Пример #1
0
 def setUp(self):
     self.dbconfig = 'data/dbconfig.json'
     self.platform_json = 'data/platform_db_data.json'
     self.seqrun_json = 'data/seqrun_db_data.json'
     self.pipeline_json = 'data/pipeline_data.json'
     dbparam = read_dbconf_json(self.dbconfig)
     base = BaseAdaptor(**dbparam)
     self.engine = base.engine
     self.dbname = dbparam['dbname']
     Base.metadata.create_all(self.engine)
     self.session_class = base.get_session_class()
     base.start_session()
     # load platform data
     pl = PlatformAdaptor(**{'session': base.session})
     pl.store_platform_data(data=read_json_data(self.platform_json))
     # load seqrun data
     sra = SeqrunAdaptor(**{'session': base.session})
     sra.store_seqrun_and_attribute_data(
         data=read_json_data(self.seqrun_json))
     # load platform data
     pla = PipelineAdaptor(**{'session': base.session})
     pla.store_pipeline_data(data=read_json_data(self.pipeline_json))
     pipeline_seed_data = [
         {
             'pipeline_name': 'demultiplexing_fastq',
             'seed_id': '1',
             'seed_table': 'seqrun'
         },
     ]
     pla.create_pipeline_seed(data=pipeline_seed_data)
     base.close_session()
Пример #2
0
 def test_create_pipeline_seed(self):
     pipeline_seed_data1 = [
         {
             'seed_id': '1',
             'seed_table': 'seqrun'
         },
     ]
     pl = PipelineAdaptor(**{'session_class': self.session_class})
     pl.start_session()
     with self.assertRaises(ValueError):
         pl.create_pipeline_seed(data=pipeline_seed_data1)
     pl.close_session()
Пример #3
0
 def setUp(self):
     self.dbconfig = 'data/dbconfig.json'
     dbparam = read_dbconf_json(self.dbconfig)
     base = BaseAdaptor(**dbparam)
     self.engine = base.engine
     self.dbname = dbparam['dbname']
     Base.metadata.create_all(self.engine)
     self.session_class = base.get_session_class()
     base.start_session()
     project_data = [{
         'project_igf_id': 'IGFP0001_test_22-8-2017_rna_sc',
         'project_name': 'test_22-8-2017_rna',
         'description': 'Its project 1',
         'project_deadline': 'Before August 2017',
         'comments': 'Some samples are treated with drug X',
     }]
     pa = ProjectAdaptor(**{'session': base.session})
     pa.store_project_and_attribute_data(data=project_data)
     sample_data = [
         {
             'sample_igf_id': 'IGF00001',
             'project_igf_id': 'IGFP0001_test_22-8-2017_rna_sc',
             'library_source': 'TRANSCRIPTOMIC_SINGLE_CELL',
             'library_strategy': 'RNA-SEQ',
             'experiment_type': 'POLYA-RNA'
         },
         {
             'sample_igf_id': 'IGF00003',
             'project_igf_id': 'IGFP0001_test_22-8-2017_rna_sc',
             'library_source': 'TRANSCRIPTOMIC_SINGLE_CELL',
             'experiment_type': 'POLYA-RNA'
         },
         {
             'sample_igf_id': 'IGF00002',
             'project_igf_id': 'IGFP0001_test_22-8-2017_rna_sc',
         },
     ]
     sa = SampleAdaptor(**{'session': base.session})
     sa.store_sample_and_attribute_data(data=sample_data)
     experiment_data = [
         {
             'project_igf_id': 'IGFP0001_test_22-8-2017_rna_sc',
             'sample_igf_id': 'IGF00001',
             'experiment_igf_id': 'IGF00001_HISEQ4000',
             'library_name': 'IGF00001'
         },
         {
             'project_igf_id': 'IGFP0001_test_22-8-2017_rna_sc',
             'sample_igf_id': 'IGF00003',
             'experiment_igf_id': 'IGF00003_HISEQ4000',
             'library_name': 'IGF00001'
         },
         {
             'project_igf_id': 'IGFP0001_test_22-8-2017_rna_sc',
             'sample_igf_id': 'IGF00002',
             'experiment_igf_id': 'IGF00002_HISEQ4000',
             'library_name': 'IGF00002'
         },
     ]
     ea = ExperimentAdaptor(**{'session': base.session})
     ea.store_project_and_attribute_data(data=experiment_data)
     pipeline_data = [{
         "pipeline_name": "alignment",
         "pipeline_db": "sqlite:////data/aln.db",
         "pipeline_init_conf": {
             "input_dir": "data/fastq_dir/",
             "output_dir": "data"
         },
         "pipeline_run_conf": {
             "output_dir": "data"
         }
     }]
     pl = PipelineAdaptor(**{'session': base.session})
     pl.store_pipeline_data(data=pipeline_data)
     pipeline_seed_data = [
         {
             'pipeline_name': 'alignment',
