survGroup: Predict genesets associated with survival

In thesushantpatil/maftools: Summarize, Analyze and Visualize MAF Files

Description

Predict genesets associated with survival

Usage

survGroup(
  maf,
  top = 20,
  genes = NULL,
  geneSetSize = 2,
  minSamples = 5,
  clinicalData = NULL,
  time = "Time",
  Status = "Status",
  verbose = TRUE
)

Arguments

maf	an MAF object generated by read.maf
top	If genes is NULL by default used top 20 genes
genes	Manual set of genes
geneSetSize	Default 2
minSamples	minimum number of samples to be mutated to be considered for analysis. Default 5
clinicalData	dataframe containing events and time to events. Default looks for clinical data in annotation slot of MAF.
time	column name contining time in clinicalData
Status	column name containing status of patients in clinicalData. must be logical or numeric. e.g, TRUE or FALSE, 1 or 0.
verbose	Default TRUE

Examples

laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools")
laml.clin <- system.file("extdata", "tcga_laml_annot.tsv", package = "maftools")
laml <- read.maf(maf = laml.maf,  clinicalData = laml.clin)
survGroup(maf = laml, top = 20, geneSetSize = 1, time = "days_to_last_followup", Status = "Overall_Survival_Status")

thesushantpatil/maftools documentation built on May 18, 2020, 9:54 p.m.