def validate_snv_genotyping(yamldata): tumour_cells = utils.get(yamldata, 'tumour_cells') for sample in tumour_cells: for library in tumour_cells[sample]: utils.check_cells_data(tumour_cells[sample][library]) vcf_files = utils.get(yamldata, 'vcf_files') for sample in vcf_files: for library in vcf_files[sample]: utils.check_data_type(['museq_vcf', 'strelka_snv_vcf'], str, vcf_files[sample][library])
def validate_variant_calling(yamldata): normals = yamldata['normal'] for region in normals: utils.check_data_type(['bam'], str, normals[region]) utils.check_genomic_regions(region) tumours = yamldata['tumour'] for region in tumours: utils.check_data_type(['bam'], str, tumours[region]) utils.check_genomic_regions(region)
def validate_sample_info(yamldata): for cell in yamldata: celldata = yamldata[cell] utils.check_data_type(['column', 'img_col', 'row'], int, celldata) utils.check_data_type(['condition', 'pick_met', 'index_i5', 'index_i7'], str, celldata) utils.check_barcodes(utils.get(celldata, 'primer_i5')) utils.check_barcodes(utils.get(celldata, 'primer_i7')) if not utils.get(celldata, 'index_i5').startswith('i5-'): raise utils.DLPIndexError() if not utils.get(celldata, 'index_i7').startswith('i7-'): raise utils.DLPIndexError()
def validate_count_haps(yamldata): utils.check_cells_data(utils.get(yamldata, 'tumour')) utils.check_data_type(['haplotypes'], str, yamldata)
def validate_split_wgs_bam(yamldata): data = utils.get(yamldata, 'normal') utils.check_data_type(['bam'], str, data)
def validate_annotation(yamldata): utils.check_data_type( ['hmmcopy_metrics', 'hmmcopy_reads', 'alignment_metrics', 'gc_metrics', 'segs_pdf_tar'], str, yamldata )
def validate_hmmcopy_bams(yamldata): for cell, celldata in yamldata.items(): utils.check_data_type(['bam'], str, celldata)
def validate_alignment_fastqs(data): for sample, sample_data in data.items(): for lane, lane_data in sample_data['fastqs'].items(): if not utils.get(lane_data, 'fastq_1') or not utils.get(lane_data, 'fastq_2'): raise utils.MissingInput() utils.check_data_type(['sequencing_center', 'sequencing_instrument'], str, lane_data)