[BioC] Gene filtering for differential expression (limma)

[Matjaž Hren]

Hello everyone!

We are dealing with a quite straightforward microarray experimental design on TIGR potato cDNA microarray. We 

Here is a brief description of the experiments: we hybridise virus-infected versus mock-infected potato plant RNA from several potato cultivars - each microarray is hybridised with RNA of the same cultivar - but there is no common reference (at least three biological replicates including dye swaps for each cultivar: balanced block design).

Scanning and image analysis was done with ArrayPro Analyzer (Media Cybernetics). We also performed initial quality control and spot filtering in that software to remove "bad spots". Although we are not experienced R users we are trying to carry on the further analysis with limma package. 

And here are some of the problems/questions regarding limma:

1. As advised we would like to reduce the number of the spots before differential expression analysis (limma) - filter out genes. Does anyone have any suggestions which criteria should be used for gene filtering after normalisation (we have already removed "bad quality spots")?

2. Can be multifactorial testing done in limma, or do you suggest any other package (we would like to compare response to viral infection in 4 cultivars)? Does anyone have any suggestions on the design and contrast matrices?


Thanks for any answers/comments,


Matjaz Hren and Spela Baebler



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National Institute of Biology
Dept. of Plant Physiology and Biotechnology
Ljubljana
SLOVENIA
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