[BioC] limma and paired data

[Naomi Altman]

The simplest way to handle this is probably to take the difference of the 
pairs and feed that into limma as a 1-sample t.

--Naomi

At 12:22 PM 4/20/2004 +1000, Gordon Smyth wrote:
>At 03:09 AM 20/04/2004, Danielle Fletcher wrote:
>>Hi,
>>
>>I am using limma to analyse a 2-colour microarray experiment. There are 2 
>>treatments and 4 replicates in each of these groups. Each replicate is 
>>paired to a replicate in the otehr treatment group. Each sample was 
>>hybridised with a reference, so 8 slides in total.
>>
>>The targets file looks like this (hopefuly that will make it clearer):
>>SlideNumber   Name   FileName   Cy3   Cy5
>>1   1M   1.gpr   monolayer   ref
>>2   1P   5b.gpr   pellet   ref
>>3   2M   2.gpr   monolayer   ref
>>4   2P   7.gpr   pellet   ref
>>5   3M   3.gpr   monolayer   ref
>>6   3P   6.gpr   pellet   ref
>>7   4M   B.gpr   monolayer   ref
>>8   4P   A.gpr   pellet   ref
>>
>>Initially my design matrix looked like this:
>>
>>    Sample-Ref Monolayer-Pellet
>>1M           1          0
>>1P           1          1
>>2M           1          0
>>2P           1          1
>>3M           1          0
>>3P           1          1
>>4M           1          0
>>4P           1          1
>>
>>but thinking about it again, i don't think this takes into account the 
>>paired nature of the data. I am sure that the answer is probably a simple one,
>
>There is no simple answer. There was a big discussion about this in 
>Bioconductor very recently, please look at the list archives.
>
>In the very latest versions of limma, there is a new argument 'block' in 
>duplicateCorrelation() and lmFit() to handle a blocking structure like you 
>describe. This feature is however very lightly documented so far and so is 
>offered on a user beware basis. In your case, block=c(1,1,2,2,3,3,4,4).
>
>Gordon
>
>>  but I am not sure what the best solution is.  I would appreciate any 
>> advice.
>>
>>Thanks in advance
>>
>>Danielle
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111