NAME

       cnvkit_batch - Run the complete CNVkit pipeline on one or more BAM files.

DESCRIPTION

       usage: cnvkit.py batch [-h] [-m {hybrid,amplicon,wgs}]

       [--segment-method {cbs,flasso,haar,none,hmm,hmm-tumor,hmm-germline}]
              [-y]  [-c]  [--drop-low-coverage]  [-p  [PROCESSES]]  [--rscript-path  PATH]  [-n [FILES ...]] [-f
              FILENAME] [-t FILENAME] [-a FILENAME]  [--annotate  FILENAME]  [--short-names]  [--target-avg-size
              TARGET_AVG_SIZE]  [-g FILENAME] [--antitarget-avg-size ANTITARGET_AVG_SIZE] [--antitarget-min-size
              ANTITARGET_MIN_SIZE] [--output-reference  FILENAME]  [--cluster]  [-r  REFERENCE]  [-d  DIRECTORY]
              [--scatter] [--diagram] [bam_files ...]

   positional arguments:
       bam_files
              Mapped sequence reads (.bam)

   options:
       -h, --help
              show this help message and exit

       -m {hybrid,amplicon,wgs}, --seq-method {hybrid,amplicon,wgs}, --method {hybrid,amplicon,wgs}
              Sequencing   assay   type:   hybridization   capture   ('hybrid'),  targeted  amplicon  sequencing
              ('amplicon'), or whole genome sequencing ('wgs'). Determines whether and  how  to  use  antitarget
              bins. [Default: hybrid]

       --segment-method {cbs,flasso,haar,none,hmm,hmm-tumor,hmm-germline}
              Method used in the 'segment' step. [Default: cbs]

       -y, --male-reference, --haploid-x-reference
              Use  or  assume a male reference (i.e. female samples will have +1 log-CNR of chrX; otherwise male
              samples would have -1 chrX).

       -c, --count-reads
              Get read depths by counting read midpoints within each bin. (An alternative algorithm).

       --drop-low-coverage
              Drop very-low-coverage bins before segmentation to avoid false-positive deletions in  poor-quality
              tumor samples.

       -p [PROCESSES], --processes [PROCESSES]
              Number of subprocesses used to running each of the BAM files in parallel. Without an argument, use
              the maximum number of available CPUs. [Default: process each BAM in serial]

       --rscript-path PATH
              Path to the Rscript executable to use for running R code. Use this option to specify a non-default
              R installation. [Default: Rscript]

   To construct a new copy number reference:
       -n [FILES ...], --normal [FILES ...]
              Normal  samples  (.bam) used to construct the pooled, paired, or flat reference. If this option is
              used but no filenames are given, a "flat"  reference  will  be  built.  Otherwise,  all  filenames
              following this option will be used.

       -f FILENAME, --fasta FILENAME
              Reference genome, FASTA format (e.g. UCSC hg19.fa)

       -t FILENAME, --targets FILENAME
              Target intervals (.bed or .list)

       -a FILENAME, --antitargets FILENAME
              Antitarget intervals (.bed or .list)

       --annotate FILENAME
              Use  gene models from this file to assign names to the target regions. Format: UCSC refFlat.txt or
              ensFlat.txt file (preferred), or BED, interval list, GFF, or similar.

       --short-names
              Reduce multi-accession bait labels to be short and consistent.

       --target-avg-size TARGET_AVG_SIZE
              Average size of split target bins (results are approximate).

       -g FILENAME, --access FILENAME
              Regions of accessible sequence on chromosomes (.bed), as output by the 'access' command.

       --antitarget-avg-size ANTITARGET_AVG_SIZE
              Average size of antitarget bins (results are approximate).

       --antitarget-min-size ANTITARGET_MIN_SIZE
              Minimum size of antitarget bins (smaller regions are dropped).

       --output-reference FILENAME
              Output  filename/path  for  the  new  reference  file  being  created.  (If  given,  ignores   the
              -o/--output-dir  option and will write the file to the given path. Otherwise, "reference.cnn" will
              be created in the current directory or specified output directory.)

       --cluster
              Calculate and use cluster-specific summary stats in the reference pool to normalize samples.

   To reuse an existing reference:
       -r REFERENCE, --reference REFERENCE
              Copy number reference file (.cnn).

   Output options:
       -d DIRECTORY, --output-dir DIRECTORY
              Output directory.

       --scatter
              Create a whole-genome copy ratio profile as a PDF scatter plot.

       --diagram
              Create an ideogram of copy ratios on chromosomes as a PDF.

cnvkit.py batch 0.9.10                              July 2023                                    CNVKIT_BATCH(1)