MAF.survgroup: Patient group identification via survival data and mutation...

In survtype: Subtype Identification with Survival Data

Description

The groups of patients are identified according to whether the varints exist on a single gene. Survival difference between patients with and without mutations is compared.

Usage

MAF.survgroup(surv.data, time, status, maf, variants = NULL,
              sample.name = "Tumor_Sample_Barcode", gene.name = "Hugo_Symbol",
              variant.type = "Variant_Classification", num.genes = 10,
              siginificant.genes = 1, ...)

Arguments

surv.data	survival data
time	survival time
status	status indicator
maf	a MAF file
variants	types of varints on a single gene for mutated samples. samples with any mutations, defined as mutated samples by default.
sample.name	the column name containing sample names (defult: "Tumor_Sample_Barcode")
gene.name	the column name containing gene names (defult: "Hugo_Symbol")
variant.type	the column name containing variant types (defult: "Variant_Classification")
num.genes	the number of top genes based on the number of mutated genes (default: 10)
siginificant.genes	the number of top genes based on the statistical siginificance of mutated genes (default: 1)
...	additional parameters for the "ggsurvplot" for the statistically siginificant genes

Value

time	survival time
status	status indicator
surv.data	survival data
maf.matrix	a mutation matrix
summary	a list of number of samples with variants, chi-squared statistics and p-values
cluster	a vector of integers indicating the cluster to which each sample is assigned, for the most significant gene
fit	fitted survival curves, for the most significant gene

Author(s)

Dongmin Jung

See Also

survival::Surv, survival::survfit, survival::survdiff, survminer::ggsurvplot

Examples

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,
                                num.genes = 3, siginificant.genes = 1,
                                pval = TRUE)

survtype documentation built on Nov. 8, 2020, 7:24 p.m.