orig pub
caller class
input type
somatic/denovo
from
validated vs.
cited
used by
compared by
algorithm
features
description
installation
study
source
bic-seq2
2016
cnv
somatic
1
CLAMMS
2016
CNV
exome
Regeneron Genetics Center
3
HMM/mixture model
exome capture data, normalizes GC content
Copy number estimation using Lattice-Aligned Mixture Models. Evaluate the adherence of CNV calls from CLAMMS and four other algorithms to Mendelian inheritance patterns on a pedigree
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681995/
https://github.com/rgcgithub/clamms
CNVKit
2016
CNV
targeted seq
somatic
UCSF
5
biocondor
CBS algorithm (circular binary segmentation)
targeted reads, uses off-target reads
CNV detection that takes advantage of both on– and off-target sequencing reads and applies a series of corrections to improve accuracy in copy number calling.
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004873
http://cnvkit.readthedocs.io/en/stable/index.html
ERDS-pe
2016
CNV
0
paired HMM
https://www.computer.org/csdl/proceedings/bibm/2016/1611/00/07822508-abs.html
https://github.com/microtan0902/erds-pe
PopSV
2016
CNV
population
McGill U Canada, Bourque
0
Population-based detection of structural variation from High-Throughput Sequencing
http://biorxiv.org/content/early/2016/05/09/034165
https://github.com/jmonlong/PopSV/blob/master/5-FAQ.md
triocnv
2016
cnv
trio
AS-GENSENG
2015
CNV
exome or wgs
UNC Chapel Hill
7
HMM/model total and allele specific separate
combines allele-specific RC with total RC
incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4538801/
https://sourceforge.net/projects/asgenseng/
Codex
2015
CNV
exome
population
U Penn Philadelphia
18
Poisson latent factor/recursive segmentation
includes terms that specifically remove biases due to GC content, exon length and capture and amplification efficiency, and latent systematic artifacts
relies on the availability of multiple samples processed using the same sequencing pipeline. Unlike current approaches, CODEX uses a Poisson log-linear model that is more suitable for discrete count data. The normalization model in CODEX includes terms that specifically remove biases due to GC content, exon length and capture and amplification efficiency, and latent systematic artifacts
https://www.ncbi.nlm.nih.gov/pubmed/25618849
http://www.bioconductor.org/packages/devel/bioc/html/CODEX.html
CONSERTING
2015
CNV/SV
St Jude
13
regression tree segmentation
dep on bambino, picard
integrate read-depth change with structural variation (SV) identification through an iterative process of segmentation by read depth, segment merging, and localized SV detection. recursive partitioning techniques to find the transition point for read depth changes.
https://www.ncbi.nlm.nih.gov/pubmed/25938371
http://www.stjuderesearch.org/site/lab/zhang
CopywriteR
2015
CNV
targeted seq
Netherlands Cancer Institute
16
CBS algorithm, uses off-target sequencing reads
reference-free
exploiting ‘off-target’ sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels
https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0617-1
https://github.com/PeeperLab/CopywriteR
falcon
2015
CNV
somatic
UC Davis
8
bivariate mixed Binomial, Bayesian criterion for count estimates
calculates allele-specific copy numbers, deduce clonal history
based on a change-point model on a bivariate mixed Binomial process, which explicitly models the copy numbers of the two chromosome haplotypes and corrects for local allele-specific coverage biases. By using the Binomial distribution rather than a normal approximation, falcon more effectively pools evidence from sites with low coverage
https://www.ncbi.nlm.nih.gov/pubmed/25477383
https://github.com/PacificBiosciences/FALCON/wiki/Manual
Grom-RD
2015
CNV
Grigoriev-Lab
1
wgs, no control req
excessive coverage masking, GC bias mean and variance normalization, GC weighting, dinucleotide repeat bias detection and adjustment, and a size-varying sliding window CNV search.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4369336
http://grigoriev.rutgers.edu/software/grom-rd/index.html
modSaRa
2015
CNV
3
screening and ranking algo
http://c2s2.yale.edu/software/modSaRa/
AbsCN-seq
2014
CNV/purplo
exome
UCSD, Messer
15
estimates purity and ploidy