             'seed_id': '1',
             'seed_table': 'experiment'
         },
     ]
     pl.create_pipeline_seed(data=pipeline_seed_data)
     base.close_session()
Пример #4
0
 def setUp(self):
     self.dbconfig = 'data/dbconfig.json'
     dbparam = read_dbconf_json(self.dbconfig)
     base = BaseAdaptor(**dbparam)
     self.engine = base.engine
     self.dbname = dbparam['dbname']
     Base.metadata.create_all(self.engine)
     self.session_class = base.get_session_class()
     base.start_session()
     platform_data = [{
         "platform_igf_id": "M00001",
         "model_name": "MISEQ",
         "vendor_name": "ILLUMINA",
         "software_name": "RTA",
         "software_version": "RTA1.18.54"
     }, {
         "platform_igf_id": "NB500000",
         "model_name": "NEXTSEQ",
         "vendor_name": "ILLUMINA",
         "software_name": "RTA",
         "software_version": "RTA2"
     }, {
         "platform_igf_id": "K00000",
         "model_name": "HISEQ4000",
         "vendor_name": "ILLUMINA",
         "software_name": "RTA",
         "software_version": "RTA2"
     }]
     flowcell_rule_data = [{
         "platform_igf_id": "K00000",
         "flowcell_type": "HiSeq 3000/4000 SR",
         "index_1": "NO_CHANGE",
         "index_2": "NO_CHANGE"
     }, {
         "platform_igf_id": "K00000",
         "flowcell_type": "HiSeq 3000/4000 PE",
         "index_1": "NO_CHANGE",
         "index_2": "REVCOMP"
     }, {
         "platform_igf_id": "NB500000",
         "flowcell_type": "NEXTSEQ",
         "index_1": "NO_CHANGE",
         "index_2": "REVCOMP"
     }, {
         "platform_igf_id": "M00001",
         "flowcell_type": "MISEQ",
         "index_1": "NO_CHANGE",
         "index_2": "NO_CHANGE"
     }]
     pl = PlatformAdaptor(**{'session': base.session})
     pl.store_platform_data(data=platform_data)
     pl.store_flowcell_barcode_rule(data=flowcell_rule_data)
     seqrun_data = [{
         'seqrun_igf_id': '171003_M00001_0089_000000000-TEST',
         'flowcell_id': '000000000-D0YLK',
         'platform_igf_id': 'M00001',
         'flowcell': 'MISEQ',
     }]
     sra = SeqrunAdaptor(**{'session': base.session})
     sra.store_seqrun_and_attribute_data(data=seqrun_data)
     seqrun = sra.fetch_seqrun_records_igf_id(
         seqrun_igf_id='171003_M00001_0089_000000000-TEST')
     pipeline_data = [{
         "pipeline_name": "demultiplexing_fastq",
         "pipeline_db": "sqlite:////data/bcl2fastq.db",
         "pipeline_init_conf": {
             "input_dir": "data/seqrun_dir/",
             "output_dir": "data"
         },
         "pipeline_run_conf": {
             "output_dir": "data"
         }
     }]
     pipeseed_data = [{
         "pipeline_name": "demultiplexing_fastq",
         "seed_table": "seqrun",
         "seed_id": seqrun.seqrun_id
     }]
     pp = PipelineAdaptor(**{'session': base.session})
     pp.store_pipeline_data(data=pipeline_data)
     pp.create_pipeline_seed(
         data=pipeseed_data,
         required_columns=['pipeline_id', 'seed_id', 'seed_table'])
     base.close_session()
     self.seqrun_input_list = 'data/reset_samplesheet_md5/seqrun_pipeline_reset_list.txt'
     with open(self.seqrun_input_list, 'w') as fp:
         fp.write('')
            'seed_table': 'seqrun'
        },
        {
            'pipeline_name': 'DemultiplexIlluminaFastq',
            'seed_id': 2,
            'seed_table': 'seqrun'
        },
        {
            'pipeline_name': 'DemultiplexIlluminaFastq',
            'seed_id': 3,
            'seed_table': 'seqrun'
        },
    ]
    pla = PipelineAdaptor(**{'session': base.session})
    pla.store_pipeline_data(data=pipeline_data)
    pla.create_pipeline_seed(data=pipeline_seed_data)
    pipeline_data = [{
        "pipeline_name": "PrimaryAnalysis",
        "pipeline_db": "sqlite:////analysis.db",
    }]

    pipeline_seed_data = [{
        'pipeline_name': 'PrimaryAnalysis',
        'seed_id': 1,
        'seed_table': 'experiment'
    }, {
        'pipeline_name': 'PrimaryAnalysis',
        'seed_id': 2,
        'seed_table': 'experiment'
    }, {
        'pipeline_name': 'PrimaryAnalysis',
 def setUp(self):
     self.dbconfig = 'data/dbconfig.json'
     dbparam = read_dbconf_json(self.dbconfig)
     base = BaseAdaptor(**dbparam)
     self.engine = base.engine
     self.dbname = dbparam['dbname']
     Base.metadata.drop_all(self.engine)
     if os.path.exists(self.dbname):
         os.remove(self.dbname)
     Base.metadata.create_all(self.engine)
