Just some info on PLIER (info from webtalk available on Affy website) incase you are interested. I have got hold of a beta test version of new GREX software (any Affymetrix customer can get hold of this through Affy distributors), and new GREX software gives several options. 1) Standard mas5 algorithm 2) Quantile normalisation 3) bg subtraction, none, percentage background, or MM estimates bg. 4) PP-MM, PM only, or MM treated as PM values. 5) Modelling of probe affinities and target concentration using M-estimator (PLIER bit) With PLIER, M vs A plots are much cleaner at low end in comparison to mas5, but they are still more noisy than rma plots. I am currently looking at comparing qRT-PCR results with the different algorithms to see which algortihm most accurately predicts the actual gene expression level (since rma doesn't adjust for probe affinities I don't expect rma to gove the best correlation with PCR but not sure yet). I can send some M vs A plots with my own data just for interest if you like. Regards Anthony X-Original-To: anthonyb@ichr.uwa.edu.au Delivered-To: anthonyb@ichr.uwa.edu.au Date: Mon, 17 May 2004 12:25:13 -0400 From: "James MacDonald" <jmacdon@med.umich.edu> To: <bioconductor@stat.math.ethz.ch>, <naomi@stat.psu.edu> Subject: Re: [BioC] median polish vs mas X-Virus-Scanned: by amavisd-new Cc: wliu@hes.hmc.psu.edu X-BeenThere: bioconductor@stat.math.ethz.ch X-Mailman-Version: 2.1.4 List-Id: The Bioconductor Project Mailing List <bioconductor.stat.math.ethz.ch> List-Unsubscribe: <https: www.stat.math.ethz.ch="" mailman="" listinfo="" bioconductor="">, <mailto:bioconductor- request@stat.math.ethz.ch?subject="unsubscribe"> List-Archive: <https: www.stat.math.ethz.ch="" pipermail="" bioconductor=""> List-Post: <mailto:bioconductor@stat.math.ethz.ch> List-Help: <mailto:bioconductor- request@stat.math.ethz.ch?subject="help"> List-Subscribe: <https: www.stat.math.ethz.ch="" mailman="" listinfo="" bioconductor="">, <mailto:bioconductor- request@stat.math.ethz.ch?subject="subscribe"> Sender: bioconductor-bounces@stat.math.ethz.ch X-Spam-Checker-Version: SpamAssassin 2.63 (2004-01-11) on poohbear.ichr.uwa.edu.au X-Spam-Status: No, hits=-2.8 required=5.0 tests=AWL,BAYES_10 autolearn=no version=2.63 X-Spam-Level: Dear Naomi, I think we are talking about two different things here. Your question appears to be whether or not rma is a reasonable method for computing expression values, and you appear not to distinguish between justRMA and rma. My statement is directed towards the purpose of justRMA. To answer your question, I personally like rma, and I am not convinced that there is any over-normalization occuring by doing a quantile normalization followed by medianpolish. I have tried pretty much everything out there, and I have yet to find a method for computing expression values that I think does a better job in general use. This is based primarily on how well a given method works with the affy spike- in and GeneLogic dilution data sets (I have had arguments with other statisticians who think that rma only works as well as it does with these data sets because it has been specifically 'tuned' for them. If so, my hat is off to Rafael and Ben for their ability to come up with an algorithm that can magically pick the 16 spiked-in genes out of the other 18,000 or so other genes...). For a variety of reasons, not the least of which is the fact that rma 'beats' most other methods, rma has sort of become the canonical method for computing expression values for Affy data. It has been implemented in other non-BioC packages such as GeneSpring, etc, and although I haven't seen anything concrete, I would bet dollars to donuts that the Affy PLIER algorithm is simply rma by another name. I think this is why your reviewer wants to know why you are doing quantile normalization followed by Tukey's biweight instead of what he/she would consider to be the 'usual' method. Now to the point I was originally trying to make. One of the problems that people encounter with rma is the fact that you first have to create an AffyBatch with all of your chips, and then compute expression values which are stored in an exprSet. This can take a huge amount of RAM, and people with maybe 512 Mb of RAM (which is plenty for the vast majority of things you will ever do on a computer) were running out of memory with a relatively small number of chips. Rafael noted that a modification could be made to rma that would use much less memory, and with his help I wrote the original justRMA. This function was designed for one purpose only; to allow people with less RAM to be able to do rma. The decision to use medianpolish wasn't arbitrary at all; justRMA is designed to give the exact same results as rma (which of course uses medianpolish to compute expression values), so by default I had to use medianpolish. Best, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> Naomi Altman <naomi@stat.psu.edu> 05/17/04 11:33AM >>> Dear Jim, The reason I ask is that I have been using expresso with "mas". But I recently had a paper returned with the comment that median polish was "known to be better". If so, I should probably use it. The reviewer appears to have based his/her remarks on the fact (mentioned in the review) that median polish is the "default". If the decision to use median polish in justRMA was arbitrary, I would like to know this, since I am currently in the process of redoing all of the statistical analyses and tables in the paper (which is pretty time-consuming). The main reason we are redoing everything, rather than defending our decision to use "mas" is that I certainly have no evidence that Tukey's biweight is "better" except for the heuristic about over-normalization, and I figured in the long run we will have fewer arguments with reviewers if we use the default. I should not have said that median polish is the "default" in justRMA, since it is the only method available, but I do think that its use in justRMA is an endorsement meaning that anyone doing anything besides Affy-type MAS5 or justRMA or justGCRMA (if this is available) is going to be asked to justify what they are doing with more stringency. --Naomi At 10:49 AM 5/17/2004, James MacDonald wrote: The default (and only) option for justRMA is medianpolish because justRMA is designed to *just* do *RMA*, which is a quantile normalization followed by medianpolish. The only reason justRMA exists is to allow people with less RAM to be able to do rma. If you think a quantile normalization followed by Tukey's biweight will do better than rma, you can certainly do that using the expresso() function. Best, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> Naomi Altman <naomi@stat.psu.edu> 05/17/04 10:15AM >>> I have been wondering why the default in justRMA is summary.method="medianpolish" instead of "mas" which is Tukey's biweight. Since we are already doing quantile normalization, doesn't the extra between array step imposed by median polish give the possibility of masking differential expression? Naomi S. Altman 814-865-3791 (voice) Associate Professor Bioinformatics Consulting Center Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111 _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Bioinformatics Consulting Center Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111 _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor -- ______________________________________________ Anthony Bosco - PhD Student Institute for Child Health Research (Company Limited by Guarantee ACN 009 278 755) Subiaco, Western Australia, 6008 Ph 61 8 9489 , Fax 61 8 9489 7700 email anthonyb@ichr.uwa.edu.au