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MAFDash
Cuz once you’ve called the variants, it’s a MAF dash to the finish line
Example
Here are some example dashboards created using TCGA data:
Scope
Mutation Annotation Format (MAF) is a tabular data format used for storing genetic mutation data. For example, The Cancer Genome Atlas (TCGA) project has made MAF files from each project publicly available.
This repo – MAFDash – contains a set of R tools to easily create an HTML dashboard to summarize and visualize data from MAF file.
The resulting HTML file serves as a self-contained report that can be used to explore the result. Currently, MAFDash produces mostly static plots powered by maftools, ComplexHeatmap and circlize, as well as interactive visualizations using canvasXpress and plotly. The report is generated with a parameterized R Markdown script that uses flexdashboard to arrange all the information. I hope to add more interactivity
This repo is a companion to a Shiny app I made, MAFWiz. Instead of relying on a Shiny server, this dashboard is an attempt to try some of those things using client-side javascript functionality.
Making a MAFDash
The MAFDash.Rmd file can be rendered in R using the rmarkdown library like this:
# MAF data
maf_file="/path/to/maf/file"
# [Optional] A string to use as a title for the dashboard
title_label="My Title for the MAF Report"
# Path to the Rmd script
rmd_filename="scripts/MAFDash.Rmd"
# Make a filename for the output HTML
html_filename=gsub(".Rmd",".html",basename(rmd_filename))
# Render the report
rmarkdown::render(rmd_filename,
knit_root_dir=getwd(),
output_format="all", output_file=html_filename,
params = list(
maffile=maf_file,
titletext=title_label
))
Details
maf_filecan be anything that’s accepted by maftools’sread.maffunction (path to a file, or aMAF,data.frame, ordata.tableobject)- The
make_tcga_maf.Rscript contains a full example of how to render the Rmd file.
Required libraries
Here’s some code that will try to install required libraries that are not already installed (from my Gist about this)
all_pkgs<-c("rmarkdown",
"knitr",
"flexdashboard",
"htmltools",
"DT",
"bsplus",
"crosstalk",
"plotly",
"canvasXpress",
"maftools",
"dplyr",
"ComplexHeatmap",
"circlize",
"RColorBrewer",
"ggbeeswarm")
### Figure out which ones are available in Bioconductor and install any new that are not already present
bioc_universe <- BiocManager::available()
bioc_packages <- intersect(bioc_universe, pkglist)
print(paste0(length(bioc_packages), " of ", length(pkglist), " packages found in Bioconductor."))
bioc_packages <- bioc_packages[!(bioc_packages %in% installed.packages()[,"Package"])]
print(paste0("Installing ",length(bioc_packages), " new packages from Bioconductor..."))
if(length(bioc_packages)) BiocManager::install(bioc_packages)
### Figure out which ones are available in CRAN and install any new that are not already present
cran_universe <- available.packages(repos="https://cloud.r-project.org")[,"Package"]
cran_packages <- intersect(cran_universe, pkglist)
print(paste0(length(cran_packages), " of ", length(pkglist), " packages found in CRAN."))
cran_packages <- cran_packages[!(cran_packages %in% installed.packages()[,"Package"])]
print(paste0("Installing ",length(cran_packages), " new packages from CRAN..."))
