Normalizing large scale RNA-seq datasets
1
0
Entering edit mode
zqzneptune • 0
@zqzneptune-12327
Last seen 4.7 years ago

I am currently processing large scale RNA-seq data from independent cohorts.

Is there a systematic strategy to normalize the TPM of each transcript so that the expression levels can be compared without concerning the batch effect?

Thanks!

 

deseq2 • 738 views
ADD COMMENT
1
Entering edit mode
@mikelove
Last seen 3 days ago
United States

A critical question here is if you are interested in making comparisons within cohorts (e.g. comparing disease vs normal across numerous studies, each with normal and disease samples), or across cohorts (e.g. this study has disease A, this other study has disease B). The first kind of comparison is called "balanced" while the second one is "confounded".

ADD COMMENT
0
Entering edit mode

The problem here tends to be the first scenario, where samples from the tissues are to be compared to generate hypothesis. Since, this is a "balanced" case, is the package "sva" one of the solutions?

ADD REPLY
0
Entering edit mode

Yes, sva is appropriate and a great normalization tool. You can make contrasts in limma as well after sva normalization. 

ADD REPLY

Login before adding your answer.

Traffic: 333 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6