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Old 03-19-2020, 10:47 PM   #1
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Location: Germany

Join Date: Jul 2019
Posts: 3
Default How do I differentiate outliers from in-group variations in a DESeq2 PCA plot?

I have a PCA plot (please see below) from DESeq2's
HTML Code:
plotPCA(vsd, intgroup=c("conditions"))
function. I have 9 samples distributed in to 3 groups of 3 biological replicates each. My reason for trying to visualise all on the same PCA plot is to see that samples from the same group (condition) cluster together and to see a separation between the clustered groups.

The PCA plot I have is does not appear as I expect and my samples spread out on the plot:

1-Can I just remove a sample which I deem is the outlier and perform a reclustering of the rest on the PCA?

2-What parameter can I use to declare that a point is an outlier rather than an in-group biological variation? From visual inspection, which sample could be an outlier?

3- Can I show a PCA plot where I have just two samples in a particular condition?

4-I also wish to find out if it is allowed to plot more than two groups of sample at a time on a PCA plot.

Thank you in advance for your kind hints.

Last edited by CharlesG; 03-19-2020 at 10:50 PM. Reason: pca plot added
CharlesG is offline   Reply With Quote

deseq2, pca plot, rnaseq clustering

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