[BioC] tagwise parameters for negative binomial distribution in edgeR

Davide Cittaro cittaro.davide at hsr.it
Thu Mar 20 15:59:11 CET 2014


Dear Gordon, 
thanks for the answer.

On 20/mar/2014, at 01:04, Gordon K Smyth <smyth at wehi.EDU.AU> wrote:

> Dear Davide,
> 
> Do you want to identify tags (genes) with dispersion values that are so 
> high (relative to other genes with similar count sizes) that they should 
> be considered outliers?

Mmm, actually I would like to identify the sample that is an outlier for a specific gene, that's why I thought I could focus on tagwise distribution.

> 
> The easiest way to do this is to use
> 
>   d <- estimateDisp(d, design, robust=TRUE)
> 
> and then look at the output values for prior.df:
> 
>   summary(d$prior.df)
> 
> Any tag with a small prior.df is considered an outlier.  You can sort tags 
> by their prior.df values to select the most significant outliers.

Does this identify a tag that is an outlier over all samples? 

> 
> Note that the methodology used by the estimateDisp() robust procedure is 
> more complicated than simply using NB probabilities, because one has to 
> take into acccount the genome-wide distribution of the dispersion values 
> as well as accounting for the fact that the fitted values (p) have been 
> estimated from the same data.  The methodology is mostly explained in:
> 
>  http://www.statsci.org/smyth/pubs/edgeRChapterPreprint.pdf
>  http://www.statsci.org/smyth/pubs/RobustEBayesPreprint.pdf
> 

I have a lot to read :-)
Thanks

d

> Best wishes
> Gordon
> 
>> From: Davide Cittaro <cittaro.davide at hsr.it>
>> To: "bioconductor at r-project.org list" <bioconductor at r-project.org>
>> Subject: [BioC] tagwise parameters for negative binomial distribution
>> 	in	edgeR
>> 
>> Dear list,
> 
>> I have a DGElist object in edgeR, already processed with 
>> calcNormFactors, estimateCommonDispersion and estimateTagWiseDispersion. 
>> Now, I would like to identify tagwise outliers in my data, I thought I 
>> could estimate NB distribution for each tag. Given that a NB is defined 
>> by two parameters (r and p), I assume that r = 1/x$tagwise.dispersion, 
>> how can I get tagwise p from DGEList dataframe?
> 
>> Thanks
>> 
>> d
> 
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