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mutationSeq specifications

Information


Unique identifier OMICS_00086
Name mutationSeq
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++, Python
Computer skills Advanced
Stability Stable
Requirements
numpy, scipy, matplotlib, scikit-learn, intervaltree
Maintained Yes

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Maintainer


  • person_outline Sohrab Shah <>

Publication for mutationSeq

mutationSeq citations

 (11)
library_books

Formalin fixation increases deamination mutation signature but should not lead to false positive mutations in clinical practice

2018
PMCID: 5919577
PMID: 29698444
DOI: 10.1371/journal.pone.0196434

[…] bwa [] and results filtered to remove all aligned reads with four or more mismatching bases or six or more soft clipped bases. single nucleotide variants (snv) were identified and annotated using mutationseq v4.3.8 [] in paired deep mode with criteria -v -q 30—coverage 100 -t 0.5. the complete list of snvs for all patient groups, is included in . reported snvs were then extracted […]

library_books

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

2018
PMCID: 5852328
PMID: 29552334
DOI: 10.1016/j.csbj.2018.01.003

[…] information is discarded and reads are assembled and re-aligned., machine learning methods have been very successful in classification, and variant calling is essentially a classification problem. mutationseq, somaticseq, snooper, and baysic , , , are representative variant callers that apply machine learning methods. mutationseq extracts relevant features on each site and trains four […]

library_books

Detection and genomic characterization of a mammary like adenocarcinoma

2017
PMCID: 5701302
PMID: 28877932
DOI: 10.1101/mcs.a002170

[…] tools (bbt) (). wgs variants identified using samtools v0.1.7 mpileup (). the tumor and normal samples were compared with identify somatic events. snvs were called using strelka v0.4.62 () and mutationseq v1.0.2 (). strelka v0.4.62 was also used to called small insertions and deletions. the somatic variant annotation was done with the ensemble database (v69), and the effect calculation […]

library_books

Engineered in vitro cell line mixtures and robust evaluation of computational methods for clonal decomposition and longitudinal dynamics in cancer

2017
PMCID: 5647443
PMID: 29044127
DOI: 10.1038/s41598-017-13338-8

[…] sample volumes were mixed and re-suspended with te buffer to obtain the required volume for qpcr., exome sequences were aligned using bwa and snvs were called using samtools in experiment 1 and mutationseq in experiment 2., the 2-step pcr sequencing method used primers that were designed as singleplex primers. chosen target positions were entered into primer3, an online program used […]

library_books

Enhancing knowledge discovery from cancer genomics data with Galaxy

2017
PMCID: 5437943
PMID: 28327945
DOI: 10.1093/gigascience/gix015

[…] somatic snvs. the ensembl_vcf tool receives the output of variant callers and selects variants detected by a user-specified number of tools. this example workflow runs four variant callers (strelka, mutationseq, radia and somaticsniper) and runs vcf2maf to annotate the resulting list of variants with support from a sufficient number of tools., additional file fig. s2 achieving parallelization […]

library_books

Small molecule epigenetic screen identifies novel EZH2 and HDAC inhibitors that target glioblastoma brain tumor initiating cells

2016
PMCID: 5312317
PMID: 27449082
DOI: 10.18632/oncotarget.10661

[…] were used to identify copy number aberrations and loss of heterozygosity respectively. for identification of single nucleotide variants, samtools (v1.0.2) was applied followed by filtering with mutationseq (v1.0.2), and the results were combined with variant called with strelka (v0.4.6.2). small indels were also identified using strelka. these variants were annotated using ensembl (v69). […]


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mutationSeq institution(s)
Department of Molecular Oncology, BC Cancer Agency, Vancouver, BC, Canada; Department of Computer Science, University of British Columbia, Vancouver, BC, Canada; Canada’s Michael Smith Genome Science Centre, University of British Columbia, Vancouver, BC, Canada; Department of Pathology, University of British Columbia, Vancouver, BC, Canada
mutationSeq funding source(s)
Supported by a Canadian Institutes for Health Research (CIHR) Catalyst Grant: Bioinformatics Approaches to Cancer Research, application #202452, the Canadian Breast Cancer Foundation, the Michael Smith Foundation for Health Research and by the OvCaRe - Clear Cell Project.

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