Given a set of single-sample VCF files, it counts how many times each variant is called in the set. It reports this in the following format:
chrom start stop alts count_with_other_filters count_with_filter_pass
chr1 11021 11022 ('A',) 1 0
Build the Docker image using the following command after replacing [TAG] with your preferred tag.
docker build --platform linux/amd64 -t [TAG] .
The following is an example input to the workflow.
{
"VariantOccurrenceFrequency.sample_ids": [
"SP0001643",
"SP0001677",
"SP0001710",
"SP0001952",
"SP0002342"
],
"VariantOccurrenceFrequency.vcf_files": [
"SP0001643.vcf.gz",
"SP0001677.vcf.gz",
"SP0001710.vcf.gz",
"SP0001952.vcf.gz",
"SP0002342.vcf.gz"
],
"VariantOccurrenceFrequency.runtime_override_encode": {"docker": "pzm:latest"},
"VariantOccurrenceFrequency.runtime_override_merge": {"docker": "pzm:latest"},
"VariantOccurrenceFrequency.runtime_override_decode": {"docker": "pzm:latest"},
"VariantOccurrenceFrequency.max_batch_size": 100
}
The workflow batches the input variants into batches of max_batch_size size.
The batching is related to the first step of the workflow that reads the VCF files to extract information.
The rest of the pipeline is not batched. It takes about ~30seconds to read each VCF, hence a batch of 100, may take
~3000 seconds per batch.