## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) ## ---- eval=FALSE-------------------------------------------------------------- # # new S4 function (note the capital W) # ?Waterfall # # # older established function # ?waterfall ## ---- message=FALSE, tidy=TRUE------------------------------------------------ # set a seed set.seed(426) # load GenVisR into R library(GenVisR) ## ---- message=FALSE, tidy=TRUE------------------------------------------------ # get the disk location for maf test file testFileDir <- system.file("extdata", package="GenVisR") testFile <- Sys.glob(paste0(testFileDir, "/brca.maf")) # define the objects for testing mafObject <- MutationAnnotationFormat(testFile) ## ---- message=FALSE, tidy=TRUE------------------------------------------------ # get the disk location for test files testFileDir <- system.file("extdata", package="GenVisR") testFile <- Sys.glob(paste0(testFileDir, "/*.vep")) # define the object for testing vepObject <- VEP(testFile) ## ---- tidy=TRUE--------------------------------------------------------------- # get the disk location for test files testFileDir <- system.file("extdata", package="GenVisR") testFile <- Sys.glob(paste0(testFileDir, "/FL.gms")) # define the objects for testing gmsObject <- GMS(testFile) ## ---- tidy=TRUE, eval=FALSE--------------------------------------------------- # # view the samples from the VEP file # getSample(vepObject) ## ---- tidy=TRUE, warning=FALSE------------------------------------------------ waterfallPlot <- Waterfall(vepObject, recurrence=.40) ## ----eval=FALSE--------------------------------------------------------------- # # extract data by the slot name # getData(waterfallPlot, name="primaryData") # # # extract data by the slot index (same as above) # getData(waterfallPlot, index=1) ## ----eval=FALSE--------------------------------------------------------------- # # draw the plot # drawPlot(waterfallPlot) # # # draw the plot and save it to a pdf # pdf(file="waterfall.pdf", height=10, width=15) # drawPlot(waterfallPlot) # dev.off() ## ---- fig.keep='last', fig.width=10, fig.height=6.5, tidy=TRUE, warning=FALSE---- # draw a waterfall plot for the maf object drawPlot(Waterfall(vepObject, recurrence=.20)) ## ---- fig.keep='last', fig.width=10, fig.height=6.5, tidy=TRUE, warning=FALSE---- # show those genes which recur in 50% of the cohort for these 4 samples drawPlot(Waterfall(vepObject, recurrence=.50, samples=c("FLX0040Naive", "FLX0070Naive", "FLX0050Naive", "FLX0030Naive"))) ## ---- fig.keep='last', fig.width=10, fig.height=6.5, tidy=TRUE, warning=FALSE---- # define a coverage for each sample sampCov <- c("FLX0040Naive"=1.45e7, "FLX0070Naive"=1.39e7, "FLX0050Naive"=1.21e7, "FLX0030Naive"=1.3e7, "FLX0010Naive"=1.1e7) drawPlot(Waterfall(vepObject, recurrence=.50, coverage=sampCov, plotA="burden", plotATally="complex", drop=FALSE)) ## ---- fig.keep='last', fig.width=10, fig.height=6.5, tidy=TRUE, warning=FALSE---- # find which mutations are in the input data mutations <- getMutation(vepObject)$Conse # define a new color and hierarchy for mutations library(data.table) newHierarchy <- data.table("mutation"=c("splice_region_variant", "splice_acceptor_variant", "splice_donor_variant", "missense_variant", "stop_gained"), "color"=c("tomato1", "tomato2", "tomato3", "purple", "cyan")) # draw the plot drawPlot(Waterfall(vepObject, recurrence=.50, mutationHierarchy = newHierarchy, plotATally="complex", drop=FALSE)) ## ---- fig.keep='last', fig.width=10, fig.height=6.5, tidy=TRUE, warning=FALSE, message=FALSE---- # determine the appropriate BSgenome object to use from the vep header assembly <- getHeader(vepObject) assembly <- assembly[grepl("assembly", assembly$Info),] # load in the correct BSgenome object library(BSgenome.Hsapiens.UCSC.hg19) # create a MutSpectra plot drawPlot(MutSpectra(vepObject, BSgenome=BSgenome.Hsapiens.UCSC.hg19)) ## ---- fig.keep='last', fig.width=10, fig.height=6.5, tidy=TRUE, warning=FALSE, message=FALSE---- # determine the appropriate BSgenome object to use from the vep header assembly <- getHeader(vepObject) assembly <- assembly[grepl("assembly", assembly$Info),] # load in the correct BSgenome object library(BSgenome.Hsapiens.UCSC.hg19) # create a Rainfall plot drawPlot(Rainfall(vepObject, BSgenome=BSgenome.Hsapiens.UCSC.hg19)) ## ---- fig.keep='last', fig.width=10, fig.height=6.5, tidy=TRUE, warning=FALSE, message=FALSE---- # create a Rainfall plot limiting the chromosomes and samples plotted drawPlot(Rainfall(vepObject, BSgenome=BSgenome.Hsapiens.UCSC.hg19, sample=c("FLX0010Naive"), chromosomes=c("chr1", "chr2", "chr3"))) ## ---- message=FALSE, tidy=TRUE------------------------------------------------ sessionInfo()