Merge: Merge microarray data sets

In metaOmic/preproc: Preprocessing of Normalized Gene Expression Data

Description

Merge microarray data sets in possibly irregular order.

Usage

Merge(datasets, name)

Arguments

datasets	a list of gene expression matrice or list of Study. object. Each row of the matrix (study@datasets[[i]]) is for one gene, each column is for one sample. The row names are gene symbols.
name	The name od the Study object that will be returened

Details

The gene expression data sets may be in possibly irregular order with different numbers of genes. This function is used to extract the common genes across studies. The merged data sets have the same genes in the same order.

Value

If dataset is a list of gene expression matrice, it returns a list of gene expression matrice after merging. Each matrix is for one study. Each row of the matrix is for one gene and each column is for one sample. The row names are gene symbols. If dataset is a list of Study object, it returns a Study object with multiple study type, and datasets would be a list of gene expression matrice after merging, clinicals would be a list of clinical data after merging.

Author(s)

Lin Wang, Schwannden Kuo

Examples

data(datasets.eg)
data(preproc.option)
SinglePreproc <- function(x) {
  x <- Annotate(dataset=x, id.type=ID.TYPE.probeID, platform=PLATFORM.hgu133plus2)
  x <- Impute(dataset=x)
  x <- PoolReplicate(dataset=x)
}
# Merge for list of expression matrix
datasets.eg <- lapply(datasets.eg, SinglePreproc)
res <- Merge(datasets=datasets.eg)
# Merge for list of Study
studies <- lapply(datasets.eg, function(dataset) {
             new("Study", name="test", dtype=DTYPE.microarray, datasets=list(dataset))
           })
res <- Merge(datasets=studies, name="mergedStudy")

metaOmic/preproc documentation built on May 22, 2019, 6:54 p.m.