there was a package addressing cross-sample distributional shapes, edd, but
it was retired due to lack of use, IIRC

http://books.google.com/books?id=jIMO2rRaCbMC&pg=PA55&lpg=PA55&dq=edd+expression+density+diagnostics&source=bl&ots=tXKdRicJ8x&sig=vZF9tRCrLAhiaVinx7yeEMh3bSA&hl=en&sa=X&ei=DgOyUbitItLl4AOXhYHYAQ&ved=0CFAQ6AEwBw#v=onepage&q=edd%20expression%20density%20diagnostics&f=false

On Fri, Jun 7, 2013 at 11:26 AM, James W. MacDonald <jmacdon@uw.edu> wrote:

> Hi Miguel,
>
>
> On 6/7/2013 5:11 AM, Miguel Moreno-Risueno wrote:
>
>>
>>
>> Hello all,
>>
>>
>>
>> We have recently received a microarray experiment in the Nimblegen
>> platform
>> where the intensity of the probe sets follow a bi-modal distribution. We
>> have been said from the facility that this is because of the dynamic range
>> of the Agilent scanner they use. We are concerned about the statistical
>> analysis with bioconductor as it is our understanding that these
>> statistical
>> analyses are developed for normal or normal-like distribution. We
>> appreciate
>> any information on this regard.
>>
>
> If I understand your question correctly, you are noting that the overall
> distribution of probes within a sample has a bi-modal distribution. This
> doesn't really have anything to do with any statistical tests you might be
> computing, as you are not doing any statistics within a sample (e.g., one
> usually doesn't test to see if probe X is differentially expressed as
> compared to probe Z in sample Q).
>
> Instead, what you should be concerned with are the distributions of the
> individual probes across samples. With microarray data we usually don't
> have enough data to even begin to assess the across-sample, within probe
> distributions (e.g., if you have three replicates for two sample types,
> good luck trying to discern if those probes follow a normal distribution,
> or are even 'hump-shaped'). In addition, there are usually tens of
> thousands of probes on a given chip. I have never heard of anybody looking
> at each probe, trying to assess if it follows a reasonable distribution
> across samples. I suppose you could do it, but to what point?
>
> Instead we simply assume that the data follow a reasonable distribution
> and then do the test. This is one of the reasons that it is imperative to
> follow up promising leads with confirmatory testing, preferably with new
> samples.
>
> Best,
>
> Jim
>
>
>
>
>>
>>
>> Thank you in advance for your help,
>>
>>
>>
>> Miguel
>>
>>
>>
>>
>>
>>
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>>
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>>
>
> --
> James W. MacDonald, M.S.
> Biostatistician
> University of Washington
> Environmental and Occupational Health Sciences
> 4225 Roosevelt Way NE, # 100
> Seattle WA 98105-6099
>
>
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