Table 2

Read depth (RD)-based tools for CNV detection using whole genome sequencing data

Tool

URL

Language

Input

Comments

Ref.


SegSeqa

http://www.broad.mit.edu/cancer/pub/solexa_copy_numbers/ webcite

Matlab

Aligned read positions

Detecting CNV breakpoints using massively parallel sequence data

[33]

CNV-seqa

http://tiger.dbs.nus.edu.sg/cnv-seq webcite/

Perl, R

Aligned read positions

Identifying CNVs using the difference of observed copy number ratios

[31]

RDXplorerb

http://rdxplorer.sourceforge.net webcite/

Python, Shell

BAM

Detecting CNVs through event-wise testing algorithm on normalized read depth of coverage

[28]

BIC-seqa

http://compbio.med.harvard.edu/Supplements/PNAS11.html webcite

Perl, R

BAM

Using the Bayesian information criterion to detect CNVs based on uniquely mapped reads

[41]

CNAsega

http://www.compbio.group.cam.ac.uk/software/cnaseg webcite

R

BAM

Using flowcell-to-flowcell variability in cancer and control samples to reduce false positives

[44]

cn.MOPSb

http://www.bioinf.jku.at/software/cnmops/ webcite

R

BAM/read count matrices

Modelling of read depths across samples at each genomic position using mixture Poisson model

[46]

JointSLMb

http://nar.oxfordjournals.org/content/suppl/2011/02/16/gkr068.DC1/JointSLM_R_Package.zip webcite

R

SAM/BAM

Population-based approach to detect common CNVs using read depth data

[45]

ReadDepth

http://code.google.com/p/readdepth webcite/

R

BED files

Using breakpoints to increase the resolution of CNV detection from low-coverage reads

[38]

rSW-seqa

http://compbio.med.harvard.edu/Supplements/BMCBioinfo10-2.html webcite

C

Aligned read positions

Identifying CNVs by comparing matched tumor and control sample

[34]

CNVnator

http://sv.gersteinlab.org webcite/

C++

BAM

Using mean-shift approach and performing multiple-bandwidth partitioning and GC correction

[40]

CNVnorma

http://www.precancer.leeds.ac.uk/cnanorm webcite

R

Aligned read positions

Identifying contamination level with normal cells

[32]

CMDSb

https://dsgweb.wustl.edu/qunyuan/software/cmds webcite

C, R

Aligned read positions

Discovering CNVs from multiple samples

[47]

mrCaNaVar

http://mrcanavar.sourceforge.net webcite/

C

SAM

A tool to detect large segmental duplications and insertions

[35]

CNVeM

N/A

N/A

N/A

Predicting CNV breakpoints in base-pair resolution

[42]

cnvHMM

http://genome.wustl.edu/software/cnvhmm webcite

C

Consensus sequence from SAMtools

Using HMM to detect CNV

N/A


aTools require matched case-control sample as input.

bTools use multiple samples as input.

Zhao et al. BMC Bioinformatics 2013 14(Suppl 11):S1   doi:10.1186/1471-2105-14-S11-S1

Open Data