teststat: Calculating F-Type Statistics To Test a General Linear...

In rmRNAseq: RNA-Seq Analysis for Repeated-Measures Data

Description

This function is to calculate F-type test statistics for a general linear hypothesis for each of G genes.

Usage

teststat(C.matrix, beta0 = NULL, regression.output, ncores = 1)

Arguments

C.matrix	is a list of matrix Ci in testing H0: Ci*beta = 0.
beta0	vector of the hypothesized value of beta, usually, beta0 is a 0 vector. The default option beta0 = NULL means that beta0 is a vector of 0.
regression.output	this is a data.frame containing the output of glsCAR1 function for all G genes.
ncores	number of cores for embarrassingly parallel procedure. Default value of ncores is 1.

Value

A matrix of dimension G X length(C.matrix) of F-similar test statistics

Examples

data(design)
beta0 <- NULL
regression.output <- res$ori.res$newlm[1:50,]
ncores <- 1
C.matrix <- list()
C.matrix[[1]] <- limma::makeContrasts(line2, levels = design)
C.matrix[[2]] <- limma::makeContrasts(time2, time6, time24, levels = design)
names(C.matrix) <- c("line2","time")
teststatout <- rmRNAseq:::teststat(C.matrix, beta0, regression.output, ncores)
head(teststatout)

rmRNAseq documentation built on Nov. 8, 2019, 5:06 p.m.