Dear Matthew, Your question relates to the limma package. contrasts.fit() includes all information, including info on genes with missing values. You can use topTable() for example to rank genes, including those with missing values. However eBayes() does not compute F-statistics for genes with missing values. I agree that this is a restriction, but I don't have any plans to change it, because some methods in limma that use F-statistics expect to have full df. Personally, I like to preprocess microarray data so that missing values are not introduced in the first place. That would be one possible solution. Best wishes Gordon > Message: 1 > Date: Mon, 22 Sep 2008 11:01:14 -0700 > From: "Matt Lebo" <lebo at="" usc.edu=""> > Subject: [BioC] Missing Values in contrasts.fit > To: bioconductor at stat.math.ethz.ch > > Hi, > I am working on a time course series looking at expression differences > between males and females. We expect some genes to be sex- differentially > expressed at only some time points, and to show no expression at other time > points (i.e have missing values). When I use contrasts.fit to do an > ANOVA-like analysis to find genes with sex-differential expression, any gene > like this will not be analyzed. However, using the aov function in R, these > genes are analyzed. Is there any way to include these genes so they are > analyzed when using contrasts.fit? > > Thanks, > -- > Matthew Lebo > Molecular and Computational Biology > University of Southern California