[BioC] RE: Bioconductor Digest, Vol 8, Issue 15

Baker, Stephen Stephen.Baker at umassmed.edu
Wed Oct 8 13:45:02 MEST 2003


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 at umassmed.edu
Worcester, MA 01655  USA


-----Original Message-----
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[mailto:bioconductor-request at stat.math.ethz.ch] 
Sent: Wednesday, October 08, 2003 10:22 AM
To: bioconductor at stat.math.ethz.ch
Subject: Bioconductor Digest, Vol 8, Issue 15


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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 at 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 at aventis.com)
   8. Histogram and boxplot of MM data (donghu at 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 at stat.math.ethz.ch>
Subject: Re: [BioC] "Rgraphviz" installation problem
To: "Weiming Zhang" <Weiming.Zhang at uchsc.edu>
Cc: bioconductor at stat.math.ethz.ch
Message-ID: <16259.58528.241239.832103 at gargle.gargle.HOWL>
Content-Type: text/plain; charset=us-ascii

>>>>> "Weiming" == Weiming Zhang <Weiming.Zhang at 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 at channing.harvard.edu>
Subject: Re: [BioC] Rdbi
To: Kasper Daniel Hansen <K.Hansen at biostat.ku.dk>
Cc: bioconductor at stat.math.ethz.ch
Message-ID:
	
<Pine.GSO.4.40.0310080806390.19036-100000 at 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 at jimmy.harvard.edu>
Subject: Re: [BioC] Rdbi
To: K.Hansen at biostat.ku.dk, bioconductor at stat.math.ethz.ch
Message-ID: <200310081239.IAA17449 at blaise.dfci.harvard.edu>
Content-Type: TEXT/plain; charset=us-ascii


>From: Kasper Daniel Hansen <K.Hansen at biostat.ku.dk>
>To: bioconductor at stat.math.ethz.ch
>Date: Wed, 8 Oct 2003 12:00:18 +0200
>User-Agent: KMail/1.4.3
>MIME-Version: 1.0
>Content-Transfer-Encoding: 8bit
>X-Virus-Scanned: by amavisd-milter (http://amavis.org/)
>X-Virus-Scanned: by amavisd-milter (http://amavis.org/)
>X-Spam-Checker-Version: SpamAssassin 2.60 (1.212-2003-09-23-exp) on 
>hypatia
>X-Spam-Status: No, hits=-4.6 required=5.0 tests=AWL, BAYES_00
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 at 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 at aventis.com>
Subject: [BioC] Affy: Present calls in an eset
To: <bioconductor at stat.math.ethz.ch>
Message-ID:
	
<C80ECAFA2ACC1B45BE45D133ED660ADE410B0D at crbsmxsusr04.pharma.aventis.com>
	
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 at libero.it>
Subject: [BioC] order restricted inference
To: <bioconductor at stat.math.ethz.ch>
Message-ID: <002101c38d9b$f7c95500$81081b9d at 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 at blindglobe.net (A.J. Rossini)
Subject: Re: [BioC] Affy: Present calls in an eset
To: <Arne.Muller at aventis.com>
Cc: bioconductor at stat.math.ethz.ch
Message-ID: <85llrvn9bm.fsf at blindglobe.net>
Content-Type: text/plain; charset=us-ascii

<Arne.Muller at 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 at 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 at aventis.com>
Subject: RE: [BioC] Affy: Present calls in an eset
To: <rossini at u.washington.edu>
Cc: bioconductor at stat.math.ethz.ch
Message-ID:
	
<C80ECAFA2ACC1B45BE45D133ED660ADE410B0E at crbsmxsusr04.pharma.aventis.com>
	
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 at blindglobe.net]
> Sent: 08 October 2003 15:33
> To: Muller, Arne PH/FR
> Cc: bioconductor at stat.math.ethz.ch
> Subject: Re: [BioC] Affy: Present calls in an eset
> 
> 
> <Arne.Muller at 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 at 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 at itsa.ucsf.edu
Subject: [BioC] Histogram and boxplot of MM data
To: bioconductor at stat.math.ethz.ch
Message-ID: <200310080018.h980IEv19068 at 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 at stat.psu.edu>
Subject: [BioC] marrayClass - how to extract expr values for a gene
To: bioconductor at stat.math.ethz.ch
Message-ID: <6.0.0.22.2.20031008091634.01c52d10 at 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 at yahoo.it>
Subject: [BioC] time-course experiments
To: bioconductor at stat.math.ethz.ch
Message-ID: <20031008100236.12628.qmail at 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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