<html>
Hi,<br><br>
As a user I can second that- we definitely use P/A (as well as scaling
factor) to see if a chip within a treatment group has gone awry.
<br><br>
Regarding P/A calls as a filter- I'm fairly certain most users
would agree that, among the probe sets found to be present in 100% of the
chips in the study, there are a greater proportion of statistically
significant findings than would be found among the chips that were 100%
absent- of course this is with MAS5 as a probe level algorithm.
<br><br>
Interestingly, our own lab's observations are that, among probe sets in
which >80% of the chips shows presence calls in one treatment group
and <20% of the chips show presence in the other treatment group (a
relatively small group of 20 genes in the example I'm using- 10 chips per
group), the significance proportion was actually worse than in the 'fully
present cadre'. I've seen this in at least three other data sets with 7or
more chips per group. Although my initial assumption was that selecting
for presence in one group and absence in the other would bias me towards
finding significant results, my interpretation after seeing that this
selection actually reduces the 'significance proportion' is that dividing
up the data by P/A call like this isolates probe sets for which the data
is noisier, but not necessarily smaller, in one group than the
other.<br><br>
Regarding MAS4 algorithm going to MAS5, I think the greatest tragedy was
the eradication of the negative values by artificially altering the MM
values. If the fragment was not present in the mix, then PM and MM should
both be randomly hybridizing, and I would expect that about half of the
time the PM < MM, so those values, while they may not make biological
sense, are exactly what you would expect by the probe set design.
Further, if, as you mention and we've seen in our own data, some negative
values are good discriminators, then there may be some negative values
that are there for other reasons- 'cross hybridization' or Affy's
assumptions regarding how probe sets behave may not hold true in every
case. However the MAS5 algorithm blinds users to such changes.<br><br>
I've also gone in and looked at the dichotomy between MAS5 and RMA
(different probe level algorithms, same test; 1-way ANOVA). As I've said
before, there is no shortage of discrepancies between the two (RMA finds
508 significant, MAS5 finds 409, there is an overlap of 146 between the
two). We specifically looked at feature values in probe sets that
were:<br>
1) RMA: very significant (p < .001) with RMA and very non-significant
(p>.9) with MAS5 <br>
2) MAS5: very significant (p < .001) with MAS5 and very
non-significant (p>.9) with RMA<br>
3) RMA & MAS5: high concordance (p<.001 in both)<br><br>
We isolated images and extracted PM and MM values for the top 10 probe
sets in each of the three categories. The plotted PM and MM values reveal
different phenomena that go into the 'failure to agree'. First, in cases
where tests performed with RMA found significant differences and MAS5 did
not, this was often because of some large variations in the behavior of
the MM features. Where tests performed with MAS5 found significant
differences and RMA did not, this was often because the MM subtraction
amplified a difference that already existed in the PM, or, there was no
difference in the PM and the entire result was due to the MM differences
between the two treatment groups. Of course the probe sets that showed
concordance between the two probe level algorithms were well-behaved. I
presented some of this at the 3rd annual Virtual Conference on Genomics
and Bioinformatics, but I never thought it was really worth pursuing as a
publication. <br><br>
Do you think that there is enough interest out there to publish this, and
if so, where?<br>
-E<br><br>
At 12:01 PM 10/9/2003 +0200, you wrote:<br>
<blockquote type=cite class=cite cite>Date: Wed, 8 Oct 2003 11:11:08
-0700 (PDT)<br>
From: Francois Collin <fcollin@sbcglobal.net><br>
Subject: RE: [BioC] Affy: Present calls in an eset<br>
To: Crispin Miller <CMiller@PICR.man.ac.uk>,<br>
<x-tab> </x-tab>bioconductor@stat.math.ethz.ch<br>
Message-ID:
<20031008181108.47125.qmail@web80406.mail.yahoo.com><br>
Content-Type: text/plain<br><br>
Indeed %present calls is arguably the best of all data quality indicators
that are suggested by Affymetrix. If you rehybe the same hybe mix
to chips under different conditions - change scanner, hybridization time
or temperature, hybe station - %present calls can vary widely.
Genes don't appear and disappear out of the hybe mix, but probe
affinities change under the different conditions. Making sure that
%present calls are consistent across a set of chips is a way to check
that the processing and experimental conditions that affect hybridization
kinetics were fairly consistent across a set of chips.<br>
<br>
As for the Present calls ability to discriminate between samples in which
a given mRNA fragment is present vs a samples in which it isn't, it will
vary from probe set to probe set. In an ideal probe sets in which
all PM/MM probe pairs have similar non-specific binding affinities and
the PM probe has good binding affinity to the target mRNA fragment, and
the target doesn't bind to too many other probes on the chip, the calls
will work well. It is not clear for what proportion of probe sets
the calls actually work as intended. You can definitely find probe
sets for which MM>>PM for several probe pairs in the set and these
fragments will never be called present. The reverse is also
true. <br>
<br>
Very little has been published on the subject as far as I know.
There is the work by Ben Rubenstein mentioned earlier in this
thread. More work obviously need to go into this question. I
think that one should be aware that by screening out absent calls, you
may be losing many interesting target fragments. In the days of MAS
4.0, I recall some genes with negative expression being very good
discriminators of tumor class.<br>
<br>
francois</blockquote>
<x-sigsep><p></x-sigsep>
Eric Blalock, PhD<br>
Dept Pharmacology, UKMC<br>
859 323-8033<br><br>
<font size=1><u>STATEMENT OF CONFIDENTIALITY<br><br>
</u></font><font size=1 color="#333333">The contents of this e-mail
message and any attachments are confidential and are intended solely for
addressee. The information may also be legally privileged. This
transmission is sent in trust, for the sole purpose of delivery to the
intended recipient. If you have received this transmission in error, any
use, reproduction or dissemination of this transmission is strictly
prohibited. If you are not the intended recipient, please immediately
notify the sender by reply e-mail or at (859) 323-8033 and delete this
message and its attachments, if any.</font></html>