computeChiSquaredTest: Compute chi-squared test

In wikum/divergence: Divergence: Functionality for assessing omics data by divergence with respect to a baseline

Description

Given a binary or ternary data matrix with class associations of samples, computes chi-squared tests for each feature between given groups

Usage

computeChiSquaredTest(Mat, Groups, classes)

Arguments

Mat	Matrix of digitized binary or ternary data with each column corresponding to a sample and each row corresponding to a feature
Groups	Factor indicating class association of samples
classes	Vector of class labels; the test will be applied between the classes given.

Value

A data frame with columns 'statistic' and 'pval'.

Examples

baseMat = breastTCGA_Mat[, breastTCGA_Group == "NORMAL"]
dataMat = breastTCGA_Mat[, breastTCGA_Group != "NORMAL"]
seMat.base = SummarizedExperiment(assays=list(data=baseMat))
seMat = SummarizedExperiment(assays=list(data=dataMat))
div = computeUnivariateDigitization(
  seMat = seMat,
  seMat.base = seMat.base,
 parallel = TRUE
)
assays(seMat)$div = div$Mat.div
sel = which(colnames(seMat) %in% colnames(dataMat))
div.chi = computeChiSquaredTest(Mat=assays(seMat)$div, 
                                Groups=breastTCGA_ER[sel],
                                classes=c("Positive", "Negative"))

wikum/divergence documentation built on Sept. 17, 2021, 12:33 a.m.