[BioC] large amount of slides/ out of memory

Simon Lin simon.lin at duke.edu
Tue Jun 8 23:28:18 CEST 2004


"Out of memory error" is a common challenge of running a very large batch of
Affymetrix chips with RMA or gcRMA.
To solve this program, I am working on a dcExpresso function. It is in alpha
stage now. I will move it into beta release in the next two weeks.
Best regards,

Simon


=================================================
  Simon M. Lin, M.D.
  Manager, Duke Bioinformatics Shared Resource
  Assistant Research Professor, Biostatistics and Bioinformatics
  Box 3958, Duke University Medical Center
  Rm 286 Hanes, Trent Dr, Durham, NC 27710
  Ph: (919) 681-9646 FAX: (919) 681-8028
  Lin00025 (at) mc.duke.edu
  http://dbsr.duke.edu
=================================================




Date: Mon, 7 Jun 2004 08:36:24 +0200 (MEST)
From: "R.G.W. Verhaak" <r.verhaak at erasmusmc.nl>
Subject: Re: [BioC] large amount of slides
To: bioconductor at stat.math.ethz.ch
Message-ID:
<43766.130.115.244.114.1086590184.squirrel at 130.115.244.114>
Content-Type: text/plain;charset=iso-8859-1

I have succesfully ran GCRMA on a dataset of 285 HGU133a chips, on a
machine with 8 Gb RAM installed; I noticed a peak memory use of 5,5 Gb
(although I have not been monitoring it continuously). I would say 200
chips use equally less memory, so around 4 Gb.

Roel Verhaak

>
> Message: 9
> Date: Fri, 04 Jun 2004 10:06:14 -0500
> From: "Vada Wilcox" <v_wilcox at hotmail.com>
> Subject: [BioC] large amount of slides
> To: bioconductor at stat.math.ethz.ch
> Message-ID: <BAY19-F34SDGAIXWb9D0002ec89 at hotmail.com>
> Content-Type: text/plain; format=flowed
>
> 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?
>



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