Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives

Min Zhao; Qingguo Wang; Quan Wang; Peilin Jia; Zhongming Zhao

doi:10.1186/1471-2105-14-S11-S1

Table 2 Read depth (RD)-based tools for CNV detection using whole genome sequencing data

From: Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives

Tool	URL	Language	Input	Comments	Ref.
SegSeq^a	http://www.broad.mit.edu/cancer/pub/solexa_copy_numbers/	Matlab	Aligned read positions	Detecting CNV breakpoints using massively parallel sequence data	[33]
CNV-seq^a	http://tiger.dbs.nus.edu.sg/cnv-seq/	Perl, R	Aligned read positions	Identifying CNVs using the difference of observed copy number ratios	[31]
RDXplorer^b	http://rdxplorer.sourceforge.net/	Python, Shell	BAM	Detecting CNVs through event-wise testing algorithm on normalized read depth of coverage	[28]
BIC-seq^a	http://compbio.med.harvard.edu/Supplements/PNAS11.html	Perl, R	BAM	Using the Bayesian information criterion to detect CNVs based on uniquely mapped reads	[41]
CNAseg^a	http://www.compbio.group.cam.ac.uk/software/cnaseg	R	BAM	Using flowcell-to-flowcell variability in cancer and control samples to reduce false positives	[44]
cn.MOPS^b	http://www.bioinf.jku.at/software/cnmops/	R	BAM/read count matrices	Modelling of read depths across samples at each genomic position using mixture Poisson model	[46]
JointSLM^b	http://nar.oxfordjournals.org/content/suppl/2011/02/16/gkr068.DC1/JointSLM_R_Package.zip	R	SAM/BAM	Population-based approach to detect common CNVs using read depth data	[45]
ReadDepth	http://code.google.com/p/readdepth/	R	BED files	Using breakpoints to increase the resolution of CNV detection from low-coverage reads	[38]
rSW-seq^a	http://compbio.med.harvard.edu/Supplements/BMCBioinfo10-2.html	C	Aligned read positions	Identifying CNVs by comparing matched tumor and control sample	[34]
CNVnator	http://sv.gersteinlab.org/	C++	BAM	Using mean-shift approach and performing multiple-bandwidth partitioning and GC correction	[40]
CNVnorm^a	http://www.precancer.leeds.ac.uk/cnanorm	R	Aligned read positions	Identifying contamination level with normal cells	[32]
CMDS^b	https://dsgweb.wustl.edu/qunyuan/software/cmds	C, R	Aligned read positions	Discovering CNVs from multiple samples	[47]
mrCaNaVar	http://mrcanavar.sourceforge.net/	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	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.

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