<img src="vignettes/maftools_hex.svg" align="left" height="140" /></a> ## maftools - An R package to summarize, analyze and visualize MAF files [](https://github.com/poisonalien/maftools/issues) [](https://github.com/PoisonAlien/maftools/actions) ## Introduction maftools is a comprehensive toolkit for processing somatic variants from cohort-based cancer genomic studies. maftools offers over 80 functions to perform the most commonly required tasks in cancer genomics, using [MAF](https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/) as the only input file type. ## Installation ```{r} #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](https://www.nejm.org/doi/full/10.1056/nejmoa1301689) as a case study can be found [here](http://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html). <p align="left"> <img src="https://user-images.githubusercontent.com/8164062/97981605-d8a59500-1dd2-11eb-9f5e-cc808f7b3f91.gif" height="320" height="400"> </p> ## Primary applications maftools is extremely easy to use, starting with importing an [MAF](https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/) file along with the associated clinical data. Once the data is successfully imported, the resulting MAF object can be passed to various functions. Key applications include: - [Cohort summarization using oncoplots](https://bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/oncoplots.html#08_Combining_everything) - [Identify co-occurring and mutually exclusive events](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#91_Somatic_Interactions) - [Clinical enrichment analysis](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#96_Clinical_enrichment_analysis) - [Detect cancer driver genes](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#92_Detecting_cancer_driver_genes_based_on_positional_clustering) - [Infer tumor heterogeneity](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#99_Tumor_heterogeneity_and_MATH_scores) - [Analyze known cancer signaling pathways](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#98_Oncogenic_Signaling_Pathways) - [De-novo somatic signature analysis with NMF](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#9103_Signature_analysis) - [Compare two cohorts to identify differentially mutated genes](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#95_Comparing_two_cohorts_(MAFs)) - [Perform survival analysis and predict genesets associated with survival](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#942_Predict_genesets_associated_with_survival) - [Drug-gene interactions](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#97_Drug-Gene_Interactions) Besides the MAF files, maftools can handle sequencing alignment BAM files, copy number output from GISTIC and mosdepth. Please refer to the package documentation sections below to learn more. - [Generate personalized cancer report](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/cancer_hotspots.html) for known somatic [hotspots](https://www.cancerhotspots.org/) - [Sample mismatch and relatedness analysis](https://bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html#12_Sample_swap_identification) - [Copy number analysis](https://bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/cnv_analysis.html) with [ASCAT](https://github.com/VanLoo-lab/ascat) and [mosdepth](https://github.com/brentp/mosdepth) Moreover, analyzing all 33 TCGA cohorts along with the harmonized clinical data is a breeze. - A single command [tcgaLoad](https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html#13_TCGA_cohorts) will import the desired TCGA cohort thereby avoiding costly time spent on data mining from public databases. - Please refer to an associated software package [TCGAmutations](https://github.com/PoisonAlien/TCGAmutations) that provides ready to use `MAF` objects for 33 TCGA cohorts and 2427 cell line profiles from CCLE - along with relevant clinical information for all sequenced samples. ## Citation **_Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP. 2018. Maftools: efficient and comprehensive analysis of somatic variants in cancer. [Genome Research](https://doi.org/10.1101/gr.239244.118). PMID: [30341162](https://www.ncbi.nlm.nih.gov/pubmed/?term=30341162)_** ## Useful links | File Fomats | Data portals | Annotation tools | |--------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------| | [Mutation Annotation Format](https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/) | [TCGA](http://cancergenome.nih.gov) | [vcf2maf](https://github.com/mskcc/vcf2maf) - for converting your VCF files to MAF | | [Variant Call Format](https://en.wikipedia.org/wiki/Variant_Call_Format) | [ICGC](https://docs.icgc.org/) | [annovar2maf](https://github.com/PoisonAlien/annovar2maf) - for converting annovar output files to MAF | | ICGC [Simple Somatic Mutation Format](https://docs.icgc.org/submission/guide/icgc-simple-somatic-mutation-format/) | [Broad Firehose](https://gdac.broadinstitute.org/) | [bcftools csq](https://samtools.github.io/bcftools/howtos/csq-calling.html) - Rapid annotations of VCF files with variant consequences | | | [cBioPortal](https://www.cbioportal.org/) | [Annovar](https://annovar.openbioinformatics.org/en/latest/) | | | [PeCan](https://pecan.stjude.cloud/) | [Funcotator](https://gatk.broadinstitute.org/hc/en-us/articles/360037224432-Funcotator) | | | [CIViC](https://civicdb.org/home) - Clinical interpretation of variants in cancer | | | | [DGIdb](http://www.dgidb.org/) - Information on drug-gene interactions and the druggable genome | | ## Useful packages/tools Below are some more useful software packages for somatic variant analysis * [TRONCO](https://github.com/BIMIB-DISCo/TRONCO) - Repository of the TRanslational ONCOlogy library (R) * [dndscv](https://github.com/im3sanger/dndscv) - dN/dS methods to quantify selection in cancer and somatic evolution (R) * [cloneevol](https://github.com/hdng/clonevol) - Inferring and visualizing clonal evolution in multi-sample cancer sequencing (R) * [sigminer](https://github.com/ShixiangWang/sigminer) - Primarily for signature analysis and visualization in R. Supports `maftools` output (R) * [GenVisR](https://github.com/griffithlab/GenVisR) - Primarily for visualization (R) * [comut](https://github.com/vanallenlab/comut) - Primarily for visualization (Python) * [TCGAmutations](https://github.com/PoisonAlien/TCGAmutations) - pre-compiled curated somatic mutations from TCGA cohorts (from Broad Firehose and TCGA MC3 Project) that can be loaded into `maftools` (R) * [somaticfreq](<https://github.com/PoisonAlien/somaticfreq>) - rapid genotyping of known somatic hotspot variants from the tumor BAM files. Generates a browsable/sharable HTML report. (C) *** #### Powered By * [data.table](https://github.com/Rdatatable/data.table/wiki) at [warp speed](https://en.wikipedia.org/wiki/Warp_drive)