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Baker, Stephen
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@baker-stephen-469
Last seen 9.7 years ago
Gary Churchill at the Jackson Labs in Maine has an R program on his
website for performing mixed models ANOVA on microarray data. The
only
problem with this is it uses least squares to fit the model (which
would
include a within-subjects factor for the time effect) and would
requires
that there are no missing data points and all subjects being measured
at
the same time points. This is because the least squares solution
involves inverting a matrix and missing data would make it not of full
rank.
An alternative approach which wouldn't be done in R would be to use
PROC
MIXED in the SAS stats package. This uses maximum likelihood to fit
mixed models and works well. If you really want to try to do it in R,
Yudi Pawitan at Dept. of Stats at University of Cork in Ireland has a
book and a set of R programs which would give you a leg up on it:
http://statistics.ucc.ie/staff/yudi/likelihood/index.htm
-.- -.. .---- .--. ..-.
Stephen P. Baker, MScPH, PhD (ABD) (508) 856-2625
Sr. Biostatistician- Information Services
Lecturer in Biostatistics (775) 254-4885 fax
Graduate School of Biomedical Sciences
University of Massachusetts Medical School, Worcester
55 Lake Avenue North
stephen.baker@umassmed.edu
Worcester, MA 01655 USA
-----Original Message-----
From: bioconductor-request@stat.math.ethz.ch
[mailto:bioconductor-request@stat.math.ethz.ch]
Sent: Wednesday, October 08, 2003 10:22 AM
To: bioconductor@stat.math.ethz.ch
Subject: Bioconductor Digest, Vol 8, Issue 15
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"Re: Contents of Bioconductor digest..."
Today's Topics:
1. Re: "Rgraphviz" installation problem (Martin Maechler)
2. Re: Rdbi (Vincent Carey 525-2265)
3. Re: Rdbi (John Zhang)
4. Affy: Present calls in an eset (Arne.Muller@aventis.com)
5. order restricted inference (Stefano Barbi)
6. Re: Affy: Present calls in an eset (A.J. Rossini)
7. RE: Affy: Present calls in an eset (Arne.Muller@aventis.com)
8. Histogram and boxplot of MM data (donghu@itsa.ucsf.edu)
9. marrayClass - how to extract expr values for a gene (Naomi
Altman)
10. time-course experiments (edoardo missiaglia)
----------------------------------------------------------------------
Message: 1
Date: Wed, 8 Oct 2003 12:19:12 +0200
From: Martin Maechler <maechler@stat.math.ethz.ch>
Subject: Re: [BioC] "Rgraphviz" installation problem
To: "Weiming Zhang" <weiming.zhang@uchsc.edu>
Cc: bioconductor@stat.math.ethz.ch
Message-ID: <16259.58528.241239.832103@gargle.gargle.HOWL>
Content-Type: text/plain; charset=us-ascii
>>>>> "Weiming" == Weiming Zhang <weiming.zhang@uchsc.edu>
>>>>> on 07 Oct 2003 10:52:06 -0600 writes:
Weiming> Hi,
Weiming> Problem solved. I changed linux kernel-headers from
2.4.20
to 2.4.9 and
Weiming> it worked.
Weiming> Thank you all for the help, especially Robert.
Interesting.... but quite problematic, since 2.4.20 is not a beta
Linux
kernel but a "production" one, and a very widely used one too: Redhat
9's kernel (at least here) *is* 2.4.20.
So I assume the graphviz need to be
notified about this as well, right?
Martin
Weiming> On Mon, 2003-10-06 at 20:21, Vincent Carey 525-2265
wrote:
>> > from common.h:10,
>> > from Rgraphviz.c:1:
>> > /usr/include/bits/local_lim.h:36:26: linux/limits.h: No such
file or
>> > directory
>> > In file included from Rgraphviz.c:1:
>> > common.h:19:20: render.h: No such file or directory
>> > common.h:20:19: graph.h: No such file or directory
>> > common.h:21:22: dotprocs.h: No such file or directory
>> > common.h:22:24: neatoprocs.h: No such file or directory
>> > common.h:23:20: adjust.h: No such file or directory
>> > Rgraphviz.c:2:20: circle.h: No such file or directory
>>
>> these errors suggest that the graphviz installation from
>> RPM is not supporting development level resources.
