,
hash='b9e43289cec5603b0886b5e8507c8d019387c125'
),
OFile(
name='cases_cnaseq.txt',
size=696,
hash='b87e2da8dce0fddbadec348efe2986519b2a794b'
),
OFile(
name='cases_cna.txt',
size=628,
hash='053481a8299e9430117f8e45e081aa7ec21033a6'
),
OFile(
name='cases_sequenced.txt',
size=641,
hash='ef9f5aef03c2527bf576470168660557ca1c7cc9'
)
])
],
dir=output_dir)
}
self.assertCWLDictEqual(output_json, expected_output)
comments, mutations = load_mutations(
os.path.join(output_dir, 'analysis', 'Proj_08390_G.muts.maf'))
self.assertEqual(len(mutations), 34)
comments, mutations = load_mutations(
os.path.join(output_dir, 'portal', 'data_mutations_extended.txt'))
self.assertEqual(len(mutations), 27)
# TODO: fix the Facets column headers so that this passes
# load the data_CNA.txt file
path = os.path.join(output_dir, 'portal/data_CNA.txt'
) # renamed from the data_CNA.scna.txt file ...
with open(path) as f:
header = next(f)
header_parts = header.split()
expected_header_parts = [
'Hugo_Symbol', 's_C_VJ7F47_P001_d', 's_C_X50T9Y_P001_d'
]
self.assertEqual(header_parts, expected_header_parts)
path = os.path.join(output_dir, 'portal/data_CNA.ascna.txt')
with open(path) as f:
header = next(f)
header_parts = header.split()
expected_header_parts = [
'Hugo_Symbol', 's_C_VJ7F47_P001_d', 's_C_X50T9Y_P001_d'
]
self.assertEqual(header_parts, expected_header_parts)
def test_run_worflow_one_maf(self):
"""
Test that the workflow works correctly when run with a single maf
"""
self.skipTest("Fix jenkins error")
data_clinical_file = os.path.join(
DATA_SETS['Proj_08390_G']['INPUTS_DIR'],
"Proj_08390_G_sample_data_clinical.txt")
sample_summary_file = os.path.join(DATA_SETS['Proj_08390_G']['QC_DIR'],
"Proj_08390_G_SampleSummary.txt")
self.input = {
"project_id":
"Proj_08390_G",
"project_name":
"Proj_08390_G",
"project_short_name":
"Proj_08390_G",
"project_description":
"project",
"project_pi":
"Dr. Jones",
"request_pi":
"Dr. Franklin",
"is_impact":
True,
"argos_version_string":
"2.x",
"cancer_type":
"MEL",
"cancer_study_identifier":
'Proj_08390_G',
"analysis_gene_cna_filename":
"Proj_08390_G.gene.cna.txt",
"analysis_mutations_filename":
"Proj_08390_G.muts.maf",
"analysis_mutations_share_filename":
"Proj_08390_G.muts.share.maf",
"analysis_segment_cna_filename":
"Proj_08390_G.seg.cna.txt",
"analysis_sv_filename":
"Proj_08390_G.svs.maf",
"cbio_meta_cna_segments_filename":
"Proj_08390_G_meta_cna_hg19_seg.txt",
"cbio_segment_data_filename":
"Proj_08390_G_data_cna_hg19.seg",
"helix_filter_version":
"20.06.1",
'IMPACT_gene_list': {
"path": IMPACT_FILE,
"class": "File"
},
"data_clinical_file": {
"path": data_clinical_file,
"class": "File"
},
"sample_summary_file": {
"path": sample_summary_file,
"class": "File"
},
"targets_list": {
"path": DATA_SETS['Proj_08390_G']["targets_list"],
"class": "File"
},
"known_fusions_file": {
"path": KNOWN_FUSIONS_FILE,
"class": "File"
},
"mutation_maf_files": [{
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample1.Sample2.muts.maf"),
"class":
"File"
}],
"mutation_svs_txt_files": [{
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample1.Sample2.svs.pass.vep.portal.txt"),
"class":
"File"
}],
"mutation_svs_maf_files": [{
"path":
os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'],
"Sample1.Sample2.svs.pass.vep.maf"),
"class":
