Entering edit mode
Lizhe Xu
▴
210
@lizhe-xu-666
Last seen 10.2 years ago
I got the following message when runing dChip, should I ignore the
warning message or ignore the method?
> dDataA<-expresso(DataA, bgcorrect.method="mas",
normalize.method="invariantset", pmcorrect.method="pmonly",
summary.method="liwong")
background correction: mas
normalization: invariantset
PM/MM correction : pmonly
expression values: liwong
background correcting...done.
normalizing...done.
22283 ids to be processed
Warning message:
No convergence achieved in outlier loop
in: fit.li.wong(probes, ...)
Warning message:
No convergence achieved in outlier loop
in: fit.li.wong(probes, ...)
Thanks.
Lizhe
-----Original Message-----
From: bioconductor-request@stat.math.ethz.ch [mailto:bioconductor-
request@stat.math.ethz.ch]
Sent: Tuesday, March 16, 2004 11:29 AM
To: bioconductor@stat.math.ethz.ch
Subject: Bioconductor Digest, Vol 13, Issue 36
Send Bioconductor mailing list submissions to
bioconductor@stat.math.ethz.ch
To subscribe or unsubscribe via the World Wide Web, visit
https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
or, via email, send a message with subject or body 'help' to
bioconductor-request@stat.math.ethz.ch
You can reach the person managing the list at
bioconductor-owner@stat.math.ethz.ch
When replying, please edit your Subject line so it is more specific
than "Re: Contents of Bioconductor digest..."
Today's Topics:
1. RE: MOE430 A and B - bug? (Jose Duarte)
2. Re: Where are the new metadata packages (John Zhang)
3. canine annotation library package (LIANHE SHAO)
4. BioConductor: Affy Package (Julius Viloria)
5. Re: warning messages in gcrma (paolo.sirabella@uniroma1.it)
6. QualityWeights (using limma) joycel_balaena.bio.vu.nl)
7. Re: Where are the new metadata packages (Jeff Gentry)
8. Canine annotation package (LIANHE SHAO)
9. RE: Quantile normalization vs. data distributions
(Arne.Muller@aventis.com)
----------------------------------------------------------------------
Message: 1
Date: 16 Mar 2004 15:05:19 +0000
From: Jose Duarte <jose.duarte@human-anatomy.oxford.ac.uk>
Subject: RE: [BioC] MOE430 A and B - bug?
To: Aedin <aedin.culhane@ucd.ie>
Cc: bioconductor@stat.math.ethz.ch
Message-ID: <1079449519.20677.30.camel@fgu013.anat.ox.ac.uk>
Content-Type: text/plain
I am getting exactly the same error in aafGO:
> a<-aafGO(probeids,"moe430a")
Error in exists(num, GOBPID2TERM) : Object "GOBPID2TERM" not found
This is when using version 1.5.0 of the moe430a metadata package. In a
different machine with version 1.4.0 this works alright. annaffy
version
is 1.0.3 in both.
Thanks
Jose
On Mon, 2004-03-15 at 17:04, Aedin wrote:
> Hi
> I am having problems using annaffy GO (aafGO) annotations on these
chips? I
> have updated my chip annotation files, and GO library, but still get
>
> > a<-aafGO(rownames(chipA), "moe430a")
> Error in exists(num, GOBPID2TERM) : Object "GOBPID2TERM" not found
>
> Thanks for your help,
> Aedin
>
> -----Original Message-----
> From: bioconductor-bounces+aedin.culhane=ucd.ie@stat.math.ethz.ch
> [mailto:bioconductor-
bounces+aedin.culhane=ucd.ie@stat.math.ethz.ch]On
> Behalf Of Ben Bolstad
> Sent: 15 March 2004 14:17
> To: peter robinson
> Cc: bioconductor@stat.math.ethz.ch
> Subject: Re: [BioC] MOE430 A and B
>
>
> you need to read in the type A and type B files into separate
affybatch
> objects.
