Question: Can I replace the single end sequenced sample with the failed pair end sequenced sample in RNAseq experiment?
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gravatar for doanphuong19
4 months ago by
doanphuong190 wrote:

Hi all, I have a RNAseq experiment to measure gene expression with 3 treatment and 3 control, but one of my treatment failed, now I just have 2 treatment vs 3 control. My question is that can I take another treatment sequenced in single end read to replace for one of my failed treatment? I am just beginner and have no experience in this area. I am much appreciated for your help.

sequencing rna-seq forum • 150 views
ADD COMMENTlink modified 4 months ago by Devon Ryan96k • written 4 months ago by doanphuong190

The question is will it add noise or decrease noise. I think that the chance that a gene will be different between the two batches is higher than having a noisy reading in the other two treatments. So yeah, do it 2 vs 3, not too bad, depends on the experiment though.

ADD REPLYlink written 4 months ago by Asaf8.2k

Thank you very much Asaf, I forgot to mention that my 3 treatments and 3 controls are in pair end reading. Could you please don't mind explain how it depends on the experiment? Thanks a lot.

ADD REPLYlink written 4 months ago by doanphuong190

What Devon said.

ADD REPLYlink written 4 months ago by Asaf8.2k

Thanks a lot Asaf, Cheers,

ADD REPLYlink written 4 months ago by doanphuong190
2
gravatar for Devon Ryan
4 months ago by
Devon Ryan96k
Freiburg, Germany
Devon Ryan96k wrote:

The problem with adding samples post-hoc is that you're likely going to have a batch effect, due to different preparation dates. Sometimes you get lucky and this isn't a problem, but more often than not you're have a large number of genes different simply due to processing date in the lab. If your biological effect size is very large it may swamp out this effect. On the flip side, if your effect size is moderate or small then I would be very concerned that adding samples would simply increase noise and prevent you from finding anything significant.

Fewer more comparable samples is preferable to more less comparable samples.

ADD COMMENTlink written 4 months ago by Devon Ryan96k

Thank you very much Devon, I got what you mean, Cheers

ADD REPLYlink written 4 months ago by doanphuong190
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