Hi Simon,

I have tried clustering the proteins, first I transposed the data and
applied the minimal set of commands but could not go further. Here is my
code and the error message.

tspectral=t(spectral)
cds2=newCountDataSet(tspectral,rep( "dummy", ncol(tspectral)))
> cds2
CountDataSet (storageMode: environment)
assayData: 5 features, 36 samples
  element names: counts
protocolData: none
phenoData
  sampleNames: Gene_01 Gene_02 Gene_03 Gene_04 ... Gene_36 (36
    total)
  varLabels: sizeFactor condition
  varMetadata: labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation:
> cds2=estimateSizeFactors(cds2)
> cds2=estimateVarianceFunctions(cds2)
Error in estimateVarianceFunctions(cds2) :
  NAs found in size factors. Have you called already 'estimateSizeFactors'?

Thank you for your help,
Yolande
On Tue, Apr 5, 2011 at 5:22 AM, Simon Anders <anders@embl.de> wrote:

> Hi Yolanda
>
>
> On 04/04/2011 07:34 PM, Yolande Tra wrote:
>
>> For clustering the proteins what would be conds (defined in the
>> vignette) in
>> cds3<-newCountdataSet(countsTable,conds)
>> since there are many proteins with no specific condition.
>>
>
> Just put something, e.g.,
>
>   cds3 <- newCountDataSet( countsTable,
>      rep( "dummy", ncol(countsTable) )
>
> This assigns the same condition to all of them. Of course, you cannot use
> the 'nbinomTest' function, if you have only one condition, but that wouldn't
> make sense anyway.
>
>
> 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").
>>
>
> In a contrast, you compare two condition. In the vignette example, we ask:
> Is the expression in "T" stronger or weaker than in "N"?
>
> How would you generalize such a question to three conditions? I don't see
> what other option there is than to make three pair-wise comparisons --
> unless you want to go away from the "which condition has the stronger
> expression?" kind of question to some other hypothesis formulation.
>
>  Simon
>
>
>

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