Description Usage Arguments Value Author(s) References Examples
View source: R/PreprocessMetaAnalysis.R
Preprocessing for microarray meta-analysis. It is about gene filtering and missing value imputation.
1 | PreprocessMetaAnalysis(DList, cutRatioByMean=.4, cutRatioByVar=.4, doImpute=FALSE, na.rm.pct=.1, na.rm.pct.each=.5, verbose=FALSE)
|
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. |
list object of all data matrices after filtering and imputation.
Don Kang (donkang75@gmail.com) and George Tseng (ctseng@pitt.edu)
Dongwan D. Kang and George C. Tseng. (2011) Meta-PCA: Meta-analysis in the Dimension Reduction of Genomic data.
1 2 3 4 5 6 | ## 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)
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