"File"
}],
"facets_hisens_cncf_files": [{
"path":
os.path.join(
DATA_SETS['Proj_08390_G']['FACETS_DIR'],
"Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.cncf.txt"
),
"class":
"File"
}],
"facets_hisens_seg_files": [{
"path":
os.path.join(
DATA_SETS['Proj_08390_G']['FACETS_DIR'],
"Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.seg"
),
"class":
"File"
}],
}
output_json, output_dir = self.run_cwl()
expected_output = {
'analysis_dir':
ODir(name='analysis',
items=[
OFile(name='Proj_08390_G.gene.cna.txt',
size=87905,
hash='7cc89d24556de93b9a409812317581e67e5df494'),
OFile(name='Proj_08390_G.muts.maf',
size=33243,
hash='2c8904927a917d6e935ef207582d995680574d16'),
OFile(name='Proj_08390_G.muts.share.maf',
size=7462,
hash='b5af4e0fcd89fecabf8095aa3d7690e5edb8dca1'),
OFile(name='Proj_08390_G.seg.cna.txt',
size=1632,
hash='f0ebb82c34b6530447fa1e70b6dedcc039840d61'),
OFile(name='Proj_08390_G.svs.maf',
size=23603,
hash='df420706bb5b772a79317843c0a01a3c88a9571d')
],
dir=output_dir),
'portal_dir':
ODir(
name='portal',
items=[
OFile(name='meta_clinical_sample.txt',
size=140,
hash='4c567d81c3b17a76c324fd3e2f73793a6e804f65'),
OFile(name='data_clinical_patient.txt',
size=643,
hash='9417dcabddd6ab2cbe98167bccd9b9e4fa182562'),
OFile(name='data_clinical_sample.txt',
size=7592,
hash='2a0c59593fa7726743b2fe46db9d955dbc625453'),
OFile(name='meta_study.txt',
size=152,
hash='2b0a5fd1a97329adf7c3b1596c84cd6567059a95'),
OFile(name='meta_clinical_patient.txt',
size=142,
hash='9cdc9a7e44a230c012f48b0236bdcf0bbc7de67f'),
OFile(name='meta_CNA.txt',
size=270,
hash='a9bf16f6a0490b19e611e8814b85f7bf1d52417a'),
OFile(name='meta_fusions.txt',
size=227,
hash='77649e888bafc6a4ed61261d1c46d2f238e1c32b'),
OFile(name='meta_mutations_extended.txt',
size=253,
hash='fd04fcd0129b35bb8b8aaef57b2efa16b8f42e1d'),
OFile(name='Proj_08390_G_meta_cna_hg19_seg.txt',
size=200,
hash='59b54d3cd81acdd9fc21df1dc05a71cebfbfe11e'),
OFile(name='data_CNA.txt',
size=5365,
hash='931d82412733d7f93dd4117cd955f35e5dcbacc1'),
OFile(name='data_CNA.ascna.txt',
size=6164,
hash='452d5ddef12a44693d5a98a05f5d300801734cfe'),
OFile(name='data_mutations_extended.txt',
size=5106,
hash='e713516cf04750a3e3f1ef932b1c7202d4b75bf2'),
OFile(name='Proj_08390_G_data_cna_hg19.seg',
size=1632,
hash='f0ebb82c34b6530447fa1e70b6dedcc039840d61'),
OFile(name='data_fusions.txt',
size=99,
hash='c16f763b248813fcdde76f7486f1ddc4e9856038'),
ODir(
name='case_lists',
items=[
OFile(
name='cases_all.txt',
size=616,
hash='b9e43289cec5603b0886b5e8507c8d019387c125'
),
OFile(
name='cases_cnaseq.txt',
size=696,
hash='b87e2da8dce0fddbadec348efe2986519b2a794b'
),
OFile(
name='cases_cna.txt',
size=628,
hash='053481a8299e9430117f8e45e081aa7ec21033a6'
),
OFile(
name='cases_sequenced.txt',
size=641,
hash='ef9f5aef03c2527bf576470168660557ca1c7cc9'
)
])
],
dir=output_dir)
}
self.assertCWLDictEqual(output_json, expected_output)
comments, mutations = load_mutations(
os.path.join(output_dir, 'analysis', 'Proj_08390_G.muts.maf'))
self.assertEqual(len(mutations), 22)
comments, mutations = load_mutations(
os.path.join(output_dir, 'portal', 'data_mutations_extended.txt'))
self.assertEqual(len(mutations), 17)
# load the data_CNA.txt file
path = os.path.join(output_dir, 'portal/data_CNA.txt'
) # renamed from the data_CNA.scna.txt file ...
