OPTITYPE

Precision 4-digit HLA-I-typing from NGS data based on integer linear programming. Use razers3 beforehand to generate input fastq files only mapping to HLA-regions. Please see https://github.com/FRED-2/OptiType

Software dependencies

  • optitype ==1.3.4

Example

This wrapper can be used in the following way:

rule optitype:
    input:
        # list of input reads
        reads=["reads/{sample}_1.fished.fastq", "reads/{sample}_2.fished.fastq"]
    output:
        multiext("optitype/{sample}", "_coverage_plot.pdf", "_result.tsv")
    log:
        "logs/optitype/{sample}.log"
    params:
        # Type of sequencing data. Can be 'dna' or 'rna'. Default is 'dna'.
        sequencing_type="dna",
        # optiype config file, optional
        config="",
        # additional parameters
        extra=""
    wrapper:
        "0.65.0/bio/optitype"

Note that input, output and log file paths can be chosen freely. When running with

snakemake --use-conda

the software dependencies will be automatically deployed into an isolated environment before execution.

Authors

  • Jan Forster

Code

__author__ = "Jan Forster"
__copyright__ = "Copyright 2020, Jan Forster"
__email__ = "j.forster@dkfz.de"
__license__ = "MIT"


import os
from snakemake.shell import shell

extra = snakemake.params.get("extra", "")
log = snakemake.log_fmt_shell(stdout=True, stderr=True)
outdir = os.path.dirname(snakemake.output[0])

# get sequencing type
seq_type = snakemake.params.get("sequencing_type", "dna")
seq_type = "--{}".format(seq_type)

# check if non-default config.ini is used
config = snakemake.params.get("config", "")
if any(config):
    config = "--config {}".format(config)

shell(
    "(OptiTypePipeline.py"
    " --input {snakemake.input.reads}"
    " --outdir {outdir}"
    " --prefix {snakemake.wildcards.sample}"
    " {seq_type}"
    " {config}"
    " {extra})"
    " {log}"
)