first work that has provided a working pipeline to estimate purity, ploidy and absolute copy numbers from raw WES data
http://bioinformatics.oxfordjournals.org/content/early/2014/01/13/bioinformatics.btt759.long
http://biostats.mcc.ucsd.edu/files/absCNseq_1.0.tar.gz
ADTEx
2014
CNV/purplo
exome
somatic testing
U Melbourne, Halgamuge
18
HMM
estimates purity and ploidy
uses two Hidden Markov Models to predict copy number and genotypes and computationally resolves polyploidy/aneuploidy, normal cell contamination and signal baseline shift. Our method makes explicit detection on chromosome arm level events, which are commonly found in tumour samples
http://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-15-732
http://adtex.sourceforge.net/tutorial.html
CANOES
2014
CNV
exome
Columbia U
15
models sequence coverage using the negative binomial distribution
http://nar.oxfordjournals.org/content/early/2014/04/25/nar.gku345.long
http://www.columbia.edu/~ys2411/canoes/
CliMAT
2014
CNV/LOH
U Hefei, China
12
robust to contamination and aneuploidy
takes integrated analysis of read count and allele frequency derived from sequenced tumor samples, and provides extensive data processing procedures including GC-content and mappability correction of read count and quantile nor-malization of B allele frequency
https://www.ncbi.nlm.nih.gov/pubmed/24845652
http://bioinformatics.ustc.edu.cn/CLImAT/
CNVCapSeq
2014
CNV
targeted reseq
Imperial College London
0
cnvCapSeq integrates evidence from both RD and read pairs (RP) to achieve high breakpoint resolution regardless of coverage uniformity
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4227763/
https://sourceforge.net/projects/cnvcapseq/
CNVOffSeq
2014
CNV
Imperial College London, Coin
4
normalization framework for off-target read depth that is based on local adaptive singular value decomposition (SVD). This method is designed to address the heterogeneity of the underlying data and allows for accurate and precise CNV detection and genotyping in off-target regions.
http://bioinformatics.oxfordjournals.org/content/30/17/i639.long
https://sourceforge.net/projects/cnvoffseq/
CNVrd2
2014
CNV
cnvnator, cn.mops
8
first uses observed read-count ratios to refine segmentation results in one population. Then a linear regression model is applied to adjust the results across multiple populations, in combination with a Bayesian normal mixture model to cluster segmentation scores into groups for individual CN counts.
https://www.ncbi.nlm.nih.gov/pubmed/25136349/
http://www.bioconductor.org/packages/devel/bioc/html/CNVrd2.html
m-HMM
2014
CNV
528
HMM
http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-109
https://www.stt.msu.edu/users/hengwang/mHMM.html
OncoCNV
2014
CNV
amplicon
Curie Institute
15
defining a method to normalize read coverage with a small set of normal control samples and (ii) assigning statistical significance to putative CNAs resulting from the segmentation of normalized profiles
https://www.ncbi.nlm.nih.gov/pubmed/25016581
PatternCNV
2014
CNV
exome
somatic
Mayo
12
compares paired samples
WIG format bams for speed
accounts for the read coverage variations between exons while leveraging the consistencies of this variability across different samples;
https://bioinformatics.oxfordjournals.org/content/30/18/2678
http://bioinformaticstools.mayo.edu/research/patterncnv/
PyLOH
2014
CNV/LOH/purplo
UC Irvine
14
biocondor
estimates purity and ploidy
deconvolve read mixture to identify reads associated with tumor cells or a particular subclone of tumor cells. Integrate somatic copy number alterations and loss of heterozygosity in a unified probabilistic framework.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103592/
https://github.com/uci-cbcl/PyLOH
qdnaseq
2014
CNV
34
read-depth, no paired analysis needed
shallow depth ok, robust to FFPE
http://genome.cshlp.org/content/early/2014/09/18/gr.175141.114
http://www.bioconductor.org/packages/release/bioc/html/QDNAseq.html
CNVem
2013
CNV
UCLA
15
use maximum likelihood to estimate locations and copy numbers of copied regions and implement an expectation-maximization (EM) algorithm
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3590897/
http://genetics.cs.ucla.edu/cnvem/index.html
CoNVEX available?
