rlog vs vst for outlier identification
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Bex • 0
@fa3421e0
Last seen 13 hours ago
United Kingdom

Hiya,

I have 110 samples and am looking at sample clustering. Using rlog it seems to show outliers, which if I removed then throws up further outliers and so on ... after each sequential removal and re-run. If I use VST it seems that these extreme outliers do not exist or at least are not as obvious when looking at the PCA. Reading around it looks like VST is recommended for sample clustering outlier identification - am I correct in this thinking or is it best to keep removing samples based on sequential rlog repeats until no obvious outliers exist anymore?

rlog DESeq2 vst outliers • 88 views
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@mikelove
Last seen 22 hours ago
United States

Yes, I recommend VST for PCA and outlier identification. There's another related thread just posted, and perhaps the rlog issue is related to a preponderance of low count features. Either way, I would stick to VST.

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Thank you for the quick reply will have a search for the other thread too. I have already filtered out counts <10 etc.... to reduce memory

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