>
> eg
>
> my.Data.A <-
> ReadAffy(filenames=c("blahA1.cel","blahA2.cel","blahA3.cel"))
>
> my.Data.B <-
> ReadAffy(filenames=c("blahB1.cel","blahB2.cel","blahB3.cel"))
>
> Ben
>
>
>
>
>
>
> On Mon, 2004-03-15 at 04:20, peter robinson wrote:
> > Dear List members,
> >
> > I would like to use the affy package to analyze data from MOE430A
and -B
> > chips. I tried to read in data from both types of chips at once
using
> > data <- ReadAffy(widget=T)
> > and then reading in 3 MOE430A and 3 MOE430B CEL files.
> > I got the error message:
> > "Cel file does not seem to beo of 430MOEA type" when the script
tried to
> input
> > data from a 430MOEB Cel file. I had imported the CDF and
annotation
> packages
> > for both types of chip.
> > I am using R 1.81, Bioconductor 1.3 on a SuSe 8.1 linux system.
> >
> > Thanks for any advice/tips!
> >
> > Peter
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor@stat.math.ethz.ch
> > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
> --
> Ben Bolstad <bolstad@stat.berkeley.edu>
> http://www.stat.berkeley.edu/~bolstad
>
> _______________________________________________
> 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
--
Jose Duarte <jose.duarte@anat.ox.ac.uk>
------------------------------
Message: 2
Date: Tue, 16 Mar 2004 10:07:33 -0500 (EST)
From: John Zhang <jzhang@jimmy.harvard.edu>
Subject: Re: [BioC] Where are the new metadata packages
To: Claudio.Lottaz@molgen.mpg.de
Cc: bioconductor@stat.math.ethz.ch
Message-ID: <200403161507.KAA02425@blaise.dfci.harvard.edu>
Content-Type: TEXT/plain; charset=us-ascii
>A few days ago versions 1.5.1 of several data packages have been
announced and
were accessible for a little while. However, I no longer find them,
the links on
the bioconductor page lead to version 1.5.0 (e.g. for GO) and
download.packages2
fetches version 1.5.0 of GO.
We have decided to also have a release (currently 1.5.0) and
developmental
version (currently 1.5.1) of annotation data packages. The link to
metaData is
for the release version. Our system is not quite ready for the
developmental
version yet. A very temporary solution is to do the following to get
the
developmental version (currently 1.5.1):
library(reposTools)
z <- getReposEntry("http://www.bioconductor.org/data/metaData-devel")
Then you can use z in the 'repEntry' arguments:
update.packages2(repEntry=z)
Example for install.packages2
install.packages2("hgu95av2", repEntry=z)
Sorry for the confusion.
>
>Has a problem been found with the packages?
>Or is the problem that the new versions have been accidentally
removed from the
repository?
>
>Cheers
>Claudio
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor@stat.math.ethz.ch
>https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
Jianhua Zhang
Department of Biostatistics
Dana-Farber Cancer Institute
44 Binney Street
Boston, MA 02115-6084
------------------------------
Message: 3
Date: Tue, 16 Mar 2004 07:17:06 -0800
From: LIANHE SHAO <lshao2@jhmi.edu>
Subject: [BioC] canine annotation library package
To: bioconductor@stat.math.ethz.ch
Message-ID: <aa71cbaa71ac.aa71acaa71cb@jhmimail.jhmi.edu>
Content-Type: text/plain; charset=us-ascii
Hi,
Can anybody tell me where to find Canine Annotation package. Seems
there is no such package on the Bioconductor website. Thanks.
