Hi BioC list,

I am analyzing some new Agilent 4x44 C. Elegans arrays, and as our previous
Agilent celegans arrays, there are 120 genes that are printed many (> 10)
times.  However, now on each array everything is duplicated: Those 120 spots
are printed 20 times (not 10), and all others are printed twice  (and one
spot is printed 4 times...it probably was meant to be 2 different genes).
As far as I can tell, the duplicated spots are randomly spaced.  I would
like to use duplicateCorrelation on the normalized data, sorted by gene
name, as described previously on the list:

https://stat.ethz.ch/pipermail/bioconductor/attachments/20060123/4890ea8e/attachment.pl

My only problem now is the spots that are replicated 20  times.  In the past
I haven't dealt with them using very stringent statistics, since it was only
120 spots that I was dealing with (and maybe 1 gene in the group was
differentially expressed).  Now however, since all 20K spots are duplicated,
we need to take of the duplicates.  Clearly duplicateCorrelation is the
simplest way to do this, but it won't work if we have 120 genes that are
printed 20 times.

My question is: how do I deal with these gens?  Could I just ignore those
120 genes for the calculation of the consensus correlation?   I read on this
list that small numbers of genes won't affect this calculation: 120 /20K is
less than 1% of the genes.

If I do that, what would become of the 120 spots?  Can I somehow apply the
same consensus correlation to them?

What other solutions do people propose?


Thanks in advance for your time.

Jeremy Davis-Turak

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