cnvkit.sh Files

# cnvkit.sh
# Author: Chin-Chen Pan
# Directore, General and Surgical Pathology
# Professor, attending pathologist
# Department of Pathology and Laboratory Medicine
# Taipei Veterans General Hospital
# TAIWAN
# Version 2.1.1
# Date: Feb 6, 2019

[Introduction]

cnvkit.sh is a shell script to run CNVkit for exome-seq. The shell uses the files produced by exome_test.sh. It allows for recentering the baseline by the average log2ratio of a certain chromosome. The adjusted seg is further annotated by cytoband.

[Before running]

1. Install the following dependencies. CNVkit only works with certain versions of the dependencies.
    
  sudo pip install biopython pyfaidx pysam pyvcf --upgrade
  sudo apt-get install python-matplotlib python-reportlab 
  sudo pip install numpy==1.14.5
  sudo pip install pandas==0.23.3
  sudo pip install scipy==1.1.0
  sudo pip install python-dateutil==2.5.2
  sudo pip install biopython==1.72
  sudo pip install futures==3.2.0
  
2. Install R program.

  sudo R
  source("http://bioconductor.org/biocLite.R")
  biocLite(c("DNAcopy", "cghFLasso"))

3. Install cnvkit

  git clone https://github.com/etal/cnvkit
  
4. Download cnvkit.target.bed.gz and cnv_annotate.sh. Unzip them to /path/to/programs.

5. cytoband_loc files can be created by followings:

  http://hgdownload.cse.ucsc.edu/goldenPath/hg19/database/cytoBand.txt.gz 
  zcat cytoBand.txt.gz | cut -f1,2,3,4 | sort -t "`echo -e "\t"`" -k1,1 -k2,2n -u | awk -F '\t' '{print $2 "\t" $3 "\t" $4 >>"cytoband_loc_" $1}'
  copy the files to /path/to/programs/cytoband_loc


[RUNNING]

Syntax:  sh cnvit.sh sample_name mate_name output_directory -options
	
	options:
	-chr[1-22,X,Y]: The chromosome whose average Log2Ratio the baseline is adjusted to
        -kt: keep temporary files

	ex1:
	  sh cnvkit.sh test normal cnv_output -kt
	ex2:
	  sh cnvkit.sh test normal cnv_output chr4 -s