runLimma: DEG analysis with limma in batch mode
In tgirke/longevityTools: Analysis tools for longevity research

Description Usage Arguments Value Author(s) Examples

The sampleList function extracts the sample comparisons (contrasts) from the CMAP annotation table and stores them as a list. The runLimma function performs the actual DEG analysis with the limma package for all comparisons defined by sampleList.

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sampleList(cmap, myby)

runLimma(df, comp_list, fdr = 0.05, foldchange = 1, verbose = TRUE, affyid=NULL)

`df`	`data.frame` containing normalized intensity values. Row names are the probe set identifiers of the corresponding Affymetrix chip.
`comp_list`	Sample comparison `list` generated by `sampleList`.
`fdr`	FDR cutoff filter value on scale between 0 to 1.
`foldchange`	log2 fold change filter.
`affyid`	If `affyid=NULL`, a binary DEG matrix will be returned; if `affyid` is assigned a character vector of Affy IDs, a list will be returned containing for each treatment the `topTable` output subsetted by the corresponding Affy IDs.
`verbose`	Function prints status output if `verbose=TRUE`, while `FALSE` suppresses it.
`cmap`	Input `data.frame` defining sample comparisons, such as CMAP annotation file (cmap_instances_02.txt).
`myby`	If `myby=CMP` the comparisons will consider only the compound information, while `myby=CMP_CELL` also the cell types used in the assyas.

Function sampleList returns a list of character vectors.

If affyid=NULL, the function runLimma returns a list with the following three components. DEG: binary matrix where DEGs meeting the cutoff settings are indicated by 1s; logFC: matrix with corresponding logFC values; FDR matrix with corresponding FDR values. If affyid is assigned a character vector of Affy IDs, then the function returns a list containing for each treatment the topTable output subsetted by the corresponding Affy IDs.

Thomas Girke

## Not run: 
## Generate CEL file list for treatment vs. control comparisons
cmap <- read.delim("./data/cmap_instances_02.txt", check.names=FALSE)
comp_list <- sampleList(cmap, myby="CMP") 
comp_list <- sampleList(cmap, myby="CMP_CELL") # includes cell type info

## Load normalized expression data
chiptype_dir <- unique(readRDS("./data/chiptype.rds"))
df1 <- readRDS(paste0("data/", chiptype_dir[1], "/", "all_mas5exprs.rds"))
df2 <- readRDS(paste0("data/", chiptype_dir[2], "/", "all_mas5exprs.rds"))
df3 <- readRDS(paste0("data/", chiptype_dir[3], "/", "all_mas5exprs.rds"))
affyid <- rownames(df1)[rownames(df1) 
df <- cbind(df1[affyid,], df2[affyid,], df3[affyid,])

## DEG analysis with Limma
degMA <- runLimma(df, comp_list, fdr=0.10, foldchange=1, verbose=TRUE) 


## End(Not run)