def _calculate_sv_coverage_gatk(data, work_dir):
"""Calculate coverage in defined regions using GATK tools
TODO: This does double calculations to get GATK4 compatible HDF read counts
and then depth and gene annotations. Both are needed for creating heterogeneity inputs.
Ideally replace with a single mosdepth coverage calculation, and creat GATK4 TSV format:
CONTIG START END COUNT
chrM 1 1000 13268
"""
from bcbio.variation import coverage
from bcbio.structural import annotate
# GATK compatible
target_file = gatkcnv.collect_read_counts(data, work_dir)
# heterogeneity compatible
target_in = bedutils.clean_file(tz.get_in(["regions", "bins", "target"], data), data, bedprep_dir=work_dir)
target_cov = coverage.run_mosdepth(data, "target-gatk", target_in)
target_cov_genes = annotate.add_genes(target_cov.regions, data, max_distance=0)
return target_file, target_cov_genes
def _calculate_sv_coverage_gatk(data, work_dir):
"""Calculate coverage in defined regions using GATK tools
TODO: This does double calculations to get GATK4 compatible HDF read counts
and then depth and gene annotations. Both are needed for creating heterogeneity inputs.
Ideally replace with a single mosdepth coverage calculation, and creat GATK4 TSV format:
CONTIG START END COUNT
chrM 1 1000 13268
"""
from bcbio.variation import coverage
from bcbio.structural import annotate
# GATK compatible
target_file = gatkcnv.collect_read_counts(data, work_dir)
# heterogeneity compatible
target_in = bedutils.clean_file(tz.get_in(["regions", "bins", "target"], data), data, bedprep_dir=work_dir)
target_cov = coverage.run_mosdepth(data, "target-gatk", target_in)
target_cov_genes = annotate.add_genes(target_cov.regions, data, max_distance=0)
return target_file, target_cov_genes