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SNVMix specifications


Unique identifier OMICS_00077
Name SNVMix
Alternative name SNVMix2
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Programming languages C, Perl
License MIT License
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Sohrab Shah <>
  • person_outline Rodrigo Goya <>

Publication for SNVMix

SNVMix citations


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

PMCID: 5852328
PMID: 29552334
DOI: 10.1016/j.csbj.2018.01.003

[…] variant callers, such as mutect and vardict, accept single sample as input (). in addition, several algorithms are dedicated to perform single-sample variant calling. these algorithms include snvmix2, shearwater, splinter, snver, outlyzer, pisces, isown, somvarius, and sinvict , , , , , , , , and fall into two categories., snvmix2, shearwater, splinter, snver, outlyzer, and pisces report […]


Comprehensive benchmarking of SNV callers for highly admixed tumor data

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

[…] saw high variability among callers and declining sensitivity with increasing admixture levels for all tools (). precision was very high for all tools and admixture levels, except for snvsniffer, snvmix2, samtools and freebayers for admixture levels above 60%., our comparison of parameter settings across tools and data types showed that parameters related to base-quality cutoffs can be used […]


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

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

[…] particular probabilistic graphical model. furthermore, they showed that the joint modeling method, jointsnvmix1, observes 80-fold reduction of false positives compared with its independent analogue (snvmix1) []. somaticsniper models the joint diploid genotype likelihoods for both tumour and normal samples []. strelka models the joint probabilistic distribution of allele frequencies […]


Statistical modeling for sensitive detection of low frequency single nucleotide variants

PMCID: 5001245
PMID: 27556804
DOI: 10.1186/s12864-016-2905-x

[…] to the discrete count nature of the data generated by ngs sequencers. such models were broadly applied in dna sequencing (dna-seq) based variants identification such as samtools [], varscan2 [], and snvmix []. for dna sequencing based single nucleotide variant (snv) identification, emerging new applications bring challenges to refine the statistical modeling methods and pushing the limit of ngs […]


The prediction of virus mutation using neural networks and rough set techniques

PMCID: 4867776
PMID: 27257410
DOI: 10.1186/s13637-016-0042-0

[…] at position u in the current sequence z, given a reference sequence x and the sequence z. the genotype highest posterior probability (map) is selected. the detection of the third state is based on snvmix model [], which uses the bayesian theorem and map to calculate the posterior probabilities for a mixed genotype g m. in this case, the p(g m|a i) can be calculated as shown in eq. […]


Medulloblastoma associated DDX3 variant selectively alters the translational response to stress

PMCID: 5053718
PMID: 27058758
DOI: 10.18632/oncotarget.8612
call_split See protocol

[…] orientation of the paired-end reads. unmapped and improperly paired aligned reads were put into the mix-fragment bam. snvs were then detected on positive- and negative-split bams separately using snvmix2 [] with parameters mb and q30. the snvs were further filtered to exclude those called based on 1) reference base n; 2) only 1 read supports the variant; 3) probability of heterozygous […]

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SNVMix institution(s)
Department of Molecular Oncology Breast Cancer Research Program, British Columbia Cancer Research Centre, Vancouver, BC, Canada; Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, Canada; Centre for Translational and Applied Genomics of British Columbia Cancer Agency, Vancouver, BC, Canada; Provincial Health Services Authority Laboratories, Vancouver, BC, Canada; Department of Computer Science, University of British Columbia, Vancouver, BC, Canada
SNVMix funding source(s)
Supported by the Canadian Institutes for Health Research (CIHR), and the Michael Smith Foundation for Health Research (MSFHR) and the Canadian Breast Cancer Foundation.

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