## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.align = 'left', fig.height = 5, fig.width = 10 ) ## ----setup, message=FALSE, warning=FALSE-------------------------------------- library(maftools) ## ----------------------------------------------------------------------------- #path to TCGA LAML MAF file laml.maf = system.file('extdata', 'tcga_laml.maf.gz', package = 'maftools') #clinical information containing survival information and histology. This is optional laml.clin = system.file('extdata', 'tcga_laml_annot.tsv', package = 'maftools') laml = read.maf(maf = laml.maf, clinicalData = laml.clin, verbose = FALSE) ## ----------------------------------------------------------------------------- #By default the function plots top20 mutated genes oncoplot(maf = laml, draw_titv = TRUE) ## ----------------------------------------------------------------------------- #One can use any colors, here in this example color palette from RColorBrewer package is used vc_cols = RColorBrewer::brewer.pal(n = 8, name = 'Paired') names(vc_cols) = c( 'Frame_Shift_Del', 'Missense_Mutation', 'Nonsense_Mutation', 'Multi_Hit', 'Frame_Shift_Ins', 'In_Frame_Ins', 'Splice_Site', 'In_Frame_Del' ) print(vc_cols) oncoplot(maf = laml, colors = vc_cols, top = 10) ## ---- fig.height=5,fig.width=10, fig.align='left'----------------------------- #GISTIC results LAML all.lesions = system.file("extdata", "all_lesions.conf_99.txt", package = "maftools") amp.genes = system.file("extdata", "amp_genes.conf_99.txt", package = "maftools") del.genes = system.file("extdata", "del_genes.conf_99.txt", package = "maftools") scores.gis = system.file("extdata", "scores.gistic", package = "maftools") #Read GISTIC results along with MAF laml.plus.gistic = read.maf( maf = laml.maf, gisticAllLesionsFile = all.lesions, gisticAmpGenesFile = amp.genes, gisticDelGenesFile = del.genes, gisticScoresFile = scores.gis, isTCGA = TRUE, verbose = FALSE, clinicalData = laml.clin ) ## ---- fig.align='left',fig.height=5,fig.width=10, eval=T, fig.align='left'---- oncoplot(maf = laml.plus.gistic, top = 10) ## ----------------------------------------------------------------------------- set.seed(seed = 1024) barcodes = as.character(getSampleSummary(x = laml)[,Tumor_Sample_Barcode]) #Random 20 samples dummy.samples = sample(x = barcodes, size = 20, replace = FALSE) #Genarate random CN status for above samples cn.status = sample( x = c('ShallowAmp', 'DeepDel', 'Del', 'Amp'), size = length(dummy.samples), replace = TRUE ) custom.cn.data = data.frame( Gene = "DNMT3A", Sample_name = dummy.samples, CN = cn.status, stringsAsFactors = FALSE ) head(custom.cn.data) laml.plus.cn = read.maf(maf = laml.maf, cnTable = custom.cn.data, verbose = FALSE) oncoplot(maf = laml.plus.cn, top = 5) ## ---- fig.height=7,fig.width=10, eval=T, fig.align='left'--------------------- #Selected AML driver genes aml_genes = c("TP53", "WT1", "PHF6", "DNMT3A", "DNMT3B", "TET1", "TET2", "IDH1", "IDH2", "FLT3", "KIT", "KRAS", "NRAS", "RUNX1", "CEBPA", "ASXL1", "EZH2", "KDM6A") #Variant allele frequcnies (Right bar plot) aml_genes_vaf = subsetMaf(maf = laml, genes = aml_genes, fields = "i_TumorVAF_WU", mafObj = FALSE)[,mean(i_TumorVAF_WU, na.rm = TRUE), Hugo_Symbol] colnames(aml_genes_vaf)[2] = "VAF" head(aml_genes_vaf) #MutSig results (Right bar plot) laml.mutsig = system.file("extdata", "LAML_sig_genes.txt.gz", package = "maftools") laml.mutsig = data.table::fread(input = laml.mutsig)[,.(gene, q)] laml.mutsig[,q := -log10(q)] #transoform to log10 head(laml.mutsig) oncoplot( maf = laml, genes = aml_genes, leftBarData = aml_genes_vaf, leftBarLims = c(0, 100), rightBarData = laml.mutsig, rightBarLims = c(0, 20) ) ## ----------------------------------------------------------------------------- getClinicalData(x = laml) ## ----------------------------------------------------------------------------- oncoplot(maf = laml, genes = aml_genes, clinicalFeatures = 'FAB_classification') ## ----------------------------------------------------------------------------- #Color coding for FAB classification fabcolors = RColorBrewer::brewer.pal(n = 8,name = 'Spectral') names(fabcolors) = c("M0", "M1", "M2", "M3", "M4", "M5", "M6", "M7") fabcolors = list(FAB_classification = fabcolors) print(fabcolors) oncoplot( maf = laml, genes = aml_genes, clinicalFeatures = 'FAB_classification', sortByAnnotation = TRUE, annotationColor = fabcolors ) ## ----------------------------------------------------------------------------- oncoplot(maf = laml, genes = aml_genes, additionalFeature = c("Tumor_Seq_Allele2", "C")) ## ----------------------------------------------------------------------------- getFields(x = laml) ## ----------------------------------------------------------------------------- oncoplot(maf = laml, pathways = "auto", gene_mar = 8, fontSize = 0.6) ## ----------------------------------------------------------------------------- pathways = data.frame( Genes = c( "TP53", "WT1", "PHF6", "DNMT3A", "DNMT3B", "TET1", "TET2", "IDH1", "IDH2", "FLT3", "KIT", "KRAS", "NRAS", "RUNX1", "CEBPA", "ASXL1", "EZH2", "KDM6A" ), Pathway = rep(c( "TSG", "DNAm", "Signalling", "TFs", "ChromMod" ), c(3, 6, 4, 2, 3)), stringsAsFactors = FALSE ) head(pathways) oncoplot(maf = laml, pathways = pathways, gene_mar = 8, fontSize = 0.6) ## ---- fig.height = 8, fig.width = 10------------------------------------------ oncoplot( maf = laml.plus.gistic, draw_titv = TRUE, pathways = pathways, clinicalFeatures = c('FAB_classification', 'Overall_Survival_Status'), sortByAnnotation = TRUE, additionalFeature = c("Tumor_Seq_Allele2", "C"), leftBarData = aml_genes_vaf, leftBarLims = c(0, 100), rightBarData = laml.mutsig[,.(gene, q)], ) ## ----------------------------------------------------------------------------- sessionInfo()