MutSig protocols

MutSig specifications

Information


Unique identifier OMICS_00155
Name MutSig
Alternative names Mutation Significance, MutSigCV
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data A list of mutations (and indels) from a set of samples (patients) that were subjected to DNA sequencing, a coverage file that contains information about the sequencing coverage achieved for each gene and patient/tumor, a covariate file that contains the genomic covariate data for each gene.
Input format MAF, TSV
Output data A tab-delimited report of significant mutations, listed in descending order from most significant to least significant.
Output format TSV
Operating system Unix/Linux
Programming languages MATLAB
Computer skills Advanced
Version 1.3.01
Stability Stable
Maintained No

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Publication for Mutation Significance

MutSig IN pipelines

 (6)
2018
PMCID: 5858179
PMID: 29556353
DOI: 10.7150/thno.22010

[…] present in this panel were removed. copy number change and gene expression data were obtained from tcga data portal., we identified significantly mutated genes (smgs) with three algorithms using mutsigcv, mutsigcl and mutsigfn. mutsigcv quantifies significance of non-silent mutations in a gene based on background mutation rate estimated by silent mutations with other confounding covariates […]

2018
PMCID: 5858179
PMID: 29556353
DOI: 10.7150/thno.22010

[…] copy number change and gene expression data were obtained from tcga data portal., we identified significantly mutated genes (smgs) with three algorithms using mutsigcv, mutsigcl and mutsigfn. mutsigcv quantifies significance of non-silent mutations in a gene based on background mutation rate estimated by silent mutations with other confounding covariates taken into account. mutsigcl […]

2017
PMCID: 5688099
PMID: 29142225
DOI: 10.1038/s41467-017-01730-x

[…] status of the snps. the wes samples were hierarchically clustered by the “dendextend” package in r33., to identify significantly mutated genes, somatic mutations were annotated using oncotator34. mutsigcv (v1.4)19 was applied to identify significantly mutated genes with default covariate tables. genes with q (fdr) < 0.1 were considered to be significantly mutated. we performed survival […]

2016
PMCID: 4762882
PMID: 26892726
DOI: 10.1038/ncomms10536

[…] the range of 2–10 mutations per cell line (fig. 2d). the potential for variants to be oncogenic was assessed by measuring their overlap with cancer genes, transcription factor-binding sites (tfbs), mutsig genes and familial syndrome cancer genes (methods; supplementary data 3). we then compared the frequency of the annotated somatic mutations across the three reprogramming methods using […]

2015
PMCID: 4552571
PMID: 26192918
DOI: 10.1038/ng.3343

[…] alignment/map (bam) files were deposited in the database of genotypes and phenotypes (phs000598)., competing financial interests: , the authors declare no competing financial interests., urls , mutsig algorithm, http://confluence.broadinstitute.org/display/cgatools/mutsig; ccds, http://www.ncbi.nlm.nih.gov/ccds/; broad institute picard sequencing pipeline, […]

MutSig institution(s)
The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Instituto Nacional de Medicina Genómica, Mexico City, Mexico; Yale Cancer Center, Department of Hematology, New Haven, CT, USA; Massachusetts General Hospital, Boston, MA, USA; Brigham and Women’s Hospital, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA; Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel; Boston Children’s Hospital, Boston, MA, USA; Children’s Hospital, Philadelphia, PA, USA; Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, NIH, DHHS, Durham, NC, USA; Department of Pediatric Oncology, Hospital Sant Joan de Déu, Barcelona, Spain; Genome Sciences, University of Washington, Seattle, WA, USA
MutSig funding source(s)
This work was supported as part of The Cancer Genome Atlas (TCGA), a project of the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI) and as part of the Slim Initiative for Genomic Medicine (SIGMA), a joint U.S.-Mexico project founded by the Carlos Slim Health Institute, and the Intramural Research Program of the NIEHS (NIH, DHHS) project ES065073.

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