BQSR

This function is for generating new bam with recaled base.

Note

This function is calling gatk ApplyBQSR, please install GATK before using.

gatk official docs

McKenna, Aaron, et al. “The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.” Genome research 20.9 (2010): 1297-1303.

Parameters

BQSR(bamInput=None, recalInput=None, outputdir=None,
     genome=None, ref=None, stepNum=None,
     upstream=None, threads=1,
     verbose=False, **kwargs)

  • bamInput: list, Input bam files.

  • recalInput: list, Input recal file from BaseRecalibrator.

  • outputdir: str, output result folder, None means the same folder as input files.

  • genome: str, genome version, just be hg19 or hg38.

  • ref: str, reference genome file path.

  • stepNum: int or str, step flag for folder name.

  • upstream: upstream output results, used for pipeline, just from BaseRecalibrator. This parameter can be True, which means a new pipeline start.

  • threads: int, how many threads used?

  • verbose: bool, True means print all stdout, but will be slow; False means black stdout verbose, much faster.

Warning

We recommend using this function in SNV detection. For a detailed tutorial, please see SNV detection tutorial.

Example usage:

from cfDNApipe import *
import glob

pipeConfigure(
    threads=60,
    genome="hg19",
    refdir=r"path_to_reference/hg19",
    outdir=r"path_to_output/snv_output",
    data="WGS",
    type="paired",
    build=True,
    JavaMem="10G",
)

# just set build=True to finish all the works
Configure.snvRefCheck(folder="path_to_reference/hg19/hg19_snv", build=True)

# see all the SNV related files
Configure.getConfig("snv.folder")
Configure.getConfig("snv.ref")

# indexed bam files after remove duplicates
bams = glob.glob("path_to_samples/*.bam")

res1 = addRG(bamInput=bams, upstream=True)

res2 = BaseRecalibrator(
    upstream=res1, knownSitesDir=Configure.getConfig("snv.folder")
)
res3 = BQSR(upstream=res2)

res4 = getPileup(
    upstream=res3,
    biallelicvcfInput=Configure.getConfig('snv.ref')["7"],
)

res5 = contamination(upstream=res4)

# In this step, files are split to chromatin
res6 = mutect2t(
    caseupstream = res5,
    vcfInput=Configure.getConfig('snv.ref')["6"],
    ponbedInput=Configure.getConfig('snv.ref')["8"],
)

#
res7 = filterMutectCalls(upstream=res6)

# put all chromatin files together
res8 = gatherVCF(upstream=res7)

# split somatic mutations
res9 = bcftoolsVCF(upstream=res8, stepNum="somatic")

# split germline mutations
res10 = bcftoolsVCF(
    upstream=res8, other_params={"-f": "'germline'"}, suffix="germline", stepNum="germline"
)