     self.session_class = base.get_session_class()
     base.start_session()
     # PLATFORM
     platform_data = [{
         "platform_igf_id": "M03291",
         "model_name": "MISEQ",
         "vendor_name": "ILLUMINA",
         "software_name": "RTA",
         "software_version": "RTA1.18.54"
     }]
     flowcell_rule_data = [{
         "platform_igf_id": "M03291",
         "flowcell_type": "MISEQ",
         "index_1": "NO_CHANGE",
         "index_2": "NO_CHANGE"
     }]
     pl = PlatformAdaptor(**{'session': base.session})
     pl.store_platform_data(data=platform_data)
     pl.store_flowcell_barcode_rule(data=flowcell_rule_data)
     # SEQRUN
     seqrun_data = [{
         'seqrun_igf_id': '180416_M03291_0139_000000000-TEST',
         'flowcell_id': '000000000-TEST',
         'platform_igf_id': 'M03291',
         'flowcell': 'MISEQ',
     }, {
         'seqrun_igf_id': '180416_M03291_0140_000000000-TEST',
         'flowcell_id': '000000000-TEST',
         'platform_igf_id': 'M03291',
         'flowcell': 'MISEQ',
     }]
     sra = SeqrunAdaptor(**{'session': base.session})
     sra.store_seqrun_and_attribute_data(data=seqrun_data)
     # PROJECT
     project_data = [{'project_igf_id': 'IGFQ000123_test_10-4-2018_Miseq'}]
     pa = ProjectAdaptor(**{'session': base.session})
     pa.store_project_and_attribute_data(data=project_data)
     # SAMPLE
     sample_data = [{
         'sample_igf_id': 'IGF00123',
         'project_igf_id': 'IGFQ000123_test_10-4-2018_Miseq'
     }, {
         'sample_igf_id': 'IGF00124',
         'project_igf_id': 'IGFQ000123_test_10-4-2018_Miseq'
     }]
     sa = SampleAdaptor(**{'session': base.session})
     sa.store_sample_and_attribute_data(data=sample_data)
     # EXPERIMENT
     experiment_data = [{
         'project_igf_id': 'IGFQ000123_test_10-4-2018_Miseq',
         'sample_igf_id': 'IGF00123',
         'experiment_igf_id': 'IGF00123_MISEQ',
         'library_name': 'IGF00123',
         'library_source': 'TRANSCRIPTOMIC_SINGLE_CELL',
         'library_strategy': 'RNA-SEQ',
         'experiment_type': 'POLYA-RNA',
         'library_layout': 'PAIRED',
         'platform_name': 'MISEQ',
         'singlecell_chemistry': 'TENX'
     }, {
         'project_igf_id': 'IGFQ000123_test_10-4-2018_Miseq',
         'sample_igf_id': 'IGF00124',
         'experiment_igf_id': 'IGF00124_MISEQ',
         'library_name': 'IGF00124',
         'library_source': 'TRANSCRIPTOMIC_SINGLE_CELL',
         'library_strategy': 'RNA-SEQ',
         'experiment_type': 'POLYA-RNA',
         'library_layout': 'PAIRED',
         'platform_name': 'MISEQ',
         'singlecell_chemistry': 'TENX'
     }]
     ea = ExperimentAdaptor(**{'session': base.session})
     ea.store_project_and_attribute_data(data=experiment_data)
     # RUN
     run_data = [{
         'experiment_igf_id': 'IGF00123_MISEQ',
         'seqrun_igf_id': '180416_M03291_0139_000000000-TEST',
         'run_igf_id': 'IGF00123_MISEQ_000000000-TEST_1',
         'lane_number': '1'
     }]
     ra = RunAdaptor(**{'session': base.session})
     ra.store_run_and_attribute_data(data=run_data)
     # PIPELINE
     pipeline_data = [{
         "pipeline_name": "PrimaryAnalysis",
         "pipeline_db": "sqlite:////aln.db",
     }, {
         "pipeline_name": "DemultiplexingFastq",
         "pipeline_db": "sqlite:////fastq.db",
     }]
     pipeline_seed_data = [
         {
             'pipeline_name': 'PrimaryAnalysis',
             'seed_id': 1,
             'seed_table': 'experiment'
         },
         {
             'pipeline_name': 'PrimaryAnalysis',
             'seed_id': 2,
             'seed_table': 'experiment'
         },
         {
             'pipeline_name': 'DemultiplexingFastq',
             'seed_id': 1,
             'seed_table': 'seqrun'
         },
         {
             'pipeline_name': 'DemultiplexingFastq',
             'seed_id': 2,
             'seed_table': 'seqrun'
         },
     ]
     update_data = [{
         'pipeline_name': 'PrimaryAnalysis',
         'seed_id': 2,
         'seed_table': 'experiment',
         'status': 'FINISHED'
     }, {
         'pipeline_name': 'DemultiplexingFastq',
         'seed_id': 2,
         'seed_table': 'seqrun',
         'status': 'FINISHED'
     }]
     pla = PipelineAdaptor(**{'session': base.session})
     pla.store_pipeline_data(data=pipeline_data)
     pla.create_pipeline_seed(data=pipeline_seed_data)
     pla.update_pipeline_seed(update_data)
     base.close_session()