## ---- fig.align='center', message=FALSE, warning=FALSE, eval=TRUE-------- library(survtype) data(lung) lung.survtype <- Surv.survtype(lung, time = "time", status = "status") plot.survtype(lung.survtype, pval = TRUE) ## ---- fig.align='center', message=FALSE, warning=FALSE, eval=TRUE-------- data(ovarian) ovarian.survtype <- Surv.survtype(ovarian, time = "futime", status = "fustat") plot.survtype(ovarian.survtype, pval = TRUE) ## ---- fig.align='center', message=FALSE, warning=FALSE, eval=FALSE------- # DLBCLgenes <- read.csv("https://doi.org/10.1371/journal.pbio.0020108.sd012", header = FALSE) # DLBCLpatients <- read.csv("https://doi.org/10.1371/journal.pbio.0020108.sd013", header = FALSE) # colnames(DLBCLpatients) <- c("time", "status") # rownames(DLBCLpatients) <- colnames(DLBCLgenes) # plot.survtype(Single.survgroup(DLBCLpatients, time = "time", status = "status", DLBCLgenes[1,]), pval = TRUE) # # SE <- SummarizedExperiment(assays=SimpleList(expression = as.matrix(DLBCLgenes))) # DLBCL.survtype <- Exprs.survtype(DLBCLpatients, time = "time", status = "status", # assay(SE), num.genes = 50, # scale = "row", gene.sel = TRUE, # clustering_method = "ward.D2", # show_colnames = FALSE) # plot.survtype(DLBCL.survtype, pval = TRUE) ## ---- fig.align='center', message=FALSE, warning=FALSE, eval=FALSE------- # library(SummarizedExperiment) # library(TCGAbiolinks) # query <- GDCquery(project = "TCGA-LUAD", # data.category = "Gene expression", # data.type = "Gene expression quantification", # platform = "Illumina HiSeq", # file.type = "normalized_results", # experimental.strategy = "RNA-Seq", # legacy = TRUE) # GDCdownload(query, method = "api") # data <- GDCprepare(query) # exprs.LUAD <- assay(data) # # cancer only # exprs.LUAD <- exprs.LUAD[,which(substr(colnames(exprs.LUAD), 14, 15) == "01")] # clinic.LUAD <- GDCquery_clinic("TCGA-LUAD", "clinical") # # stage I only # clinic.LUAD <- clinic.LUAD[clinic.LUAD$tumor_stage %in% c("stage i", "stage ia", "stage ib"),] # rownames(clinic.LUAD) <- clinic.LUAD[,1] # clinic.LUAD <- clinic.LUAD[,c("days_to_last_follow_up", "vital_status")] # clinic.LUAD$vital_status <- ifelse(clinic.LUAD$vital_status == "dead", 1, 0) # # match TCGA ID # colnames(exprs.LUAD) <- substr(colnames(exprs.LUAD), 1, 12) # # filtering # keep <- rowMeans(exprs.LUAD) > 500 # exprs.LUAD <- exprs.LUAD[keep,] # # log2 transformation # exprs.LUAD <- log2(exprs.LUAD + 1) # # normalization # exprs.LUAD <- quantile_normalization(exprs.LUAD) # dim(exprs.LUAD) # LUAD.survtype <- Exprs.survtype(clinic.LUAD, time = "days_to_last_follow_up", # status = "vital_status", exprs.LUAD, # num.genes = 100, scale = "row", # gene.sel = FALSE, clustering_method = "ward.D2", # show_colnames = FALSE) # plot(LUAD.survtype, pval = TRUE, palette = c("#619CFF", "#F8766D")) # gene.clust(LUAD.survtype, 2, scale = "row", clustering_method = "ward.D2", # show_colnames = FALSE) # # VEGFA # VEGFA.survgroup <- Single.survgroup(LUAD.survtype$surv.data, # time = "days_to_last_follow_up", # status = "vital_status", # LUAD.survtype$exprs.data["VEGFA",], # group.names = c("High Expression", # "Low Expression")) # plot(VEGFA.survgroup, title = "VEGFA", pval = TRUE) ## ---- fig.align='center', message=FALSE, warning=FALSE, eval=TRUE-------- library(maftools) laml.maf <- system.file('extdata', 'tcga_laml.maf.gz', package = 'maftools', mustWork = TRUE) laml.clin <- system.file('extdata', 'tcga_laml_annot.tsv', package = 'maftools', mustWork = TRUE) laml.maf <- read.csv(laml.maf, sep = "\t") laml.clinical.data <- read.csv(laml.clin, sep = "\t", row.names = 1) index <- which(laml.clinical.data$days_to_last_followup == -Inf) laml.clinical.data <- laml.clinical.data[-index,] laml.clinical.data <- data.frame(laml.clinical.data) laml.survgroup <- MAF.survgroup(laml.clinical.data, time = "days_to_last_followup", status = "Overall_Survival_Status", laml.maf, variants = "Missense_Mutation", num.genes = 10, top.genes = 1, pval = TRUE) head(laml.survgroup$summary)