if(length(cran_packages)) install.packages(cran_packages, repos="https://cloud.r-project.org")
Session Info
I’ve created and tested this using R 3.6.2. Here’s the complete sessionInfo
R version 3.6.2 (2019-12-12)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.6
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] grid stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggbeeswarm_0.6.0 circlize_0.4.11 RColorBrewer_1.1-2 ComplexHeatmap_2.2.0 canvasXpress_1.29.6 TCGAbiolinks_2.14.1
[7] maftools_2.2.10 knitr_1.30 bsplus_0.1.2 htmltools_0.5.0 DT_0.16 flexdashboard_0.5.2
[13] crosstalk_1.1.0.1 dplyr_1.0.2 plotly_4.9.2.1 ggplot2_3.3.2
loaded via a namespace (and not attached):
[1] R.utils_2.10.1 tidyselect_1.1.0 RSQLite_2.2.1 AnnotationDbi_1.48.0
[5] htmlwidgets_1.5.2 BiocParallel_1.20.1 DESeq_1.38.0 munsell_0.5.0
[9] codetools_0.2-18 withr_2.3.0 colorspace_1.4-1 Biobase_2.46.0
[13] rstudioapi_0.12 stats4_3.6.2 ggsignif_0.6.0 labeling_0.4.2
[17] GenomeInfoDbData_1.2.2 hwriter_1.3.2 KMsurv_0.1-5 parsetools_0.1.3
[21] bit64_4.0.5 downloader_0.4 vctrs_0.3.4 generics_0.1.0
[25] xfun_0.19 ggthemes_4.2.0 BiocFileCache_1.10.2 EDASeq_2.20.0
[29] R6_2.5.0 doParallel_1.0.16 GenomeInfoDb_1.22.1 clue_0.3-57
[33] locfit_1.5-9.4 bitops_1.0-6 DelayedArray_0.12.3 assertthat_0.2.1
[37] promises_1.1.1 scales_1.1.1 beeswarm_0.2.3 gtable_0.3.0
[41] sva_3.34.0 rlang_0.4.8 pkgcond_0.1.0 genefilter_1.68.0
[45] GlobalOptions_0.1.2 splines_3.6.2 rtracklayer_1.46.0 rstatix_0.6.0
[49] lazyeval_0.2.2 wordcloud_2.6 selectr_0.4-2 broom_0.7.2
[53] BiocManager_1.30.10 yaml_2.2.1 reshape2_1.4.4 abind_1.4-5
[57] GenomicFeatures_1.38.2 backports_1.2.0 httpuv_1.5.4 purrrogress_0.1.1
[61] tools_3.6.2 ellipsis_0.3.1 BiocGenerics_0.32.0 Rcpp_1.0.5
[65] plyr_1.8.6 progress_1.2.2 zlibbioc_1.32.0 purrr_0.3.4
[69] RCurl_1.98-1.2 prettyunits_1.1.1 ggpubr_0.4.0 openssl_1.4.3
[73] GetoptLong_1.0.4 S4Vectors_0.24.4 zoo_1.8-8 cluster_2.1.0
[77] SummarizedExperiment_1.16.1 haven_2.3.1 ggrepel_0.8.2 magrittr_1.5
[81] data.table_1.13.2 openxlsx_4.2.3 survminer_0.4.8 matrixStats_0.57.0
[85] aroma.light_3.16.0 hms_0.5.3 mime_0.9 evaluate_0.14
[89] xtable_1.8-4 XML_3.99-0.3 rio_0.5.16 jpeg_0.1-8.1
[93] readxl_1.3.1 shape_1.4.5 IRanges_2.20.2 gridExtra_2.3
[97] testthat_3.0.0 compiler_3.6.2 biomaRt_2.42.1 tibble_3.0.4
[101] crayon_1.3.4 R.oo_1.24.0 mgcv_1.8-33 later_1.1.0.1
[105] tidyr_1.1.2 geneplotter_1.64.0 postlogic_0.1.0.1 lubridate_1.7.9
[109] DBI_1.1.0 dbplyr_2.0.0 rappdirs_0.3.1 ShortRead_1.44.3
[113] Matrix_1.2-18 car_3.0-10 readr_1.4.0 cli_2.1.0
[117] R.methodsS3_1.8.1 parallel_3.6.2 GenomicRanges_1.38.0 forcats_0.5.0
[121] pkgconfig_2.0.3 km.ci_0.5-2 GenomicAlignments_1.22.1 foreign_0.8-76
[125] testextra_0.1.0.1 xml2_1.3.2 foreach_1.5.1 annotate_1.64.0
[129] vipor_0.4.5 XVector_0.26.0 rvest_0.3.6 stringr_1.4.0
[133] digest_0.6.27 Biostrings_2.54.0 rmarkdown_2.5 cellranger_1.1.0
[137] survMisc_0.5.5 edgeR_3.28.1 curl_4.3 shiny_1.5.0
[141] Rsamtools_2.2.3 rjson_0.2.20 lifecycle_0.2.0 nlme_3.1-150
[145] jsonlite_1.7.1 carData_3.0-4 viridisLite_0.3.0 askpass_1.1
[149] limma_3.42.2 fansi_0.4.1 pillar_1.4.6 lattice_0.20-41
[153] fastmap_1.0.1 httr_1.4.2 survival_3.2-7 glue_1.4.2
[157] zip_2.1.1 png_0.1-7 iterators_1.0.13 bit_4.0.4
[161] stringi_1.5.3 blob_1.2.1 latticeExtra_0.6-29 memoise_1.1.0