Regards,
William
------------------------------
Message: 4
Date: Mon, 15 Mar 2004 11:24:55 -0800
From: "Julius Viloria" <jviloria@iac-online.com>
Subject: [BioC] BioConductor: Affy Package
To: <bioconductor@stat.math.ethz.ch>
Cc: Julius Viloria <jviloria@iac-online.com>
Message-ID:
<4E419C7BF2F7A443893BF80AAD6A18B30127D9@intelligent4.iac-
online.com>
Content-Type: text/plain
Hello,
Is there a complete stand-alone version of the affy package and if so,
is the c source code available for this? I'm mostly interested in
using
some of the background correction and normalization functions of the
affy package with some other functions I have written in MATLAB. I am
not familiar with the intricacies of R and the c code required to
attach
the algorithms with the R environment. Any help would be greatly
appreciated.
Sincerely,
Julius Viloria
[[alternative HTML version deleted]]
------------------------------
Message: 5
Date: Tue, 16 Mar 2004 14:28:58 +0100
From: paolo.sirabella@uniroma1.it
Subject: Re: [BioC] warning messages in gcrma
To: bioconductor@stat.math.ethz.ch
Message-ID: <40570F2A.26736.4A51D35@localhost>
Content-Type: text/plain; charset=US-ASCII
I got the same kind of warnings referred in the attached post by Lizhe
Xu. The
configuration is R1.8.1/BioC1.3/Linux .
I have no idea of the meaning of these warnings and if they are
significant.
Does anyone give us some hints ?
Thanks
----------------------------------------------------------------
Paolo Sirabella, PhD
University of Rome - "La Sapienza"
Dept. of Human Physiology and Pharmacology - Building of Human
Physiology
P.le Aldo Moro, 5 - 00185 Roma - Italy
Web http://w3.uniroma1.it/cisb/Cisb/members/sirabella
Simplex Sigillum Veri
----------------------------------------------------------------------
--
On 15 Mar 2004 at 15:22, Lizhe Xu wrote:
> I just tried to run gcrma and got 30 warnings. I wonder if there are
something I did wrong and if these warning affect my results. Thanks.
>
> > gcrmaDataB<-gcrma(DataB)
> Loading required package: hgu133bprobe
> Loading required package: matchprobes
> background correction: gcrma
> normalization: quantiles
> PM/MM correction : pmonly
> expression values: medianpolish
> background correcting...There were 30 warnings (use warnings() to
see them)
> done.
> normalizing...done.
> 22645 ids to be processed
> .........
> > warnings()
> Warning messages:
> 1: multi-argument returns are deprecated in: return(y = yhat, wt)
> 2: multi-argument returns are deprecated in: return(y = yhat, wt)
> 3: multi-argument returns are deprecated in: return(y = yhat, wt)
> 4: multi-argument returns are deprecated in: return(y = yhat, wt)
> 5: multi-argument returns are deprecated in: return(y = yhat, wt)
> 6: multi-argument returns are deprecated in: return(y = yhat, wt)
> 7: multi-argument returns are deprecated in: return(y = yhat, wt)
> 8: multi-argument returns are deprecated in: return(y = yhat, wt)
> 9: multi-argument returns are deprecated in: return(y = yhat, wt)
> 10: multi-argument returns are deprecated in: return(y = yhat, wt)
> 11: multi-argument returns are deprecated in: return(y = yhat, wt)
> 12: multi-argument returns are deprecated in: return(y = yhat, wt)
> 13: multi-argument returns are deprecated in: return(y = yhat, wt)
> 14: multi-argument returns are deprecated in: return(y = yhat, wt)
> 15: multi-argument returns are deprecated in: return(y = yhat, wt)
> 16: multi-argument returns are deprecated in: return(y = yhat, wt)
> 17: multi-argument returns are deprecated in: return(y = yhat, wt)
> 18: multi-argument returns are deprecated in: return(y = yhat, wt)
> 19: multi-argument returns are deprecated in: return(y = yhat, wt)