>>
>> > -IboostIncl -ftemplate-depth-30 -fPIC -g -O2 -c bfsBGL.cpp
-o
bfsBGL.o
>> > In file included from /usr/include/bits/posix1_lim.h:126,
>> > from /usr/include/limits.h:144,
>> > from
>> > /usr/lib/gcc-lib/i386-redhat-linux/2.96/include/limits.h:130,
>> > from
>> > /usr/lib/gcc-lib/i386-redhat-
linux/2.96/include/syslimits.h:7,
>> > from
>> > /usr/lib/gcc-lib/i386-redhat-linux/2.96/include/limits.h:11,
>> > from boostIncl/boost/config/suffix.hpp:26,
>> > from boostIncl/boost/config.hpp:57,
>> > from RBGL.h:4,
>> > from bfsBGL.cpp:5:
>> > /usr/include/bits/local_lim.h:36:26: linux/limits.h: No such
file or
>>
>> these errors suggest inadequacy of your linux installation.
>> the missing files are basic development resources. you may
>> have chosen an "end-user-only" distribution, or the linux
>> installation is nonstandard.
>>
>> are you able to build R from source? i suspect not.
>>
------------------------------
Message: 2
Date: Wed, 8 Oct 2003 08:12:17 -0400 (EDT)
From: Vincent Carey 525-2265 <stvjc@channing.harvard.edu>
Subject: Re: [BioC] Rdbi
To: Kasper Daniel Hansen <k.hansen@biostat.ku.dk>
Cc: bioconductor@stat.math.ethz.ch
Message-ID:
<pine.gso.4.40.0310080806390.19036-100000@capecod.bwh.harvard.edu>
Content-Type: TEXT/PLAIN; charset=US-ASCII
> I'm using R 1.7.1 and Bioconductor release 1.2 under Redhat Linux 8.
>
> The package SAGElyzer (which is version 1.1.17 in BioC 1.2) requires
> the library Rdbi, when running under UNIX. This package is not
> available from CRAN anymore. You may still get it from
> http://rdbi.sourceforge.net/. Rdbi seems to have been replaced by
the
> package DBI, which is available from CRAN. I have looked at the
> development sources for SAGElyzer (v 1.2.4) and it seems to have the
> same requirements as v1.1.17.
>
> Questions/thoughts:
> 1) Is DBI sufficiently developed to replace Rdbi? If so, I guess it
> needs to be fixed in SAGElyzer.
DBI is pretty mature, the problem is that no one has written
DBI-compliant drivers for postgres. ROracle and RMySQL from CRAN do
satisfy DBI.
> 2) Otherwise I think a mention of this issue ought to be placed in
the
> FAQ since Rdbi seems to have disappeared from CRAN.
agreed. And anyone with an interest in/time to write a DBI-compliant
RPostgres is encouraged to do this!
------------------------------
Message: 3
Date: Wed, 8 Oct 2003 08:39:57 -0400 (EDT)
From: John Zhang <jzhang@jimmy.harvard.edu>
Subject: Re: [BioC] Rdbi
To: K.Hansen@biostat.ku.dk, bioconductor@stat.math.ethz.ch
Message-ID: <200310081239.IAA17449@blaise.dfci.harvard.edu>
Content-Type: TEXT/plain; charset=us-ascii
>From: Kasper Daniel Hansen <k.hansen@biostat.ku.dk>
>To: bioconductor@stat.math.ethz.ch
>Date: Wed, 8 Oct 2003 12:00:18 +0200
>User-Agent: KMail/1.4.3
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autolearn=ham
version=2.60
>Questions/thoughts:
>1) Is DBI sufficiently developed to replace Rdbi? If so, I guess it
>needs to
>be fixed in SAGElyzer.
I am evaluating DBI and will make a decision on that soon.
>2) Otherwise I think a mention of this issue ought to be placed in
the
>FAQ
>since Rdbi seems to have disappeared from CRAN.
I have included the source for Rdbi and Rdbi.PgSQL in the vignette.
Thank you for your comments.
>--
>Kasper Daniel Hansen, Research Assistent
>Department of Biostatistics, University of Copenhagen
>
>_______________________________________________
>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: 4
Date: Wed, 8 Oct 2003 14:54:56 +0200
From: <arne.muller@aventis.com>
Subject: [BioC] Affy: Present calls in an eset
To: <bioconductor@stat.math.ethz.ch>
Message-ID:
<c80ecafa2acc1b45be45d133ed660ade410b0d@crbsmxsusr04.pharma.aventis.co m="">
Content-Type: text/plain; charset="iso-8859-1"
Hello,
I'm quite new to Bioconductor/affy, and I was wondering if there's a
simple way to include the absent/present call for a gene in the
outputfile generated with write.exprs(eset, file='boo') in theaffy
package.
