Question: Differential expression with CQN normalized RNA-seq data
0
gravatar for swkim
5.4 years ago by
swkim20
Korea, Republic Of
swkim20 wrote:

Hello,

I am pretty much new to RNA-seq and wanted to ask a really basic question about differential expression analysis.

I have a set of CQN (conditional quantile normalization) normalized RNA-seq RPKM data (the are all matched-pairs like tumor vs. normal).

When we compare expression of a gene with control, we usually use a log-based fold change like log2(T/N). However, CQN values are already log2 based. So calculating a log-based fold change seems like taking logarithm twice. 

So, in this case, do we still take a log fold-change? or do different things like just using differences of those values?

Thank you all~

 

 

ADD COMMENTlink modified 5.4 years ago by Devon Ryan92k • written 5.4 years ago by swkim20
4
gravatar for Devon Ryan
5.4 years ago by
Devon Ryan92k
Freiburg, Germany
Devon Ryan92k wrote:

If the output of CQN is on the log2 scale, then just subtract the values (log2(A/B)==log2(A)-log2(B)).

Having said that, I've only ever used CQN with edgeR/DESeq2/limma, which will produce the log2(foldchange) for you. I wouldn't recommend inventing your own analysis without good reason.
 

ADD COMMENTlink modified 5.4 years ago • written 5.4 years ago by Devon Ryan92k

Thank you! I agree with you. Someone just gave me the log fold change result from CQN log2 scale data, so I wanted to double-check the result is inappropriately processed. 

 

ADD REPLYlink written 5.4 years ago by swkim20

Hi. You mention here that you use CQN together with limma. Could you maybe share how you do it, I don't think it's a default functionality, as in this post: https://support.bioconductor.org/p/56238/ Do you know any kind of resource that would help me get the two tools working together?

I know I'm resurrecting a very old post, but it's one of the only ones I found googling for using CQN together with limma.

ADD REPLYlink written 8 months ago by grzegorz.maciag0
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