compSelect: Given a dataframe of phenotypic information, use a variable...

In pearcedom/survivALL: Continuous Biomarker Assessment by Exhaustive Survival Analysis

Description

Given a dataframe of phenotypic information, use a variable (i.e. a single column) to define a patient subset of given proportion

Usage

compSelect(pheno, column, values, props)

Arguments

pheno	a phenotypic dataframe. Sample IDs must be assigned as rownames
column	the name of the column used to define the subset - e.g. "grade"
values	the values within column that you are defining by These must be categorical - e.g. c("+", "-")
props	The number of how many of each value in column to be returned. - e.g. c(50, 50). Note, be careful not to ask for more samples of a particular value than are available in the dataset

Value

A dataframe, which is the subset of pheno, with a specified proportion of each value found in column

Examples

library(survivALL)
data(nki_subset)
library(Biobase)
pheno <- pData(nki_subset)

compSelect(pheno, "grade", values = c(1, 2, 3), props = c(10, 10, 5))

#to manufacture composition from a continuous measure, first translate into a
#categorical equivalent, e.g.
age <- pheno$age
pheno$age_group <- ifelse(age < 40, "<40", ifelse(age < 50, "40-50", ">=50"))
compSelect(pheno, 
    "age_group", 
    values = c("<40", "40-50", ">=50"), 
    props = c(2, 5, 10))

pearcedom/survivALL documentation built on May 20, 2019, 2:26 p.m.