getPileup

This function is for generating pileups.table using bam files.

Note

This function is calling gatk GetPileupSummaries, 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

getPileup(bamInput=None, biallelicvcfInput=None,
          outputdir=None, stepNum=None,
          upstream=None, threads=1,
          verbose=False, other_params=None)

  • bamInput: list, Input bam files.

  • biallelicvcfInput: str, mandatory. A VCF file containing variants and allele frequencies Required. eg: small_exac_common_3_hg19.SNP_biallelic.vcf

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

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

  • upstream: upstream output results, used for pipeline, just from addRG / BQSR. 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"
)