Question: normalized input data for GAGE (R) - log-transformed or not?
0
gravatar for AdrijaK
2.9 years ago by
AdrijaK0
AdrijaK0 wrote:

Does GAGE package in R require log-transformed normalized expression values or "just" normalized expression values as an input?

ADD COMMENTlink modified 2.9 years ago by bigmawen310 • written 2.9 years ago by AdrijaK0
1
gravatar for informatics bot
2.9 years ago by
United States
informatics bot560 wrote:

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.

ADD COMMENTlink modified 2.9 years ago • written 2.9 years ago by informatics bot560

Thank you. Currently my input is RMA normalised microarray data. So I guess I can analyse this directly.

ADD REPLYlink written 2.9 years ago by AdrijaK0
0
gravatar for bigmawen
2.9 years ago by
bigmawen310
United States
bigmawen310 wrote:

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.

ADD COMMENTlink written 2.9 years ago by bigmawen310
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