[Bioc-devel] Can I analyze with bioconductor a microarray experiement where the distribution of probes intesisties follow a bi modal distribution?

James W. MacDonald jmacdon at uw.edu
Fri Jun 7 17:26:49 CEST 2013

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.



> Thank you in advance for your help,
> Miguel
> 	[[alternative HTML version deleted]]
> _______________________________________________
> Bioc-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/bioc-devel

James W. MacDonald, M.S.
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099

More information about the Bioc-devel mailing list