2013
CNV
exome
U Melbourne
30
HMM
uses ratio of tumour and matched normal average read depths at each exonic region, to predict the copy gain or loss
http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-S2-S2
Excavator 1 & 2
2013
CNV
exome
U Florence
71
read-count/HMM based with 3-step normalization, segmentation
efficient processing
combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number state
https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-10-r120
https://sourceforge.net/projects/excavatortool/
fishingcnv
2013
CNV
McGill U Canada, Majewski
31
compares coverage depth in a test sample against a background distribution of control samples and uses principal component analysis to remove batch effects
https://bioinformatics.oxfordjournals.org/content/29/11/1461
https://sourceforge.net/projects/fishingcnv/
patchwork
2013
CNV
wgs
33
https://www.ncbi.nlm.nih.gov/pubmed/23531354/
http://patchwork.r-forge.r-project.org/
THetA 2
2013
CNV/purplo
somatic
Brown, Raphael
92
biocondor
maximum likelihood mixture decomposition problem
estimates purplo, efficient
infers the most likely collection of genomes and their proportions in a sample, for the case where copy number aberrations distinguish subpopulations. THetA successfully estimates normal admixture and recovers clonal and subclonal copy number aberrations
http://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-7-r80
http://compbio.cs.brown.edu/software/
ABSOLUTE
2012
CNV/LOH
Broad, Getz
426
estimates loss of heterozygosity
detect subclonal heterogeneity and somatic homozygosity, and it can calculate statistical sensitivity for detection of specific aberrations
http://www.nature.com/nbt/journal/v30/n5/full/nbt.2203.html
http://archive.broadinstitute.org/cancer/cga/absolute
APOLLOH
2012
CNV/LOH
somatic
British Colombia Cancer Agency
75
estimates loss of heterozygosity
a hidden Markov model (HMM) for predicting somatic loss of heterozygosity and allelic imbalance in whole tumour genome sequencing data.
https://www.ncbi.nlm.nih.gov/pubmed/22637570
http://compbio.bccrc.ca/software/apolloh/
CNAnorm
2012
CNV
U Leeds
82
identify the multi-modality of the distribution of smoothed ratios. Then we use the estimates of the mean (modes) to identify underlying ploidy and the contamination level, and finally we perform the correction.
https://www.ncbi.nlm.nih.gov/pubmed/22039209
http://www.precancer.leeds.ac.uk/software-and-datasets/cnanorm/
cnanorm
2012
CNV
RD somatic
82
https://www.ncbi.nlm.nih.gov/pubmed/22039209/
http://www.precancer.leeds.ac.uk/software-and-datasets/cnanorm/
CNVHitSeq
2012
CNV
Imperial College London
19
jointly models evidence from RD, RPs and SRs at the population level. pool information across individual samples and reconcile copy number differences among data sources
https://genomebiology.biomedcentral.com/articles/10.1186/gb-2012-13-12-r120
https://sourceforge.net/projects/cnvhitseq/
CoNIFER
2012
CNV
exome
population
U Wash Seattle
239
this method can be used to reliably predict (94% overall precision) both de novo and inherited rare CNVs involving three or more consecutive exons
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409265/
http://conifer.sourceforge.net/
Contra
2012
CNV
exome
Peter MacCallum Cancer Centre
127
CBS algorithm
calls copy number gains and losses for each target region based on normalized depth of coverage. Our key strategies include the use of base-level log-ratios to remove GC-content bias, correction for an imbalanced library size effect on log-ratios, and the estimation of log-ratio variations via binning and interpolation
https://www.ncbi.nlm.nih.gov/pubmed/22474122
https://sourceforge.net/projects/contra-cnv/
ERDS avail?
2012
CNV
39
starts from read depth (RD) information, and integrates other information including paired end mapping (PEM) and soft-clip signature to call CNVS
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3511991/
?
ExomeDepth
2012
CNV
targeted seq
denovo?
