cnvbatch

This function is used for cnv calling using cnvkit.

Note

This function is calling cnvkit.py batch, please install cnvkit before using.

cnvkit official docs

Talevich, Eric, et al. “CNVkit: genome-wide copy number detection and visualization from targeted DNA sequencing.” PLoS computational biology 12.4 (2016): e1004873.

Parameters

cnvbatch(casebamInput=None, ctrlbamInput=None,
         outputdir=None, genome=None, ref=None, threads=1,
         access=None, annotate=None, reference_cnn=None,
         other_params={"-m": "wgs", "-y": True},
         stepNum=None, caseupstream=None, ctrlupstream=None,
         verbose=False, **kwargs)

  • casebamInput: list, case bam files, only this part of bam files will call cnv.

  • casebamInput: list, ctrl bam files, this bam files is using for generating reference cnn, will not call cnv.

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

  • threads: int, how many thread to use.

  • genome: str, human genome version, just support “hg19” and “hg38”

  • ref: str, reference folderpath.

  • access: str, an “access” file precomputed for the UCSC reference human genome, with some know low-mappability regions excluded. eg: access-5kb-mappable.hg19.bed.

  • annotate: str, Gene annotation databases, eg. refFlat_hg19.txt.

  • reference_cnn: str, reference cnn file, you can using the ready-made cnn file as baseline.

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

  • other_params: str or dict. other parameters for cnvkit batch. default is {“-m”: “wgs”, “-y”: True}, which means WGS data, and the ref is male.

  • caseupstream: case upstream output results, used for call cnv pipeline. This parameter can be True, which means a new pipeline start.

  • ctrlupstream: ctrl upstream output results.

Warning

We recommend using this function in bin-level CNV detection.

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",
 )

bams = ["test1.bam", "test1.bam"]
verbose = True

 res_cnvbatch = cnvbatch(
     casebamInput=bams,
     caseupstream=True,
     access=Configure.getConfig("access-mappable"),
     annotate=Configure.getConfig("refFlat"),
     verbose=verbose,
     stepNum="CNV01",
 )
 res_cnvPlot = cnvPlot(upstream=res_cnvbatch, verbose=verbose, stepNum="CNV02",)
 res_cnvTable = cnvTable(
     upstream=res_cnvbatch, verbose=verbose, stepNum="CNV03",
 )
 res_cnvHeatmap = cnvHeatmap(
     upstream=res_cnvbatch, verbose=verbose, stepNum="CNV04",
 )