MetaPCA (version 0.1.4)

DropDupGenes: MetaPCA: Meta-analysis in the Dimension Reduction of Genomic data

Description

When multiple probesets share the same gene symbols, select only the best probeset in terms of IQR

Usage

DropDupGenes(dat, isParallel=FALSE, nCores=NULL, na.rm=TRUE)

Arguments

dat

A gene expression matrix which has genes in rows and samples in columns.

isParallel

Whether to use multiple cores in parallel for fast computing. By default, it is false.

nCores

When isParallel is true, the number of cores can be set. By default, all cores in the machine are used in the unix-like machine, and 3 cores are used in windows.

na.rm

Whether to remove genes which have no annotation. Default is TRUE.

Value

A gene expression matrix which has unique genes in rows and samples in columns.

Details

References

Dongwan D. Kang and George C. Tseng. (2011) Meta-PCA: Meta-analysis in the Dimension Reduction of Genomic data.

See Also

Examples

	## Not run: 
# 	#One of example that shows how to generate a expression matrix used in the analysis
# 	requireAll(c('GEOquery', 'affy', 'hgu133plus2.db'))
# 	#It might be needed to download the source files first, and save it to local directory
# 	#such as "./data/Prostate/Varambally" in this example
# 	#ftp://ftp.ncbi.nih.gov/pub/geo/DATA/SeriesMatrix/GSE3325/GSE3325_series_matrix.txt.gz
# 	Varambally <- getGEO('GSE3325', destdir="./data/Prostate/Varambally")
# 	Varambally <- Varambally[[1]]
# 	Varambally.sLabel <- as.character(pData(Varambally)$title)
# 	Varambally.sLabel[grep("Benign",Varambally.sLabel)] <- "Normal"
# 	Varambally.sLabel[grep("primary",Varambally.sLabel)] <- "Primary"
# 	Varambally.sLabel[grep("Metastatic",Varambally.sLabel)] <- "Metastasis"
# 	Varambally <- exprs(Varambally)
# 	colnames(Varambally) <- Varambally.sLabel
# 	rownames(Varambally) <- unlist(mget(rownames(Varambally), hgu133plus2SYMBOL))
# 	Varambally <- DropDupGenes(Varambally, na.rm=TRUE)
# 	Varambally <- log2(Varambally)
# 	## End(Not run)