> 20: multi-argument returns are deprecated in: return(y = yhat, wt)
> 21: multi-argument returns are deprecated in: return(y = yhat, wt)
> 22: multi-argument returns are deprecated in: return(y = yhat, wt)
> 23: multi-argument returns are deprecated in: return(y = yhat, wt)
> 24: multi-argument returns are deprecated in: return(y = yhat, wt)
> 25: multi-argument returns are deprecated in: return(y = yhat, wt)
> 26: multi-argument returns are deprecated in: return(y = yhat, wt)
> 27: multi-argument returns are deprecated in: return(y = yhat, wt)
> 28: multi-argument returns are deprecated in: return(y = yhat, wt)
> 29: multi-argument returns are deprecated in: return(y = yhat, wt)
> 30: multi-argument returns are deprecated in: return(y = yhat, wt)
>
> Lizhe
------------------------------
Message: 6
Date: Tue, 16 Mar 2004 15:35:07 +0100
From: "joycel_balaena.bio.vu.nl" <joycel@bio.vu.nl>
Subject: [BioC] QualityWeights (using limma)
To: "bioconductor@stat.math.ethz.ch" <bioconductor@stat.math.ethz.ch>
Message-ID: <4072ADEB@twigger.nl>
Content-Type: text/plain; charset="ISO-8859-1"
I am using the limma application and am wondering whether there are is
a
QualityWeights function available for Imagene? If not, is there an
alternative
way to compute QualityWeights when using data from the Imagene image
analysis
program?
Hope someone can help me out,
Joyce van de Leemput
===============einde bericht========================
Dit bericht is verstuurd via http://www.twigger.nl. Overal
ter wereld je bestaande mailadres bereikbaar.
Stuur goedkoop SMS via http://www.twiggersms.nl
------------------------------
Message: 7
Date: Tue, 16 Mar 2004 10:30:28 -0500 (EST)
From: Jeff Gentry <jgentry@jimmy.harvard.edu>
Subject: Re: [BioC] Where are the new metadata packages
To: Claudio Lottaz <claudio.lottaz@molgen.mpg.de>
Cc: bioconductor@stat.math.ethz.ch
Message-ID:
<pine.sol.4.20.0403161022550.1867-100000@santiam.dfci.harvard.edu>
Content-Type: TEXT/PLAIN; charset=US-ASCII
> Has a problem been found with the packages? Or is the problem that
> the new versions have been accidentally removed from the repository?
Sorry, I should have made a general announcement about this. We're in
the
process of splitting the data into two tracks to match our packages,
so
that there will be a notion of "release" and "devel" data packages,
where
the former is intended to track BioC-Release and the latter BioC-
Devel. I
rolled back what is in the primary metadata repository to be
considered
"release" and have created a new "devel" metadata repository. The
problem
is that we're in a temporary state of flux as to how to handle notions
of
release/devel in general, which should be cleared up in the very near
future.
In the meantime, a temporary workaround to access the devel metadata
repository can be had with:
'z <- getReposEntry("http://www.bioconductor.org/data/metaData-
devel")'
Then you can use z in the 'repEntry' arguments:
'update.packages2(repEntry=z, prevRepos=FALSE)'
The 'prevRepos' argument turns off the default behavior of
update.packages2 which is that it will instead try to update from the
repository which you originally installed the package from.
Example for install.packages2
install.packages2("hgu95av2", repEntry=z)
-J
------------------------------
Message: 8
Date: Tue, 16 Mar 2004 07:34:00 -0800
From: LIANHE SHAO <lshao2@jhmi.edu>
Subject: [BioC] Canine annotation package
To: "'bioconductor@stat.math.ethz.ch'"
<bioconductor@stat.math.ethz.ch>
Message-ID: <aa3689aa880a.aa880aaa3689@jhmimail.jhmi.edu>
Content-Type: text/plain; charset=us-ascii
Hi,
I am tring to use R to process Canine-related affy chips.
Could anybody tell me where I can find Canine annotation package on
Bioconductor
website?
