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JointSNVMix specifications


Unique identifier OMICS_00085
Name JointSNVMix
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C, C++, Python
License GNU General Public License version 2.0
Computer skills Advanced
Version 0.8.0
Stability Stable
Maintained Yes




No version available



  • person_outline Sohrab P. Shah

Additional information

Publication for JointSNVMix

JointSNVMix citations


Single nucleotide variant profiles of viable single circulating tumour cells reveal CTC behaviours in breast cancer

PMCID: 5928770
PMID: 29565466
DOI: 10.3892/or.2018.6325
call_split See protocol

[…] were processed for local Indel realignment, base quality estimation and recalibration for further analysis.Somatic mutation calling was performed. For whole exome data, VarScan2 () combined with the JointSNVMix2 () algorithm were used to identify somatic mutations and the candidates were merged, while whole genomic data somatic mutation calling used only the VarScan2 algorithm. To reduce false-po […]


A review of somatic single nucleotide variant calling algorithms for next generation sequencing data

Comput Struct Biotechnol J
PMCID: 5852328
PMID: 29552334
DOI: 10.1016/j.csbj.2018.01.003

[…] variant calling is equivalent to calculating P(somatic) = P(AA, AB) + P(AA, BB), the probability of homozygous-reference in normal and heterozygous or homozygous-non-reference in tumor. Specifically, JointSNVMix2 applies a hierarchical Bayesian model to estimate joint genotype probabilities. Virmid views tumor as a mixture of normal tissues and somatic mutations and provides a joint estimation of […]


Comprehensive benchmarking of SNV callers for highly admixed tumor data

PLoS One
PMCID: 5636151
PMID: 29020110
DOI: 10.1371/journal.pone.0186175

[…] n for HaplotypeCaller (99.3% sensitivity and 99.9% precision), SAMtools (99.6% sensitivity and 99.8% precision), and FreeBayes (98.8% sensitivity and 99.8% precision). Atlas2 (72.5% sensitivity), and JointSNVMix (72.0% sensitivity) identified the lowest number of SNVs.Next, we looked at the concordance of calls between all callers. For the exome data, all ten germline callers correctly identified […]


Variational inference for rare variant detection in deep, heterogeneous next generation sequencing data

BMC Bioinformatics
PMCID: 5244592
PMID: 28103803
DOI: 10.1186/s12859-016-1451-5

[…] then distinguishes true rare variants from the sequencing errors []. However, the bottleneck of CRISP is its low computational efficiency due to a calculation of a large number of contingency tables.JointSNVMix introduces two Bayesian probabilistic models (JointSNVMix1 and JointSNVMix2) to jointly analyze a tumour-normal paired allelic count of NGS data []. JointSNVMix derives an expectation maxi […]


Detailed simulation of cancer exome sequencing data reveals differences and common limitations of variant callers

BMC Bioinformatics
PMCID: 5209852
PMID: 28049408
DOI: 10.1186/s12859-016-1417-7

[…] We compared the nine somatic variant calling programs deepSNV [], Genome Analysis Toolkit (GATK) HaplotypeCaller (HP) [–], GATK UnifiedGenotyper (UG) [–], JointSNVMix2 [], MuTect [], SAMtools [], SiNVICT [], SomaticSniper [], and VarScan2 []. Figure illustrates the workflow for the comparison in a flowchart. A heterogeneous cancer sample was simulated […]


Simul seq: combined DNA and RNA sequencing for whole genome and transcriptome profiling

Nat Methods
PMCID: 5734913
PMID: 27723755
DOI: 10.1038/nmeth.4028

[…] w. Briefly, somatic variants with a Bina ONCOSCORE of greater than or equal to 5 were considered high confidence and reported. To identify somatic variants and generate the ONCOSCORE, Bina integrates JointSNVMix 0.7.5 (), Mutect 2014.3-24-g7dfb931 (), Somatic Indel Detector 2014.3-24-g7dfb931, Somatic Sniper 1.0.4 () and Varscan 2.3.7 () outputs. GATK ASEReadCounter was used to determine the varia […]


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JointSNVMix institution(s)
Department of Molecular Oncology, BC Cancer Agency, University of British Columbia, Vancouver, BC, Canada; Canada’s Michael Smith Genome Sciences Centre, University of British Columbia, Vancouver, BC, Canada; Department of Computer Science; Department of Pathology, University of British Columbia, Vancouver, BC, Canada
JointSNVMix funding source(s)
Supported by Canadian Institutes for Health Research (CIHR) grant #202452, the Canadian Breast Cancer Foundation and the Michael Smith Foundation for Health Research.

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