[BioC] Re: random location of duplicate spots and use of limma

[Ingunn Berget]

I tried this approach, but I believe that the problem is that spots that are 
adjacent on the array are expected to have higher correlation than spots 
that are in the upper and lower half of the array for instance. This means 
that duplicates that are lets say 10 spots apart probably are more 
correlated than those 200 spots apart, and I am afraid  may "disturb" the 
analysis.

I maybe have made some mistakes during the programming (I''m an R beginner), 
but I have calculated the correlation between duplicate spots in this way 
for different methods of background correction and normalisation. I thought 
that the methods giving the highest correlation would be best for further 
analyses, but the highest correlation was obtained with no background 
correction and no normalisation. I found this very strange since the 
background is not uniform within the arrays, and all litterature says that 
microarray data should be normalised.

Ingunn

----- Original Message ----- 
From: "Jason Skelton" <jps at sanger.ac.uk>
To: <ingunn.berget at umb.no>; <bioconductor at stat.math.ethz.ch>
Sent: Friday, January 07, 2005 1:01 PM
Subject: random location of duplicate spots and use of limma


> >
>>
>>Hello
>>
>>There are approximately 6000 different genes on the arrays, there are two 
>>spots for each gene
>>The duplicated spots have random location, which means that the number of 
>>spots between each duplicate is not the same for every gene. This is the 
>>summary for the distances:
>>
>>  Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 4.00   32.00   71.00 
>> 86.59  135.00  244.00
>>(Distance here means number of spots between the two duplicates)
>>
>>The function duplicateCorrelation in limma can be used to estimate 
>>correlation between within-array duplicates, the methodology is based on 
>>the assumption that duplicates are equally spaced. Since this assumption 
>>is not fulfilled here does this means that I cannot calculate the 
>>correlations and must take the average of the duplicates? Are there some 
>>functions to do this in limma or other BioC packages
>>
>
> Hi ingunn & all
>
> I could be wrong about this but can you get round this in limma by:
> normalising the data first(to allow for the physical location on the 
> array)
> followed by re-arranging the normalised data so that duplicate genes 
> appear next to each other
> and therefore have equal spacing ? I.e spacing of 1 or similar.
> You obviously have to make new genelists for the  "rearranged" order but I 
> can't see any obvious problems with
> further analysis such as the linear model fitting etc. If you only have 
> two replicates then it should be ok......
> I do this routinely but the limma authors might be able to suggest a 
> better alternative ?
>
>
> Jason
>
>
>
>
>
>
>
>>-- 
>>--------------------------------
>>Jason Skelton
>>Pathogen Microarrays
>>Wellcome Trust Sanger Institute
>>Hinxton
>>Cambridge
>>CB10 1SA
>>
>>Tel +44(0)1223 834244 Ext 7123
>>Fax +44(0)1223 494919
>>--------------------------------
>>
>