Regards,
William
------------------------------
Message: 9
Date: Tue, 16 Mar 2004 16:58:08 +0100
From: <arne.muller@aventis.com>
Subject: RE: [BioC] Quantile normalization vs. data distributions
To: <naomi@stat.psu.edu>, <swsmiley@genetics.utah.edu>,
<bioconductor@stat.math.ethz.ch>
Message-ID:
<c80ecafa2acc1b45be45d133ed660ade010bf16f@crbsmxsusr04.pharma. aventis.com="">
Content-Type: text/plain; charset="iso-8859-1"
Hello,
I've two questions regarding the suggestions from Naomi.
1. I've had a look at some density plots (*after* rma bgcorret +
quantile
normalisation across all chips of my experiment). The tails of the
plots look
very similar wheras the at high density some plots differ in shape or
value.
When/how would you consider the two distributions to be equal?
2. As a non-statistician I'm a bit confused that statistical test will
nearly
always find a significant difference between distributions when the
samples
are large (I remember someone mentioned this to me - without
explanations -
about 2 years ago in a posting to the R-list). Is there a way to
"normalize"
the test results (e.g. the p-values) by the size of the sample?
I guess such a significant difference as reported by a test is a
*real*
difference (otherwise all statistical test would be worthless ...).
Can one
assume, that even if the two distributions are statistically
different, one
can treat them as equal judged by visuall investigatigation of a
density plot
or histogram?
What is a large sample? If a test finds a difference between two
distributions, how do I know it's not just because of the sample size?
Is
there something like a "maximum sample size test" (similar to
determining the
power of a test)?
Thanks again for your comments,
+kind regarrds,
Arne
--
Arne Muller, Ph.D.
Toxicogenomics, Aventis Pharma
arne dot muller domain=aventis com
> -----Original Message-----
> From: bioconductor-bounces@stat.math.ethz.ch
> [mailto:bioconductor-bounces@stat.math.ethz.ch]On Behalf Of
> Naomi Altman
> Sent: 15 March 2004 16:05
> To: Stan Smiley; Bioconductor Mailing list
> Subject: Re: [BioC] Quantile normalization vs. data distributions
>
>
> This is a very good question that I have also been puzzling
> over. It seems
> useless to try
> tests of equality of the distribution such as
> Kolmogorov-Smirnov- due to
> the huge sample size you
> would almost certainly get a significant result.
>
> Currently, I am using the following graphical method:
>
> 1. I compute a kernel density estimate of the combined data
> of all probes
> on all the arrays.
> 2. I compute a kernel density estimate of the data for each array.
> 3. I plot both smooths on the same plot, and decide if they
> are the same.
>
> Looking at what I wrote above, I think it would be better in
> steps 1 and 2
> to background correct and
> center each array before combining. It might also be between
> to reduce the
> data to standardized scores before combining, unless
> you think that the overall scaling is due to your "treatment
effect".
>
> It seems like half of what I do is ad hoc, so I always welcome any
> criticisms or suggestions.
>
> --Naomi Altman
>
> At 06:07 PM 3/11/2004, Stan Smiley wrote:
> >Greetings,
> >
> >I have been trying to find a quantitative measure to tell
> when the data
> >distributions
> >between chips are 'seriously' different enough from each
> other to violate
> >the
> >assumptions behind quantile normalization. I've been through
> the archives
> >and seen some discussion of this matter, but didn't come away with
a
> >quantitative measure I
> >could apply to my data sets to assure me that it would be OK
> to use quantile
> >normalization.
> >
> >
> >"Quantile normalization uses a single standard for all
> chips, however it
> >assumes that no serious change in distribution occurs"
> >
> >Could someone please point me in the right direction on this?
> >
> >Thanks.
> >
> >Stan Smiley
> >stan.smiley@genetics.utah.edu
> >
> >_______________________________________________
> >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
>
------------------------------
_______________________________________________
Bioconductor mailing list
Bioconductor@stat.math.ethz.ch
https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
End of Bioconductor Digest, Vol 13, Issue 36