the eset was generated with
eset <- expresso(cel, bgcorrect.method = 'rma', normalize.method =
'qspline', pmcorrect.method = 'pmonly',
summary.method='liwong')
For further analyses I'd like to exclude genes that are absent in all
chips.
thanks a lot for your help,
Arne
------------------------------
Message: 5
Date: Wed, 8 Oct 2003 14:59:11 +0200
From: "Stefano Barbi" <stefanobarbi@libero.it>
Subject: [BioC] order restricted inference
To: <bioconductor@stat.math.ethz.ch>
Message-ID: <002101c38d9b$f7c95500$81081b9d@BARBI>
Content-Type: text/plain; charset="iso-8859-1"
Dear all,
I wonder if anyone has implemented or is intentioned to implement
the procedure described in Peddada et al. "Gene selection and
clustering
for time-course and dose-response microarray experiments using
order-restricted inference" in the Bioconductor or R environment. If
not, do you know if there are other packages avalaible for R dealing
with order restricted inference?
Lastly, I would appreciate any suggestions of other approches to
classify conveniently time profiles.
Thank you in advance.
Best wishes,
Stefano.
------------------------------
Message: 6
Date: Wed, 08 Oct 2003 06:33:01 -0700
From: rossini@blindglobe.net (A.J. Rossini)
Subject: Re: [BioC] Affy: Present calls in an eset
To: <arne.muller@aventis.com>
Cc: bioconductor@stat.math.ethz.ch
Message-ID: <85llrvn9bm.fsf@blindglobe.net>
Content-Type: text/plain; charset=us-ascii
<arne.muller@aventis.com> writes:
> Hello,
>
> I'm quite new to Bioconductor/affy, and I was wondering if there's a
> simple way to include the absent/present call for a gene in the
> outputfile generated with write.exprs(eset, file='boo') in theaffy
> package.
>
> the eset was generated with
>
> eset <- expresso(cel, bgcorrect.method = 'rma', normalize.method =
> 'qspline', pmcorrect.method = 'pmonly',
> summary.method='liwong')
>
> For further analyses I'd like to exclude genes that are absent in
all
> chips.
That's tough. It isn't clear what a sensible definition of absent is.
Or present.
Do you mean "expressed" ? "Differentially expressed" ? "sort of
differentially expressed but not too weakly expressed?". For any of
these, you'll need a precise definition (there isn't any in
Bioconductor), and you can compute your own.
(I know that MAS will make these calls; I'm only familiar with Rosetta
Resolver's variant, and they don't really make sense to me -- to be
precise, I know numerically how they are derived, but fail to why they
realistically connect biologically or technologically without a great
deal of assumptions and a wild imagination).
best,
-tony
--
rossini@u.washington.edu
http://www.analytics.washington.edu/
Biomedical and Health Informatics University of Washington
Biostatistics, SCHARP/HVTN Fred Hutchinson Cancer Research
Center
UW (Tu/Th/F): 206-616-7630 FAX=206-543-3461 | Voicemail is unreliable
FHCRC (M/W): 206-667-7025 FAX=206-667-4812 | use Email
CONFIDENTIALITY NOTICE: This e-mail message and any
attachme...{{dropped}}
------------------------------
Message: 7
Date: Wed, 8 Oct 2003 15:47:42 +0200
From: <arne.muller@aventis.com>
Subject: RE: [BioC] Affy: Present calls in an eset
To: <rossini@u.washington.edu>
Cc: bioconductor@stat.math.ethz.ch
Message-ID:
<c80ecafa2acc1b45be45d133ed660ade410b0e@crbsmxsusr04.pharma.aventis.co m="">
Content-Type: text/plain; charset="iso-8859-1"
Hi,
I get your point with interpreting absent/present calls. Technically
it's a nice feature, becasue one can just discard the majority of the
genes on the chip for further analysis. In fact I think absent/present
calls make sense in terms of biology, since just a fraction of the
genes
are realy expressed at a time. How to express this numerially is a
different story (and I guess a difficult one).
Anyway, with MAS the calls are calculated anyway, can't they? So, I'd
be
nice (at least for "completness") to add a "mascall" method to the
exprSet objects generated by affy. What do you think?
