inst/doc/survtype.R

In survtype: Subtype Identification with Survival Data

## ---- 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)