[BioC] Quality Assessment

[Wolfgang Huber]

Dear Lana,

> I am trying to understand the diagnostic plot of the MAD pairwise
> differences of the M-values and how this plot can detect outliers.
> I looked at the example for the CLL data and did not detect any
> differences, but would like to know how to detect any differences.
> All the small boxes are different colors but are mirrored pairwise 
> intensities.   The notes say:  "Arrays whose distance matrix entries
> are way different give cause for suspicion".  However, the color 
> intensities look different??  Please explain how to know if they
> are "way different".

Hmm, which package and function are you refering to and which version?

The following assumes that you refer to the output of a recent 
devel-version of the affyQAReport function in the affyQCReport package?

The matrix is symmetric because the MAD distance is. More details are 
given in the man page of "dist2". This is an exploratory plot that can 
help detecting (a) outlier arrays and (b) batch effects. There are no 
objective numeric thresholds when to call something an outlier, it 
depends on your context, that's why the text is vague.

If there are outliers, you will expect to see vertical and horizontal 
stripes in the plot of darker color. Batch effects that are aligned to 
the order of the arrays as they are read in can be seen as blocks along 
the diagonal. If you see neither, you are lucky, and the data passes 
this quality criterion!

I have added some more text to explain this to the report template.

Hope this helps
  Wolfgang

------------------------------------------------------------------
Wolfgang Huber  EBI/EMBL  Cambridge UK  http://www.ebi.ac.uk/huber

PS  Please do remember to state the output of sessionInfo() and the 
relevant R code for reproducing the subject of your question.


> 
> Lana Schaffer
> Biostatistics/Informatics
> The Scripps Research Institute
> DNA Array Core Facility
> La Jolla, CA 92037
> (858) 784-2263
> (858) 784-2994
> schaffer at scripps.edu
>