[BioC] What RNA-Seq expression estimates to use for plotting to show voom/limma Differential expression
Gordon K Smyth
smyth at wehi.EDU.AU
Sat Feb 8 08:28:07 CET 2014
Dear Heather,
voom() outputs normalized log-cpm values. Just plot them.
For example after
v <- voom(y, design)
the log-cpm values are in v$E.
Best wishes
Gordon
> Date: Thu, 6 Feb 2014 15:27:59 -0800
> From: Heather Estrella <hestrella at regulusrx.com>
> To: "bioconductor at r-project.org" <bioconductor at r-project.org>
> Subject: [BioC] What RNA-Seq expression estimates to use for plotting
> to show voom/limma Differential expression
>
> HI Dr. Smyth,
>
> I am trying to find the appropriate mRNA expression level estimates to
> use for generating plots that demonstrate the differential expression
> statistics calculated from voom/limma. What do you recommend? FPKM plots
> don't always agree with my voom/limma results.
>
> For example, if the differential expression results from limma report a
> log Fold change of 2 for group A vs. group B, I want a plot (e.g.
> boxplot, bar graph, etc.) which visualizes this difference and also
> provides a realistic estimate of the expression level along the axis.
>
> If you have other types of visualization (or normalizations) that you
> prefer for showing estimated expression levels between groups that also
> demonstrate the limma differential expression trends, please share. I'm
> open to any ideas/suggestions that you have.
>
> Thanks,
> Heather
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