[BioC] large amount of slides

Adaikalavan Ramasamy ramasamy at cancer.org.uk
Fri Jun 4 17:30:02 CEST 2004

This is what I do :
1. Randomly split into manageable chuncks of say 4 batches of 50
(depends on computer)
2. Do RMA on these batches separately
3. Combine these 4 batches (e.g. cbind/merge) into one finalised dataset
4. Repeat for B times and take the average of B datasets

>From past experience, the coefficient of variation is less than 0.03 for
99% of probesets if you use B = 20 - 30.

If you like I can send my perl wrapper script that does this. This is
based on the assumption you can submit multiple jobs (e.g. clusters or
big server) but you can easily modify it.

I don't know much about increasing RAM. You can try just.rma( ...,
destructive=TRUE) but I am not sure if this uses significantly less RAM.
Regards, Adai.

On Fri, 2004-06-04 at 16:06, Vada Wilcox wrote:
> Dear all,
> I have been using RMA succesfully for a while now, but in the past I have 
> only used it on a small amount of slides. I would like to do my study on a 
> larger scale now, with data (series of experiments) from other researchers 
> as well. My questions is the following: if I want to study, let's say 200 
> slides, do I have to read them all into R at once (so together I mean, with 
> read.affy() in package affy), or is it OK to read them series by series (so 
> all wild types and controls of one researcher at a time)?
> If it is really necessary to read all of them in at one time how much RAM 
> would I need (for let's say 200 CELfiles) and how can I raise the RAM? I now 
> it's possible to raise it by using 'max vsize = ...' but I haven't been able 
> to do it succesfully for 200 experiments though. Can somebody help me on 
> this?
> Many thanks in advance,
> Vada
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