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)