Experimental Data Parsers

clinicalParser.py

parser(projectId)

project_parser(projectId, config, directory, separator)

experimental_design_parser(projectId, config, directory)

clinical_parser(projectId, config, directory, separator)

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(clinical_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_group_rels(clinical_data)

extract_biological_sample_clinical_variables_rels(clinical_data)

proteomicsParser.py

parser(projectId, directory=None)

parse_from_directory(projectId, directory, configuration=None)

parser_from_file(file_path, configuration, data_type, is_standard=True)

get_configuration(processing_tool, data_type)

update_configuration(data_type, processing_tool, value_col='LFQ intensity', columns=[], drop_cols=[], filters=None, new_config={})

parse_dataset(filepath, configuration)

parse_standard_dataset(file_path, configuration)

check_columns(data, req_columns, generated_columns)

check_minimum_configuration(configuration)

load_dataset(uri, configuration)

This function gets the molecular data from a proteomics experiment. Input: uri of the processed file resulting from MQ Output: pandas DataFrame with the columns and filters defined in config.py

remove_contaminant_tag(column, tag='CON__')

expand_groups(data, configuration)

extract_modification_protein_rels(data, configuration)

extract_protein_modification_subject_rels(data, configuration)

extract_protein_protein_modification_rels(data, configuration)

extract_peptide_protein_modification_rels(data, configuration)

extract_protein_modifications_rels(data, configuration)

extract_protein_modifications_modification_rels(data, configuration)

extract_peptides(data, configuration)

extract_peptide_subject_rels(data, configuration)

extract_peptide_protein_rels(data, configuration)

extract_protein_subject_rels(data, configuration)

get_value_cols(data, configuration)

extract_subject_replicates_from_regex(data, regex)

extract_subject_replicates(data, value_cols)

extract_attributes(data, attributes)

merge_regex_attributes(data, attributes, index, regexCols)

merge_col_attributes(data, attributes, index)

calculate_median_replicates(data, log='log2')

update_groups(data, groups)

get_dataset_configuration(processing_format, data_type)

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)