U Cambridge, Negentsev
131
biocondor
mendelian
Calls copy number variants (CNVs) from targeted sequence data, typically exome sequencing experiments designed to identify the genetic basis of Mendelian disorders.
http://bioinformatics.oxfordjournals.org/content/28/21/2747.long
https://cran.r-project.org/web/packages/ExomeDepth/index.html
Magnolya
2012
CNV/reffree
Netherlands Bioinformatics Centre
25
enables copy number variation (CNV) detections without using a reference genome. Magnolya directly compares two next-generation sequencing datasets.
https://www.ncbi.nlm.nih.gov/pubmed/23047563
https://sourceforge.net/projects/magnolya/
XHMM
2012
CNV
exome
Mt Sinai, Purcell
183
PCA/HMM
uses principal component analysis (PCA) normalization and a hidden Markov model (HMM) to detect and genotype copy number variation (CNV) from normalized read-depth data from targeted sequencing experiments.
http://www.cell.com/AJHG/abstract/S0002-9297%2812%2900417-X
http://atgu.mgh.harvard.edu/xhmm/index.shtml
BIC-seq 1&2
2011
CNV
somatic
Harvard
111
Combines normalization of the data at the nucleotide level and Bayesian information criterion-based segmentation to detect both somatic and germline copy number variations
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219132/
http://compbio.med.harvard.edu/Supplements/PNAS11.html
CNVnator
2011
CNV
Yale, Gerstein
384
metasv
read coverage
no control req
CNVnator is able to discover CNVs in a vast range of sizes, from a few hundred bases to megabases in length,
https://www.ncbi.nlm.nih.gov/pubmed/21324876
https://github.com/abyzovlab/CNVnator
ExomeCNV
2011
CNV
exome
Dana-Farber Cancer Institute
227
a statistical method to detect CNV and LOH using depth-of-coverage and B-allele frequencies, from mapped short sequence reads
http://bioinformatics.oxfordjournals.org/content/27/19/2648.short
https://cran.r-project.org/src/contrib/Archive/ExomeCNV/
ExomeCopy
2011
CNV
exome
U Oslo
38
an HMM for predicting copy number state in exome and other targeted sequencing data using observed read counts and positional covariates
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3517018/
http://www.bioconductor.org/packages/release/bioc/html/exomeCopy.html
jointSLM
2011
CNV
RD population
47
https://www.ncbi.nlm.nih.gov/pubmed/21321017/
?
readdepth
2011
CNV
111
no control req
https://www.ncbi.nlm.nih.gov/pubmed/21305028/
https://github.com/chrisamiller/readDepth
cnaseg
2010
CNV
RD somatic
78
https://www.ncbi.nlm.nih.gov/pubmed/20966003/
http://www.compbio.group.cam.ac.uk/software/cnaseg/
CNVer
2010
CNV
U Toronto
129
supplements the depth-of-coverage with paired-end mapping information, where mate pairs mapping discordantly to the reference serve to indicate the presence of variation.
docs.google.com/document/d/1Ki36Ye7cDDA6nlEhgvICsg_IsSguxyBb1u4MCWi5so0/edit
http://compbio.cs.toronto.edu/CNVer/
copyseq
2010
CNV
53
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000988
FreeC
2010
CNV
Institut Curie, Barillot
137
no control req
The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells.
http://bioinformatics.oxfordjournals.org/content/27/2/268.short
novelseq
2010
CNV
91
discover the content and location of long novel sequence insertions
https://www.ncbi.nlm.nih.gov/pubmed/20385726
http://novelseq.sourceforge.net/Home
rSW-seq
2010
CNV
RD somatic
38
https://www.ncbi.nlm.nih.gov/pubmed/20718989/
http://compbio.med.harvard.edu/Supplements/BMCBioinfo10-2.html
CMDS
2009
CNV
WashU St Louis, Province
41
correlation matrix diagonal segmentation (CMDS), identifies RCNAs based on a between-chromosomal-site correlation analysis.
http://bioinformatics.oxfordjournals.org/content/26/4/464.full
https://dsgweb.wustl.edu/qunyuan/software/cmds/
cnv-seq
2009
CNV
RD somatic
332
https://www.ncbi.nlm.nih.gov/pubmed/19267900/
http://tiger.dbs.nus.edu.sg/CNV-seq/
RDXplorer
2009
CNV
Cold Spring Harbor
373
no contol req
copy number variants (CNV) detection in whole human genome sequence data using read depth (RD) coverage. CNV detection is based on the Event-Wise Testing (EWT) algorithm
https://www.ncbi.nlm.nih.gov/pubmed/19657104
http://rdxplorer.sourceforge.net/
segseq
2009
CNV
RD somatic
414
https://www.ncbi.nlm.nih.gov/pubmed/19043412/
?