wrProteo: extractTestingResults – R documentation

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extractTestingResults

Extract results from moderated t-tests

Description

This function allows convenient access to results produced using the functions moderTest2grp or moderTestXgrp. The user can define the threshold which type of multiple testing correction should be used (as long as the multiple testing correction method was actually performed as part of testing).

Usage

extractTestingResults(
  stat,
  compNo = 1,
  statTy = "BH",
  thrsh = 0.05,
  FCthrs = 1.5,
  annotCol = c("Accession", "EntryName", "GeneName"),
  nSign = 6,
  add = "allMeans",
  filename = NULL,
  fileTy = "csvUS",
  silent = FALSE,
  callFrom = NULL
)

Arguments

`stat`	('MArrayLM'-object or list) Designed for the output from `moderTest2grp` or `moderTestXgrp`
`compNo`	(integer) the comparison number/index to be used
`statTy`	(character) the multiple-testing correction type to be considered when looking for significant changes with threshold `thrsh` (depends on which have been run initially with `moderTest2grp` or `moderTestXgrp`)
`thrsh`	(numeric) the threshold to be applied on `statTy` for the result of the statistcal testing (after multiple testing correction)
`FCthrs`	(numeric) Fold-Change threshold given as Fold-change and NOT log2(FC), default at 1.5 (for filtering at M-value =0.585)
`annotCol`	(character) column-names from the annotation to be included
`nSign`	(integer) number of significant digits whe returning results
`add`	(character) additional groups to add (so far only "allMeans" available) in addition to the means used in the pairwise comparison
`filename`	(character) optional (path and) file-name for exporting results to csv-file
`fileTy`	(character) file-type to be used with argument `filename`, may be 'csvEur' or 'csvUS'
`silent`	(logical) suppress messages
`callFrom`	(character) allow easier tracking of message(s) produced

Value

limma-type MA-object (list)

Examples

grp <- factor(rep(LETTERS[c(3,1,4)],c(2,3,3)))
set.seed(2017); t8 <- matrix(round(rnorm(208*8,10,0.4),2), ncol=8,
  dimnames=list(paste(letters[],rep(1:8,each=26),sep=""), paste(grp,c(1:2,1:3,1:3),sep="")))
t8[3:6,1:2] <- t8[3:6,1:2] +3                    # augment lines 3:6 (c-f) 
t8[5:8,c(1:2,6:8)] <- t8[5:8,c(1:2,6:8)] -1.5    # lower lines 
t8[6:7,3:5] <- t8[6:7,3:5] +2.2                  # augment lines 
## expect to find C/A in c,d,g, (h)
## expect to find C/D in c,d,e,f
## expect to find A/D in f,g,(h) 
library(wrMisc)     # for testing we'll use this package
test8 <- moderTestXgrp(t8, grp) 
extractTestingResults(test8)

wrProteo

Proteomics Data Analysis Functions

v1.4.1

GPL-3

Authors

Wolfgang Raffelsberger [aut, cre]

Initial release