calcTStatFast: Compute T-Statistics and Corresponding P-Values
In sigPathway: Pathway Analysis

Description Usage Arguments Details Value Author(s) Examples

Computes t-statistics and corresponding p-values.

1	calcTStatFast(tab, phenotype, ngroups = 2)

`tab`	a numeric matrix of expression values, with the rows and columns representing probe sets and sample arrays, respectively
`phenotype`	a numeric (or character if `ngroups` >= 2) vector indicating the phenotype
`ngroups`	an integer indicating the number of groups in the expression matrix

If there are two groups in the matrix, it is recommended to use 0 and 1 to denote which sample columns belong to which group. If the phenotype is a character vector, then the phenotype ranked first in the alphabet is considered as 0.

If ngroups = 2, the t-test done here is equivalent to a unpaired two-sample t-test, assuming unequal variances. Please note that as of version 1.1.6, the sign of the t-statistic is positive when the mean of group 1 is greater than the mean of group 0.

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.

If ngroups > 2, the f-statistics (from 1-way ANOVA) are calculated. The user will need to check that the data have similar variances among the groups.

`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

Weil Lai

## Load inflammatory myopathy data set
data(MuscleExample)
statList <- calcTStatFast(tab, phenotype, ngroups = 2)

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