[BioC] remove microarray batch effects using Limma
Xie, Zhi (NIH/NHLBI) [E]
zhi.xie at nih.gov
Mon Oct 25 20:36:35 CEST 2010
Hi everyone,
I have some microarray data files containing two sets of samples in
normal and disease condition. I have tested that the data also contain
significant batch effects with hybridization time. However, the
positive hits I obtained using the following approaches are very
different (using the same cutoff value in decideTests function). I
think I am supposed to use the first approach but I am surprised to
see a big difference between the two approaches. could anyone help
figure out the reasons?
Thanks,
Zhi Xie
NIH/NHLBI
Here eset is the expression dataset after RMA function.
___________________
Approach 1:
# Consider batch effects in the model matrix
design<-model.matrix(~0+condition.factor+batch.factor)
# fit the linear model
fit<-lmFit(eset,design)
Then I create contrast matrix and compute coefficients and errors
using contrast.fit function
___________________
Approach 2:
# remove batch effects first
exp.eset.rm.batch<-removeBatchEffect(exprs(eset),batch.factor)
# only consider normal and disease conditions in the model matrix
design<-model.matrix(~0+condition.factor)
# fit the linear model
fit<-lmFit(eset.rm.batch,design)
where eset.rm.batch is the expression dataset containing expression
values from exp.eset.rm.batch table
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