normalized input data for GAGE (R) - log-transformed or not?
2 answers
What are you using GAGE for (RNA-seq or microarray)?
For RNA-seq you can use log2 normalized data:
cnts=raw_gene_count_data
sel.rn=rowSums(cnts) != 0
cnts=cnts[sel.rn,]
libsizes=colSums(cnts)
size.factor=libsizes/exp(mean(log(libsizes)))
cnts.norm=t(t(cnts)/size.factor)
cnts.norm=log2(cnts.norm+8)
For microarray data, they use RMA/FARMS normalization in the vignette.
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You may use RMA, FARMS or other normalization methods. Array normalization usually does log(2) transformation too like in RMA and FARMS. If not, it is always advisable to do log2 or log transformation on array or RNA-Seq data for differential expression or pathway analysis.
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