Experimental Data Parsers

clinicalParser.py

parser(projectId, type='clinical')

project_parser(projectId, config, directory)

experimental_design_parser(projectId, config, directory)

clinical_parser(projectId, config, clinical_directory)

parse_dataset(projectId, configuration, dataDir, key='project')

This function parses clinical data from subjects in the project Input: uri of the clinical data file. Format: Subjects as rows, clinical variables as columns Output: pandas DataFrame with the same input format but the clinical variables mapped to the right ontology (defined in config), i.e. type = -40 -> SNOMED CT

extract_project_info(project_data)

extract_responsible_rels(project_data, separator='|')

extract_participant_rels(project_data, separator='|')

extract_project_tissue_rels(project_data, separator='|')

extract_project_disease_rels(project_data, separator='|')

extract_project_intervention_rels(project_data, separator='|')

extract_project_rels(project_data, separator='|')

extract_timepoints(project_data, separator='|')

extract_project_subject_rels(projectId, design_data)

extract_subject_identifiers(design_data)

extract_biosample_identifiers(design_data)

extract_analytical_sample_identifiers(design_data)

extract_biological_sample_subject_rels(design_data)

extract_biological_sample_analytical_sample_rels(design_data)

extract_biological_samples_info(clinical_data)

extract_analytical_samples_info(data)

extract_biosample_analytical_sample_relationship_attributes(clinical_data)

extract_biological_sample_timepoint_rels(clinical_data)

extract_biological_sample_tissue_rels(clinical_data)

extract_subject_disease_rels(clinical_data, separator='|')

extract_subject_intervention_rels(clinical_data, separator='|')

extract_biological_sample_clinical_variables_rels(clinical_data)

proteomicsParser.py

wesParser.py

parser(projectId)

parseWESDataset(projectId, configuration, dataDir)

loadWESDataset(uri, configuration)

This function gets the molecular data from a Whole Exome Sequencing experiment. Input: uri of the processed file resulting from the WES analysis pipeline. The resulting Annovar annotated VCF file from Mutect (sampleID_mutect_annovar.vcf) Output: pandas DataFrame with the columns and filters defined in config.py

extractWESRelationships(data, configuration)