[BioC] memory usage ReadAffy() and probe level information

James MacDonald jmacdon at med.umich.edu
Tue Apr 6 14:52:15 CEST 2004

Simply put, you are not going to be able to read in >300 cel files with
only(!) 2 Gb RAM. You should be able to do justRMA with this much RAM on
100 or so chips, but if you really want to be able to do huge numbers of
chips you are going to have to upgrade to a 64 bit architecture, which
at this point in time also means you have to switch to Linux.

To get the pm probes I think you want to do something like this:

my.pms <- probes(abatch, "pm", "1007_s_at") # for e.g., the 1007_s_at



James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109

>>> Roel Verhaak <r.verhaak at erasmusmc.nl> 04/06/04 08:32AM >>>

I have two questions regarding the use of the affy package:
- I have a large series of cel-files and am trying to read
them at once. Unfortunately, the ReadAffy-function seems to
use a lot of memory. My workstation has 2 Gig of RAM
installed, but trying to read >100 cel-files (HGU133a) is a
no-go. This is R1.8.1 with Bioconductor 1.3 on a Windows
machine. Reading in 50 cel-files already means a
(peak-)memory usage of 800 meg. Is there any solution to
this, because I would like to read 300 cel-files at the same
time if possible. I have played around with the
memory.limit()-function, but with no success.
- Second, after data import I would like to retrieve all
information on a probe level for several probe sets. I do
this using the pm()-function, for instance
>pm(CelFiles)[1:16, 1:50]. The problem is that I have to find out first
where which exact "location" the probe set of interest has. This is not
a big problem, but I thought there might be a more elegant solution to

Thanks in advance,
Roel Verhaak

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