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maftools - An R package to summarize, analyze and visualize MAF files

bioc bioc bioc GitHub closed issues R-CMD-check

Introduction

maftools provides a comprehensive set of functions for processing MAF files and to perform most commonly used analyses in cancer genomics. See here for a detailed usage and a case study.

Installation

#Install from Bioconductor repository
BiocManager::install("maftools")

#Install from GitHub repository
BiocManager::install("PoisonAlien/maftools")

Getting started: Vignette and a case study

A complete documentation of maftools using TCGA LAML as a case study can be found here.

Citation

Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP. 2018. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Research. PMID: 30341162

Useful links

File formats Data Portals Annotation tools
Mutation Annotation Format TCGA vcf2maf - for converting your VCF files to MAF
Variant Call Format ICGC Ensembl Variant Effect Predictor VEP
ICGC Simple Somatic Mutation Format Broad Firehose Annovar
cBioPortal Funcotator
CIViC - Clinical interpretation of variants in cancer
DGIdb - Information on drug-gene interactions and the druggable genome

Useful packages/tools

Below are some more useful software packages for somatic variant analysis

  • TRONCO - Repository of the TRanslational ONCOlogy library (R)
  • dndscv - dN/dS methods to quantify selection in cancer and somatic evolution (R)
  • cloneevol - Inferring and visualizing clonal evolution in multi-sample cancer sequencing (R)
  • sigminer - Primarily for signature analysis and visualization in R. Supports maftools output (R)
  • GenVisR - Primarily for visualization (R)
  • comut - Primarily for visualization (Python)
  • TCGAmutations - pre-compiled curated somatic mutations from TCGA cohorts (from Broad Firehose and TCGA MC3 Project) that can be loaded into maftools (R)
  • somaticfreq - rapid genotyping of known somatic hotspot variants from the tumor BAM files. Generates a browsable/sharable HTML report. (C)

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Summarize, Analyze and Visualize MAF files from TCGA or in-house studies.

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