In ashishjain1988/MAFDash: Create an HTML Dashboard to Visualize Data from MAF File

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  echo = TRUE,
  message = FALSE,
  warning = FALSE,
  fig.width=8, fig.height=5
)

Download TCGA data

Download MAF file using TCGABiolinks

MAFDash provides a wrapper function that tries to simplify retrieving data using TCGAbiolinks. Valid project codes can be viewed by running TCGAbiolinks::getGDCprojects() and checking the "tumor" column.

library(MAFDash)
library(TCGAbiolinks)
library(maftools)

tcga_code <- c("ACC","UVM")
#inputFolderPath <- paste0(tempdir()) ## This folder will be created if it doesn't exist 
caller = "mutect2"
title_label = paste0("TCGA-",tcga_code)

maf_files <- getMAFdataTCGA(tcga_code,variant_caller = caller)

Download clinical data using TCGABiolinks

# tcga_clinical <- getTCGAClinicalAnnotation#TCGAbiolinks::GDCquery_clinic(project = paste0("TCGA-",tcga_code), type = "clinical")
# tcga_clinical$Tumor_Sample_Barcode <- tcga_clinical$submitter_id
#defaultW <- getOption("warn")
#options(warn = -1)
tcga_clinical<-getTCGAClinicalAnnotation(cancerCodes = tcga_code)
#options(warn = defaultW)

Make a customized oncoplot

Filter data

The filterMAF function can be used to filter the MAF data in various ways. Importantly, by default, it will remove commonly occurring mutations that are often considered to be false position ( FLAG genes )

filtered_mafdata <- do.call("rbind",lapply(maf_files, function(maf_file){filterMAF(maf_file)}))

Add clinical data

The easiest way to add clinical annotations to the oncoplot is to add clinical data to the clinical.data slot of a MAF object before passing it to the generateOncoplot() function.

MAFDash also provides a function that defines reasonable colors for some common clinical annotations provided with TCGA datasets.

filtered_maf <- read.maf(filtered_mafdata, clinicalData = tcga_clinical$annodata,verbose = FALSE)
annotation_colors <- tcga_clinical$colorList

Make an annotated oncoplot

The add_clinical_annotations argument can be:

• A boolean indicating whether or not to add annotations built from the clinical.data slot of the MAF object. Columns with all missing values are ignored. Maximum number of annotations plotted is 10 (first 10 non-empty columns of clinical.data)
• A character vector of column names provided as clinical data

custom_onco <- generateOncoPlot(filtered_maf,add_clinical_annotations = TRUE,
                                clin_data_colors = tcga_clinical$colorList)
custom_onco

Make some other figures

TCGA Comparison

A lot of maftools's plots are base graphics, so they're drawn to a device and not returned. But we can simply save them to a file and provide the file path.

tcgaComparePlot<-generateTCGAComparePlot(maf = filtered_maf, cohortName = "test")
tcgaComparePlot$tcga_compare_plot

Chord Diagram of mutation co-occurrence

This function is built on top of maftools's somaticInteractions() function. It's just a different way of visualizing co-occurence or mutual exclusivity between genes.

#ribbonplot_file <- file.path(getwd(),"ribbon.pdf")
generateRibbonPlot(filtered_maf,save_name = NULL)

Plot similarity to COSMIC signatures

The function generateCOSMICMutSigSimHeatmap computes the cosine similarity of each individual signature against each COSMIC signature. The COSMIC signatures are also annotated using the etiologies behind the mutational signatures that were identified by analyzing thousands of whole-genome sequencing samples from TCGA. A crawler script was used to scrape the etiologies in the "Acceptance criteria" section of each signature page from COSMIC database v3.2.

library(ComplexHeatmap)
val<-generateCOSMICMutSigSimHeatmap(filtered_maf)
draw(val)

Render the dashboard

customplotlist <- list("summary_plot"=T,
                       "burden"=T,
                       "TCGA Comparison"=tcgaComparePlot$tcga_compare_plot,
                       "oncoplot"=T,
                       "Annotated Oncoplot"=custom_onco
                       )

## Filename to output to; if output directory doesn't exist, it will be created
html_filename=file.path(paste0(tempdir(),"/TCGA-UVM.custom.mafdash.html"))

## Render dashboard
getMAFDashboard(MAFfilePath = filtered_maf,
                plotList = customplotlist,
                outputFileName = html_filename, 
                outputFileTitle = "Customized Dashboard")

Output

The output can be seen here.

ashishjain1988/MAFDash documentation built on Feb. 9, 2023, 9:54 p.m.