## ----results='hide', echo=FALSE, message=FALSE, warning=FALSE------------ set.seed(42) library(knitr) opts_knit$set( self.contained = TRUE, upload.fun = image_uri ) opts_chunk$set( dev = 'png', dpi = 300, out.width = "700px", out.height = "700px" ) ## ----eval=FALSE---------------------------------------------------------- # install.packages("BiocManager") # BiocManager::install("signeR") ## ----results='hide', message=FALSE--------------------------------------- library(signeR) ## ----eval=FALSE---------------------------------------------------------- # library(VariantAnnotation) # # # BSgenome, equivalent to the one used on the variant call # library(BSgenome.Hsapiens.UCSC.hg19) # # vcfobj <- readVcf("/path/to/a/file.vcf", "hg19") # mut <- genCountMatrixFromVcf(BSgenome.Hsapiens.UCSC.hg19, vcfobj) ## ----eval=FALSE---------------------------------------------------------- # library(rtracklayer) # # target_regions <- import(con="/path/to/a/target.bed", format="bed") # opp <- genOpportunityFromGenome(BSgenome.Hsapiens.UCSC.hg19, # target_regions, nsamples=nrow(mut)) ## ----eval=FALSE---------------------------------------------------------- # library(Rsamtools) # # # make sure /path/to/genome.fasta.fai exists ! # # you can use "samtools faidx" command to create it # mygenome <- FaFile("/path/to/genome.fasta") # # mut <- genCountMatrixFromVcf(mygenome, vcfobj) # opp <- genOpportunityFromGenome(mygenome, target_regions) # ## ------------------------------------------------------------------------ mut <- read.table(system.file("extdata","21_breast_cancers.mutations.txt", package="signeR"), header=TRUE, check.names=FALSE) opp <- read.table(system.file("extdata","21_breast_cancers.opportunity.txt", package="signeR")) ## ----eval=FALSE---------------------------------------------------------- # signatures <- signeR(M=mut, Opport=opp) ## ----eval=FALSE---------------------------------------------------------- # signatures <- signeR(M=mut, Opport=opp, nlim=c(2,11)) ## ----results='hide', message=FALSE--------------------------------------- signatures <- signeR(M=mut, Opport=opp, nsig=5, main_eval=100, EM_eval=50, EMit_lim=20) ## ----eval=FALSE---------------------------------------------------------- # BICboxplot(signatures) ## ----echo=FALSE, results='asis'------------------------------------------ cat(sprintf("\n",image_uri("Model_selection_BICs.png"))) ## ------------------------------------------------------------------------ Paths(signatures$SignExposures) ## ------------------------------------------------------------------------ SignPlot(signatures$SignExposures) ## ------------------------------------------------------------------------ SignHeat(signatures$SignExposures) ## ------------------------------------------------------------------------ ExposureBoxplot(signatures$SignExposures) ## ------------------------------------------------------------------------ ExposureBarplot(signatures$SignExposures) ## ------------------------------------------------------------------------ ExposureHeat(signatures$SignExposures) ## ------------------------------------------------------------------------ # group labels, respective to each row of the mutation count matrix BRCA_labels <- c("wt","BRCA1+","BRCA2+","BRCA1+","BRCA2+","BRCA1+","BRCA1+", "wt","wt","wt","wt","BRCA1+","wt","BRCA2+","BRCA2+","wt","wt","wt", "wt","wt","wt") diff_exposure <- DiffExp(signatures$SignExposures, labels=BRCA_labels) ## ------------------------------------------------------------------------ # pvalues diff_exposure$Pvquant ## ------------------------------------------------------------------------ # most exposed group diff_exposure$MostExposed ## ------------------------------------------------------------------------ # note that BRCA_labels [15],[20] and [21] are set to NA BRCA_labels <- c("wt","BRCA+","BRCA+","BRCA+","BRCA+","BRCA+","BRCA+","wt","wt", "wt","wt","BRCA+","wt","BRCA+",NA,"wt","wt","wt","wt",NA,NA) Class <- Classify(signatures$SignExposures, labels=BRCA_labels) ## ------------------------------------------------------------------------ # Final assignments Class$class # Relative frequencies of assignment to selected groups Class$freq # All assigment frequencies Class$allfreqs ## ------------------------------------------------------------------------ citation("signeR") ## ------------------------------------------------------------------------ sessionInfo() ## ------------------------------------------------------------------------ print(names(dev.cur()))