with open(path) as f:
header = next(f)
header_parts = header.split()
expected_header_parts = ['Hugo_Symbol', 's_C_VJ7F47_P001_d']
self.assertEqual(header_parts, expected_header_parts)
path = os.path.join(output_dir, 'portal/data_CNA.ascna.txt')
with open(path) as f:
header = next(f)
header_parts = header.split()
expected_header_parts = ['Hugo_Symbol', 's_C_VJ7F47_P001_d']
self.assertEqual(header_parts, expected_header_parts)
def test_run_worflow_two_mafs(self):
"""
Test that the workflow works correctly when run with two maf files
"""
self.input = {
"is_impact": True,
"argos_version_string": "2.x",
"analysis_gene_cna_filename": "Proj_08390_G.gene.cna.txt",
"analysis_mutations_filename": "Proj_08390_G.muts.maf",
"analysis_mutations_share_filename": "Proj_08390_G.muts.share.maf",
"analysis_segment_cna_filename": "Proj_08390_G.seg.cna.txt",
"analysis_sv_filename": "Proj_08390_G.svs.maf",
"helix_filter_version": "20.06.1",
"IMPACT_gene_list": {
"class": "File",
"path": IMPACT_FILE
},
"targets_list": {
"path": DATA_SETS['Proj_08390_G']["targets_list"],
"class": "File"
},
"mutation_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample1.Sample2.muts.maf"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample4.Sample3.muts.maf"),
"class": "File"
}
],
"mutation_svs_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample1.Sample2.svs.pass.vep.maf"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample4.Sample3.svs.pass.vep.maf"),
"class": "File"
}
],
"facets_hisens_cncf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
}
],
"facets_hisens_seg_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.seg"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.seg"),
"class": "File"
}
]
}
output_json, output_dir = self.run_cwl()
expected_output = {
'analysis_dir': ODir(name='analysis', items=[
OFile(name='Proj_08390_G.gene.cna.txt', size=173982, hash='ab17d587ad5ae0a87fd6c6d4dd2d5d1701208ce9'),
OFile(name='Proj_08390_G.muts.maf', size=54458, hash='d4352ee2b702877b84db2b632972ccad2441f3e0'),
OFile(name='Proj_08390_G.muts.share.maf', size=10956, hash='086ce6517eae68e47160c8740c5f00d7c3454110'),
OFile(name='Proj_08390_G.seg.cna.txt', size=3191, hash='f6a77b280c047a7e2082e3a09e8138f861790d3a'),
OFile(name='Proj_08390_G.svs.maf', size=35595, hash='5c2a63fc01980550108e58079a8b689d53c97d8c')], dir=output_dir)
}
self.assertCWLDictEqual(output_json, expected_output)
self.assertNumMutations(os.path.join(output_dir, 'analysis', 'Proj_08390_G.muts.maf'), 34)
def test_run_worflow_mixed_mafs(self):
"""
Test that the workflow works correctly when run with a mix of Argos muts.maf files and Facets Suite annotated maf files
The Facets Suite maf files have extra columns that need to be retained in the output
"""
self.input = {
"is_impact": True,
"argos_version_string": "2.x",
"analysis_gene_cna_filename": "Proj_08390_G.gene.cna.txt",
"analysis_mutations_filename": "Proj_08390_G.muts.maf",
"analysis_mutations_share_filename": "Proj_08390_G.muts.share.maf",
"analysis_segment_cna_filename": "Proj_08390_G.seg.cna.txt",
"analysis_sv_filename": "Proj_08390_G.svs.maf",
"helix_filter_version": "20.06.1",
"IMPACT_gene_list": {
"class": "File",
"path": IMPACT_FILE
},
"targets_list": {
"path": DATA_SETS['Proj_08390_G']["targets_list"],
"class": "File"
},
"mutation_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample1.Sample2.muts.maf"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_SUITE_DIR'], "Sample4.Sample3_hisens.ccf.portal.maf"),
"class": "File"
}
],
"mutation_svs_maf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample1.Sample2.svs.pass.vep.maf"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['MAF_DIR'], "Sample4.Sample3.svs.pass.vep.maf"),
"class": "File"
}
],
"facets_hisens_cncf_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.cncf.txt"),
"class": "File"
}
],
"facets_hisens_seg_files": [
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample2.rg.md.abra.printreads__Sample1.rg.md.abra.printreads_hisens.seg"),
"class": "File"
},
{
"path": os.path.join(DATA_SETS['Proj_08390_G']['FACETS_DIR'], "Sample3.rg.md.abra.printreads__Sample4.rg.md.abra.printreads_hisens.seg"),
"class": "File"
}
]
}
output_json, output_dir = self.run_cwl()
expected_output = {
'analysis_dir': ODir(name='analysis', items=[
OFile(name='Proj_08390_G.gene.cna.txt', size=173982, hash='ab17d587ad5ae0a87fd6c6d4dd2d5d1701208ce9'),
OFile(name='Proj_08390_G.muts.maf', size=59915, hash='66a87cb8cc2eea31f490852d468bedd958c4ecc5'),
OFile(name='Proj_08390_G.muts.share.maf', size=10729, hash='cbaa23bb848978cde135efd3870db8f35b3f2861'),
OFile(name='Proj_08390_G.seg.cna.txt', size=3191, hash='f6a77b280c047a7e2082e3a09e8138f861790d3a'),
OFile(name='Proj_08390_G.svs.maf', size=35595, hash='5c2a63fc01980550108e58079a8b689d53c97d8c')], dir=output_dir)
}
self.assertCWLDictEqual(output_json, expected_output)
self.assertNumMutations(os.path.join(output_dir, 'analysis', 'Proj_08390_G.muts.maf'), 34)
# colnames = mutations[0].keys()
some_required_colnames = [
"ASCN.TOTAL_COPY_NUMBER",
"ASCN.MINOR_COPY_NUMBER",
"ASCN.EXPECTED_ALT_COPIES",
"ASCN.CCF_EXPECTED_COPIES",
"ASCN.CCF_EXPECTED_COPIES_LOWER",
"ASCN.CCF_EXPECTED_COPIES_UPPER",
"ASCN.ASCN_METHOD",
"ASCN.ASCN_INTEGER_COPY_NUMBER"
]
self.assertMutHeadersContain(os.path.join(output_dir, 'analysis', 'Proj_08390_G.muts.maf'), some_required_colnames)