[BioC] median polish vs mas/PLIER info
Anthony Bosco
anthonyb at ichr.uwa.edu.au
Tue May 18 04:44:26 CEST 2004
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
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Date: Mon, 17 May 2004 12:25:13 -0400
From: "James MacDonald" <jmacdon at med.umich.edu>
To: <bioconductor at stat.math.ethz.ch>, <naomi at stat.psu.edu>
Subject: Re: [BioC] median polish vs mas
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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 at 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 at 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
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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
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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 at ichr.uwa.edu.au
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