[BioC] missing value handling in limma

xiaocui zhu xzhu at caltech.edu
Mon Jun 7 20:53:24 CEST 2004

Hi all,

I recently used the linear model fit in limma to rank differentially
expressed genes between treated vs. control with a data set. The data
includes three log2(Treated/Control) replicate sets, and a dyeSwap for
each replicate.   So the design matrix is c(1,-1,1,-1,1-1).  Among the
top rank genes, I noticed some of them have only one log2Ratio
measurement with the rest being "NA". I set the log2Ratio of a gene to
"NA", if its green or red intensity measurement is below background,
saturated, low intensity, or non-uniform.  I am wondering how the linear
model in limma handles missing values and why a gene with only one data
point is identified as a high ranking differentially expressed gene. 

Thank you for your help in advance!


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