[BioC] scholarly reference for "don't draw PCA/heatmap dendrograms on DEGs"

Cook, Malcolm MEC at stowers.org
Mon Dec 9 16:38:48 CET 2013


Nor do I have this, but I agree with your assertion.

Nonetheless, I wonder, on this topic....

Have you done either on ALL (not just DE) genes?  If so, do your replicates cluster?  Further, if so, do the distances between replicate clusters scale in any interesting way with condition (i.e. higher dose or better knockdown or longer exposure -> further away from untreated).   I think this can be taken as "evidence" for condition effects that you and your colleague should expect.  Do you agree with this?

I'm curious as to this esp as I have submitted such as supplemental figures in the past....



 >-----Original Message-----
 >From: bioconductor-bounces at r-project.org [mailto:bioconductor-bounces at r-project.org] On Behalf Of Aaron Mackey
 >Sent: Monday, December 09, 2013 7:19 AM
 >To: Bioconductor mailing list
 >Subject: [BioC] scholarly reference for "don't draw PCA/heatmap dendrograms on DEGs"
 >A colleague of mine is skeptical of my assertion that drawing sample-level
 >PCA plots and/or clustered heatmaps based only on differentially expressed
 >genes (DEGs) is a circular, self-fulfilling prophecy -- they assert that
 >there's no guarantee samples will cluster by condition (despite the fact
 >that the condition is exactly what drives selection of DEGs), and so hopes
 >to use the observed clustering as further "evidence" of the condition
 >effects.  Rather than spend more time trying to explain statistical
 >concepts, I was hoping to checkmate the argument with a nice Nature Methods
 >review or somesuch.  Any pointers?
 >Thanks in advance,
 >	[[alternative HTML version deleted]]
 >Bioconductor mailing list
 >Bioconductor at r-project.org
 >Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

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