calcTStatFast {sigPathway}R Documentation

Compute T-Statistics and Corresponding P-Values

Description

Computes t-statistics and corresponding p-values.

Usage

calcTStatFast(tab, phenotype, ngroups = 2)

Arguments

tab a numeric matrix of expression values, with the rows and columns representing probe sets and sample arrays, respectively
phenotype a numeric vector indicating the phenotype
ngroups an integer indicating the number of groups in the expression matrix

Details

If there are two groups in the matrix, then the phenotype vector should only consist of 0 and 1 to denote which sample columns belong to which group.

If ngroups = 2, the t-test done here is equivalent to a unpaired two-sample t-test, assuming unequal variances.

If there is only one group in the matrix (e.g., Alzheimer's data set as reanalyzed in Tian et al. (2005)), then the phenotype vector should consist of continuous values. In this case, the association between phenotype and expression values is first calculated as Pearson correlation coefficients, transformed to Fisher's z, and then rescaled so that its variance is 1:

z = 0.5*log((1+rho)/(1-rho))*sqrt(n-3), where n is the number of phenotypes.

Value

pval A vector of unadjusted p-values
tstat A vector of t-statistics (ngroups = 2) or rescaled Fisher's z (ngroups = 1)
rho (Also returned when ngroups = 1) A vector of Pearson correlation coefficients

Author(s)

Weil Lai

Examples

## Load inflammatory myopathy data set
data(MuscleData)

## Create appropriate variables for 
tab <- MuscleData[, c(index.IBM, index.NORM)]
phenotype <- c(rep(0,length(index.IBM)), rep(1,length(index.NORM)))
statList <- calcTStatFast(tab, phenotype, ngroups = 2)

## Generate histogram of p-values
hist(statList$pval, xlab = "Unadjusted p-values", ylab = "Frequency")

[Package sigPathway version 1.1-2 Index]