Advice for the following PCA analysis
Hello there, I am running RNA-seq analysis on the following data: I am comparing 4 different conditions (WT-treated, WT-untreated, KO-treated, KO-untreated) and I think the following PCA is affected by a batch effect.
red=KO-untreated
green=KO-treated
blue=WT-untreated
violet=WT-treated
First of all, can you confirm that there might be this kind of bias? Secondly, how would you recommend to proceed?
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Can u also provide the legend?
And can u please elaborate more on green and violet? They are both KO-treated, what is the difference between them?
Sorry, I have just edited the legend
Yes, there is clear 'bias' as evidenced by the variation explained by PC1. I put the word 'bias' in apostrophes because, by the off chance, there may be a biological explanation for the finding.
Were those samples processed on a different batch?; are they the KO or WT? There is no legend in your plot.
Edit: thanks for editing your post to define the groupings
very sorry about that. I have just edited the legend.
If they are just a different batch, then just include
batchas a variable in the design model, assuming that you're running DESeq2. That will most likely mitigate the batch effect.Hi Kevin, yep I have done that using sva.
For Kevin( hope he will read it, since I am not able to write another reply for the next 24 hours). So, let's see if I have understood your suggestion correctly. Instead of doing this:
You are suggesting me to type this(?):
Thanks for your help Kevin. I am afraid I have just one column with all the possible condition KO_CTL, KO_TRE, WT_CTL, WT_TRE. My resultsName(dds) is
probably, I am doing something wrong.
That seems to have improved it. Can you nevertheless just include
batchas a covariate in the DESeq2 design model. I am almost certain that that will mitigate the effect that you see (if indeed those samples on the right-hand-side of your plot are from a different batch).Hi, I can see your edited post. Why do you have 3 batch variables? There should be just a single batch variable. Your parameters should be something like this:
Then use:
You could also merge Treatment and Group into a single variable with
paste(), if you wish.