[BioC] how to determine what kind of dispersion to use

[J [guest]]

Hello listserve,

Most analysis performed in edgeR rightfully assumes that the data is not Poisson and in fact follows a NB distribution. This information is important when shrinking the dispersions, however I was wondering if there was a graph or function in edgeR that I could make/use to determine what kind of dispersion (i.e. common, moderated tagwise) I need to apply in the exactTest function? 

I'm not doing a typical RNA-seq experiment (i.e. RIP-seq) so I would like to test which parts of the classic workflow are appropriate for what I'm doing. For instance, can I still use the same equation to figure out the prior.df, or will that not apply to RIP-seq? 

After doing some comparisons between the different functions and arguments within them I'm wondering if RIP-seq may pose a problem when trying to use the moderated dispersion since the reads in the untagged IP will generally be less than the IP samples. Does that seem like a possibility? 

Also for the dispersion argument in the exactTest() function, are there good rules of thumb of when to use  "common", "trended", "tagwise" or "auto"? 

Thanks




 -- output of sessionInfo(): 

> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] LSD_2.5            ellipse_0.3-8      schoolmath_0.4    
[4] colorRamps_2.3     RColorBrewer_1.0-5 gtools_3.2.1      
[7] MASS_7.3-29        edgeR_3.4.2        limma_3.18.12     

loaded via a namespace (and not attached):
[1] tools_3.0.2

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