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Compare RNAseq Data from two independent runs?
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2.8 years ago

Dear community,

I am new to RNA sequencing and unfortunately I don't know much about bioinformatics neither. I did send 6 samples to AGRF containing 2 experimental groups and a control (2 samples each group), which have been sequenced in one lane. Later we did another run with ten samples in one lane. There has been added a new experimental group (4 samples) and 2 new samples added two the 3 groups of the first sequencing (So from RNAseq1 plus RNAseq2: 3 experimental groups and a control group all containing 4 samples). I tested for DE with EdgeR, Voom and DEseq2 using Galaxy. I have been told that I shouldn't normalize my Data beforehand. If I put all the samples together I barely get any significant changes. But if I compare samples from the second run with the controls of the first run only, I get thousands of deferentially expressed genes. So there must be a difference between Run 1 and 2. So I am wondering now if it is just not a good idea to compare samples of different runs? Or can I do some kind of Normalization to make them more comparable?

Thaks in advance, Lena

RNA-Seq • 670 views
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15 months ago
Asaf 5.6k
Israel
  1. Try to figure out if the library preparation protocol was different between the batches, if it was indeed different that's not good.
  2. You can correct for batch effect in DESeq2
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Hi Asaf, thanks for your answer. It was a stranded mRNA library Prep (PolyA selection I think). Is that what you meant? I did inform AGRF that it is a top up from the first one, so I guess it was the same- in the stuff they sent me i just found 6395 RNA lib prep on both quotes.

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I don't know. You can ask for the specific protocol (you'll need it anyway). In addition, you can plot the samples using PCA to see if the second batch cluster together or with their biological relatives.

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2.2 years ago
theobroma22 ♦ 1.1k

You may have batch effects if the multiplexing for the lane was different between runs. You can try processing your data thru the SVA package available on Bioconductor.

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