mod.t.test {MKomics}

Moderated t-Test

Description

Performs moderated t-tests based on Bioconductor package limma.

Usage

mod.t.test(x, group = NULL, paired = FALSE, subject, adjust.method = "BH",
           sort.by = "none", na.rm = TRUE)

Arguments

x

a (non-empty) numeric matrix of data values.

group

an optional factor representing the groups.

paired

a logical indicating whether you want a paired test.

subject

factor with subject IDs; required if paired = TRUE.

adjust.method

see p.adjust

sort.by

see toptable

, where "logFC" corresponds to difference in means.

na.rm

logical. Should missing values (including NaN) be omitted from the calculations of group means?

Details

The function uses Bioconductor package limma to compute moderated t-tests. For more details we refer to ebayes.

Value

A data.frame with the results.

References

Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 43(7), e47.

See Also

t.test

Examples

## One-sample test
X <- matrix(rnorm(10*20, mean = 1), nrow = 10, ncol = 20)

mod.t.test(X)
## corresponds to
library(limma)
design <- matrix(1, nrow = ncol(X), ncol = 1)
colnames(design) <- "A"
fit1 <- lmFit(X, design)
fit2 <- eBayes(fit1)
topTable(fit2, coef = 1, number = Inf, confint = TRUE, sort.by = "none")[,-4]

## Two-sample test
set.seed(123)
X <- rbind(matrix(rnorm(5*20), nrow = 5, ncol = 20),
           matrix(rnorm(5*20, mean = 1), nrow = 5, ncol = 20))
g2 <- factor(c(rep("group 1", 10), rep("group 2", 10)))

mod.t.test(X, group = g2)
## corresponds to
design <- model.matrix(~ 0 + g2)
colnames(design) <- c("group1", "group2")
fit1 <- lmFit(X, design)
cont.matrix <- makeContrasts(group1vsgroup2="group1-group2", levels=design)
fit2 <- contrasts.fit(fit1, cont.matrix)
fit3 <- eBayes(fit2)
topTable(fit3, coef = 1, number = Inf, confint = TRUE, sort.by = "none")[,-4]

## Paired two-sample test
subjID <- factor(rep(1:10, 2))
mod.t.test(X, group = g2, paired = TRUE, subject = subjID)