PreprocessMetaAnalysis: MetaPCA: Meta-analysis in the Dimension Reduction of Genomic...

In donkang75/MetaPCA: MetaPCA: Meta-analysis in the Dimension Reduction of Genomic data

Description

Preprocessing for microarray meta-analysis. It is about gene filtering and missing value imputation.

Usage

PreprocessMetaAnalysis(DList, cutRatioByMean=.4, cutRatioByVar=.4, doImpute=FALSE, na.rm.pct=.1, na.rm.pct.each=.5, verbose=FALSE)

Arguments

DList	A list of all data matrices; Each data name should be set as the name of each list element. Each data should be a numeric matrix that has genes in the rows and samples in the columns. Row names should be official gene symbols and column names be sample labels.
cutRatioByMean	Proportion of genes filtered by study-wise mean. Default is 40%.
cutRatioByVar	Proportion of genes filtered by study-wise variance. Default is 40%.
doImpute	Whether to impute missing genes. Default is TRUE, and default imputation method is knn.
na.rm.pct	Proportion of genes filtered by study-wise missing proportion. Default is 10%.
na.rm.pct.each	Proportion of genes filtered by each study's missing proportion. Default is 50%.
verbose	Whether to print logs. Default is FALSE.

Value

list object of all data matrices after filtering and imputation.

Author(s)

Don Kang ([e-mail]) and George Tseng ([e-mail])

References

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

Examples

## Not run: 
DList <- PreprocessMetaAnalysis(list(Yu=Yu, Lapointe=Lapointe, Tomlins=Tomlins, Varambally=Varambally), 
		cutRatioByMean=.1, cutRatioByVar=.1, doImpute=T, na.rm.pct=.2)
str(DList)

## End(Not run)

donkang75/MetaPCA documentation built on May 15, 2019, 10:41 a.m.