Description

Copy number variant detection from high-throughput sequencing data

Input

Name (Type)
Description
Pattern

meta (map)

Groovy Map containing sample information
e.g. [ id:‘test’, single_end

]

tumour (file)

Input tumour sample bam file (or cram)

normal (file)

Input normal sample bam file (or cram)

meta2 (map)

Groovy Map containing reference information
e.g. [ id:‘test’ ]

fasta (file)

Input reference genome fasta file (only needed for cram_input and/or when normal_samples are provided)

meta3 (map)

Groovy Map containing reference information
e.g. [ id:‘test’ ]

fasta_fai (file)

Input reference genome fasta index (optional, but recommended for cram_input)

meta4 (map)

Groovy Map containing information about target file
e.g. [ id:‘test’ ]

targetfile (file)

Input target bed file

meta5 (map)

Groovy Map containing information about reference file
e.g. [ id:‘test’ ]

reference (file)

Input reference cnn-file (only for germline and tumor-only running)

Output

Name (Type)
Description
Pattern

meta (map)

Groovy Map containing sample information
e.g. [ id:‘test’, single_end

]

bed (file)

File containing genomic regions

*.{bed}

cnn (file)

File containing coverage information

*.{cnn}

cnr (file)

File containing copy number ratio information

*.{cnr}

cns (file)

File containing copy number segment information

*.{cns}

pdf (file)

File with plot of copy numbers or segments on chromosomes

*.{pdf}

png (file)

File with plot of bin-level log2 coverages and segmentation calls

*.{png}

versions (file)

File containing software versions

versions.yml

Tools

cnvkit
Apache-2.0

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.