[BioC] DESeq2 1.2.10 vs 1.5.26

[Michael Love]

hi Ido,

I can't see these images for some reason. Maybe you can forward them
as attachments to me?

You jumped from the October 2013 release to the current devel version,
and hence got a lot of improved estimates at once. Due to an
improvement in dispersion estimation from 1.2 to 1.4, the maximum
likelihood estimates in your dataset are now falling closer to the
line (variance of log dispersions of 0.711 instead of 0.977), and
hence the model "trusts" the fitted line more.

In the development branch (so from 1.4 to 1.5), we have made more
robust the estimate of the variance of the prior on log fold changes.
Note that the development branch is just that: for development. So if
you want more stability, you should use the release branch (v1.4).

best,

Mike


On Thu, Jul 17, 2014 at 11:20 AM, Ido Tamir <tamir at imp.ac.at> wrote:
> Hi,
>
> I tried to switch from DESeq2_1.2.10 (R3.0) to DESeq2_1.5.26 (R3.1)
>
> but it looks like it 1.5.26 is much more aggressive in the shrinking of the variance estimation.
> The rlog normalized fold changes are also very different.
>
> The dataset was generated with
>
> dds <-  makeExampleDESeqDataSet(n = 30000, m = 6, betaSD = 1.5)
>
> saved and worked on in 2 different R/DESeq2 versions.
>
> a)
> Now the obvious question is: is newer truthier?
>
> b)
> Is there a parameter to get similar estimates with the new version as in the old version.
> Some estimates are more robust now I read in the news e.g. Cooks distance, beta prior variance.
> But I don’t understand the large changes this entails for some estimates.
>
>
> thank you very much,
> ido
>
> dispersion estimate plot 3.0
> http://postimg.org/image/t3z7i27zz/
>
> dispersion estimate plot 3.1
> http://postimg.org/image/v9tickbgf
>
> log fc 3.1 vs 3.0
> http://postimg.org/image/mp06le1a7
>
> mean 3.1 vs 3.0 illustrating identical input data (< 100)
> http://postimg.org/image/hno76a4fz
>
> mean 3.1 vs 3.0 illustrating identical input data (all)
> http://postimg.org/image/wv46qmwan
>
> pvalue 3.1 vs 3.0
> http://postimg.org/image/7rn46mynz
>
> 3.0:
> attr(,"coefficients")
> asymptDisp  extraPois
>  0.1147892  5.3433952
> attr(,"fitType")
> [1] "parametric"
> attr(,"varLogDispEsts")
> [1] 0.9778035
> attr(,"expVarLogDisp")
> [1] 0.6449341
> attr(,"dispPriorVar")
> [1] 0.3328694
>
> 3.1:
> attr(,"coefficients")
> asymptDisp  extraPois
>  0.1117856  5.8477354
> attr(,"fitType")
> [1] "parametric"
> attr(,"varLogDispEsts")
> [1] 0.7119179
> attr(,"expVarLogDisp")
> [1] 0.6449341
> attr(,"dispPriorVar")
> [1] 0.25
>
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