Question: Rna-Seq : Biological And Technical Replicates In Expression Analysis (Deseq)
2
gravatar for Nicolas Rosewick
5.6 years ago by
Belgium, Brussels
Nicolas Rosewick7.4k wrote:

Hi,

I've to analyze several RNA-Seq samples. I've samples from several runs, unstraned and straned, and several samples sequenced multiple times ( using different library kit ). I used htseq-count to have the read counts and want now to use DESeq to check for differential expression. So I've biological replicates and technical replicates (same sample sequences several times using a different lib kit. Is that correct ?).

So I did a design matrix. In my example, A.1 means sample A, sequencing 1. A.2 : sample A, sequencing 2,... So A is sequenced two times (One unstranded, one stranded), B three times (One unstranded, two stranded), C one time (one unstraned) and D one time (one stranded). ReplicateGroup is used to put together technical replicates.

designTable : 
Sample      Condition    Stranded   ReplicateGroup
A.1         Ctrl            No            A
B.1         Treated           No            B
C.1         Treated           No            C
A.2         Ctrl            Yes          A
B.2         Treated        Yes            B
B.3         Treated        Yes            B
D.1      Treated        Yes          D

After that I use DESeq. countTable is the read count matrix.

cdsFull = newCountDataSet( countTable, designTable )
cdsFull = estimateSizeFactors( cdsFull )
cdsFull = estimateDispersions( cdsFull )

But now I don't know how to fit a model on "condition" "stranded" and "replicateGroup".

like that ?

fit1 = fitNbinomGLMs( cdsFull, count ~ Condition + Stranded + ReplicateGroup )
fit0 = fitNbinomGLMs( cdsFull, count ~ Condition )
pvalsGLM = nbinomGLMTest( fit1, fit0 )
padjGLM = p.adjust( pvalsGLM, method="BH" )

Is it the good way to analyze technical replicated. I read that I have to merge them together.. but I don't think it's a good idea due to the fact that I use different library kits. So I'm stuck...

Thanks a lot in advance

N.

replicates biology deseq rna-seq • 4.2k views
ADD COMMENTlink modified 5.6 years ago by Charles Warden6.5k • written 5.6 years ago by Nicolas Rosewick7.4k
0
gravatar for Charles Warden
5.6 years ago by
Charles Warden6.5k
Duarte, CA
Charles Warden6.5k wrote:

Looks about right.

When I did a roughly similar analysis, I specified the sample IDs using rownames(). So, the matrix only included variables. However, this probably doesn't matter.

Also, I had to set estimateDispersions() method="blind". Otherwise, it didn't seem to work, even when there were replicates (although one of my variables was specifying paired samples, so this might not be a problem for you).

The model specification and comparison looks right.

Good luck!

ADD COMMENTlink written 5.6 years ago by Charles Warden6.5k
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 889 users visited in the last hour