wrMisc (version 1.15.3.1)

test2factLimma: 2-Factorial Limma-Style t-Test

Description

The aim of this function is to provide convenient acces to two-factorial (linear) testing withing the framework of makeMAList including the emprical Bayes shrinkage. The input data 'datMatr' which should already be organized as limma-type MAList, eg using using makeMAList. Note: This function uses the Bioconductor package limma (which must be installed).

Usage

test2factLimma(
  datMatr,
  fac1,
  fac2,
  testSynerg = FALSE,
  testOrientation = "=",
  addResults = c("lfdr", "FDR", "Mval", "means"),
  addGenes = NULL,
  silent = FALSE,
  callFrom = NULL,
  debug = FALSE
)

Value

This function returns an object of class "MArrayLM" (from limma) containing/enriched by the testing results

Arguments

datMatr

matrix or data.frame with lines as indenpendent series of measures (eg different genes)

fac1

(character or factor) vector describing grouping elements of each line of 'datMatr' for first factor, must be of same langth as fac2

fac2

(character or factor) vector describing grouping elements of each line of 'datMatr' for second factor, must be of same langth as fac1

testSynerg

(logical) decide if factor-interactions (eg synergy) should be tested in model, otherwise additive factors are supposed

testOrientation

(character) default (or any non-recignized input) '=', otherwise either '>','gerater','sup','upper' or '<','inf','lower'

addResults

(character) vector defining which types of information should be included to output, may be 'lfdr','FDR' (for BY correction), 'Mval' (M values), 'means' (matrix with mean values for each group of replicates)

addGenes

(matrix or data.frame) additional information to add to output

silent

(logical) suppress messages

callFrom

(character) allow easier tracking of messages produced

debug

(logical) additional messages for debugging

See Also

makeMAList, single line testing lmFit and the eBayes-family of functions in package limma

Examples

set.seed(2014)
dat0 <- rnorm(30) + rep(c(10,15,19,20),c(9,8,7,6))
fa <- factor(rep(letters[1:4],c(9,8,7,6)))
dat2 <- data.frame(facA=rep(c("-","A","-","A"), c(9,8,7,6)),
  facB= rep(c("-","-","B","B"), c(9,8,7,6)), dat1=dat0, dat2=runif(30))
grpNa <- sub("-","",sub("\\.","", apply(dat2[,1:2], 1, paste, collapse="")))    
test2f <- test2factLimma(t(dat2[,3:4]), dat2$facA, dat2$facB)  
test2f     # just the p-values
# Similarly, you can easily summarize results using topTable from limma
if(requireNamespace("limma", quietly=TRUE)) {
  test2g <- test2factLimma(t(dat2[,3:4]), dat2$facA, dat2$facB, addR=FALSE)  
  library(limma)
  topTable(test2g, coef=1, n=5) 
  topTable(test2g, coef=2, n=5) }