In the vignette there were two conditions: "N" and "T".
For three different people (not 40), how you would define the cds in the
command
res<=nbinom(cds,"N","T").

Thanks,
Yolande
On Mon, Apr 4, 2011 at 1:11 PM, Simon Anders <anders@embl.de> wrote:

> Hi Yolanda
>
>
> On 04/04/2011 03:42 PM, Yolande Tra wrote:
>
>> I do have protein count data for 40 people (so no replicate). These are
>> healthy people, no grouping. The goal is to look at
>> similarity/dissimilarity
>> of the 40 samples based on protein count (differential expression IF
>> POSSIBLE) AND clustering of the proteins. As you said, clustering of
>> samples
>> can be done with the section "Sample Clustering" of the vignette. How
>> would
>> I go for clustering the proteins and look for differential expression (IF
>> POSSIBLE).
>>
>
> The whole point of DESeq is to allow you to work in a small sample-size
> setting, where you need to pool data from several genes to get useful
> dispersion estimates.
>
> With 40 people, you are beyond that, and you can use any conventional tests
> that are suitable for overdispersed count data.
>
>
> I don't quite know what you mean by differential expression in this case
> anyway. No two persons will have the same protein level, so everything is
> differentially expressed in some way.
>
> Maybe, you may want to estimate the variance of the proteins and look for
> strongly varying versus weakly varying ones. Supplementary Note A of our
> paper on DESeq describes a simple method-of-moments estimate for the
> biological variance that subtracts the Poisson noise and deals with
> different sequencing depths.
>
> For a discussion of the clustering, DESeq's variance-stabilizing
> transformation might help for clustering genes in a similar way as for
> clustering samples.
>
>  Simon
>
>
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