rmRNAseq (version 0.1.0)

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

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

# NOT RUN {
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)
# }

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