Table 1.
Commonly (>10 citations) applied CNV detection methods for SNP-array data.
Software | Algorithm | Code | Platform | Year a | Reference | Citations b | Software URL |
---|---|---|---|---|---|---|---|
PennCNV | HMM | Perl | Multiple | 2007 | [43] | 300 | http://penncnv.openbioinformatics.org |
Birdsuite (Birdseye, Canary) | Mixture models | Java/Python/R | Affymetrix | 2008 | [44] | 300 | http://www.broadinstitute.org |
Nexus Copy Number | Proprietary (Segmentation) | windows executable | Multiple | - | - | 100 | http://www.biodiscovery.com |
QuantiSNP | HMM | MATLAB | Multiple | 2007 | [45] | 100 | http://sites.google.com/site/quantisnp |
CNVPartition | Proprietary | windows executable | Illumina | 2006 | - | 100 | http://support.illumina.com |
Partek Genomics Suite | Proprietary (Segmentation or HMM) | windows executable | Multiple | - | - | 30 | http://www.partek.com/pgs |
CNVFinder | Experimental variability | perl | Array CGH | 2006 | [46] | 30 | http://www.sanger.ac.uk/resources/software/cnvfinder/ |
CGHCall | segmentation and mixture model | R | Array CGH | 2007 | [47] | 30 | http://www.few.vu.nl/~mavdwiel/CGHcall.html |
GenoCNV | HMM | R | Multiple | 2009 | [48] | 30 | http://www.bios.unc.edu/~weisun/software/genoCN.htm |
SW-ARRAY | Smith Waterman | R | Array CGH | 2005 | [49] | 30 | Not available |
HMMSeg | HMM wavelet smoothing | Java | Multiple | 2007 | [50] | 10 | http://noble.gs.washington.edu/proj/hmmseg |
VanillaICE | HMM | R | Affymetrix | 2008 | [51] | 10 | http://cran.r-project.org |
CNVHap | HMM, Haplotype | Java | Multiple | 2010 | [52] | 10 | http://www.imperial.ac.uk/people/l.coin |
dChip | Multiple | R | Multiple | 2008 | [53] | 10 | http://sites.google.com/site/dchipsoft |
GADA | Bayesian | R | Multiple | 2010 | [54] | 10 | http://cran.r-project.org |
CNV Workshop | Segmentation | complete VM | Multiple | 2010 | [55] | 10 | http://sourceforge.net/projects/cnv |
a Year reference when published. b At least this many citations in PubMed or company website at July 2015. Abbreviation: HMM, Hidden Markov Model.