By the way, if you ignore the call, do you set an arbitrary intensity
cutoff later in your analysis, or do just reley on the statistics
(anova
p-value or whatever)?
regards,
Arne
> -----Original Message-----
> From: A.J. Rossini [mailto:rossini@blindglobe.net]
> Sent: 08 October 2003 15:33
> To: Muller, Arne PH/FR
> Cc: bioconductor@stat.math.ethz.ch
> Subject: Re: [BioC] Affy: Present calls in an eset
>
>
> <arne.muller@aventis.com> writes:
>
> > Hello,
> >
> > I'm quite new to Bioconductor/affy, and I was wondering if
> there's a simple
> > way to include the absent/present call for a gene in the
> outputfile generated
> > with write.exprs(eset, file='boo') in theaffy package.
> >
> > the eset was generated with
> >
> > eset <- expresso(cel, bgcorrect.method = 'rma',
> normalize.method =
> > 'qspline', pmcorrect.method = 'pmonly',
> > summary.method='liwong')
> >
> > For further analyses I'd like to exclude genes that are
> absent in all chips.
>
> That's tough. It isn't clear what a sensible definition of absent
is.
> Or present.
>
> Do you mean "expressed" ? "Differentially expressed" ? "sort of
> differentially expressed but not too weakly expressed?". For any of
> these, you'll need a precise definition (there isn't any in
> Bioconductor), and you can compute your own.
>
> (I know that MAS will make these calls; I'm only familiar with
Rosetta
> Resolver's variant, and they don't really make sense to me -- to be
> precise, I know numerically how they are derived, but fail to why
they
> realistically connect biologically or technologically without a
great
> deal of assumptions and a wild imagination).
>
> best,
> -tony
>
> --
> rossini@u.washington.edu
> http://www.analytics.washington.edu/
> Biomedical and Health Informatics University of Washington
> Biostatistics, SCHARP/HVTN Fred Hutchinson Cancer
> Research Center
> UW (Tu/Th/F): 206-616-7630 FAX=206-543-3461 | Voicemail is
unreliable
> FHCRC (M/W): 206-667-7025 FAX=206-667-4812 | use Email
>
> CONFIDENTIALITY NOTICE: This e-mail message and any attachments may
be
> confidential and privileged. If you received this message in error,
> please destroy it and notify the sender. Thank you.
>
------------------------------
Message: 8
Date: Tue, 07 Oct 2003 17:18:14 PDT
From: donghu@itsa.ucsf.edu
Subject: [BioC] Histogram and boxplot of MM data
To: bioconductor@stat.math.ethz.ch
Message-ID: <200310080018.h980IEv19068@itsa.ucsf.edu>
Content-Type: text/plain
Hi,
In Bioconductor, what data does "hist" or "boxplot" use by default?
Is
it PM data? How can I make similar plots with MM data? Thanks.
Donglei Hu
------------------------------
Message: 9
Date: Wed, 08 Oct 2003 09:18:22 -0400
From: Naomi Altman <naomi@stat.psu.edu>
Subject: [BioC] marrayClass - how to extract expr values for a gene
To: bioconductor@stat.math.ethz.ch
Message-ID: <6.0.0.22.2.20031008091634.01c52d10@stat.psu.edu>
Content-Type: text/plain; charset="us-ascii"; format=flowed
On spotted arrays with duplicate spots for each gene, I would like to
extract all the normalized expression values for each gene. How can I
do this? Thanks,
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
------------------------------
Message: 10
Date: Wed, 8 Oct 2003 12:02:36 +0200 (CEST)
From: edoardo missiaglia <edo_missiaglia@yahoo.it>
Subject: [BioC] time-course experiments
To: bioconductor@stat.math.ethz.ch
Message-ID: <20031008100236.12628.qmail@web11701.mail.yahoo.com>
Content-Type: text/plain; charset=iso-8859-1
Dear all,
I am now working on some time-course experiments and I
have applied to them some classical statistic methods
to identify genes that change their expression between
time points. However I have read few papers (such as
Peddada et al. Gene selection and clustering for
time-course and dose-response microarray experiments
using order-restricted inference; GUO, X et al
Statistical significance analysis of longitudinal gene expression
data;
etc..) where they describe specific methods for the analysis of this
type of data. Unfortunately my background (I am biologist) make
difficult to transform the algorithms reported in these papers in
something usable in R. In the same time, I could not find packages in
bioconductor that face this kind of problems ( there is only GeneTS
written by Korbinian Strimmer, that is useful in a cyclic time-course
experiment). I was wondering if anybody has already developed a
package
or some functions usable in R specifically designed for time-course
experiment that consider the particular structure of this data.
Otherwise is there anybody interest in developing something from
scratch? Thank you very much in advance for your help.
Best wishes,
edoardo
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