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Simon Lin | 1 Feb 2006 01:34
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affy: How to back transform the matrix to a vector? (low-level imaging)

I am trying to transform the vector (pm and mm) extracted from  <at> exprs to a 
matrix (2-D layout), so an image can be plotted. It works out.

Now, when I back-transform the image matrix to the vector, there are some 
trouble. See the code below.

Seems that the matrix has to be transposed somehow. Any ideas? 
Thanks! -Simon

   library (affy)

   data (affybatch.example) # has 3 chips

   x<- affybatch.example

   m.vector <- log2( x <at> exprs[, 2]) # take the second array

   x.pos <- (1:nrow(x)) - (1 + getOption("BioC")$affy$xy.offset)

   y.pos <- (1:ncol(x)) - (1 + getOption("BioC")$affy$xy.offset)

   # from vector to matrix

   m <- as.matrix(rev(as.data.frame(matrix(m.vector, nrow = length(x.pos),

                ncol = length(y.pos)))))

   # ????????????????

   # from matrix to vector
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Kasper Daniel Hansen | 1 Feb 2006 04:16
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Re: affy: How to back transform the matrix to a vector? (low-level imaging)


On Jan 31, 2006, at 4:34 PM, Simon Lin wrote:

> I am trying to transform the vector (pm and mm) extracted from  
>  <at> exprs to a
> matrix (2-D layout), so an image can be plotted. It works out.

Yes. I assume the code given below has been snapped from
   getMethod("image", "AffyBatch")\

(Why do you want to generate that code anyway, when suitable image  
functions exists?)

>
>
> Now, when I back-transform the image matrix to the vector, there  
> are some
> trouble. See the code below.
>
>
>
> Seems that the matrix has to be transposed somehow. Any ideas?
> Thanks! -Simon
>
>
>
>    library (affy)
>
>    data (affybatch.example) # has 3 chips
>
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Kasper Daniel Hansen | 1 Feb 2006 06:35
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Re: ad hoc tools for affy tiling arrays?

In a a sense tiling arrays are more general tools than expression  
arrays. What you are looking for (and hence your method of analysis)  
is (or at least should be) dependent on your research question. In  
comparison, with an expression array you are interested in genes that  
are DE between different experimental conditions.

/Kasper

On Jan 26, 2006, at 1:36 AM, Dario Greco wrote:

> hi all,
> we are probably going to use affymetrix tiling arrays for human.
> i have understood that in some ways it is possible to use gcrma for  
> image
> preprocessing and that the quantile normalization might be a  
> reasonable
> method.
> but i was wondering if there is (or if there is going to be) any ad  
> hoc tool
> in bioconductor also for the later steps of the analysis and  
> interpretations
> of such experiments.
> any suggestions are warmly appreciated.
> thanks,
>
> greetings
> d
>
> -- 
>
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Li Long | 1 Feb 2006 10:55
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Re: Graph Layout

>> Hi,
>>
>>  I want to draw graph using a spring-embedding.
>>
>>  Regards,
>>  Kaustubh
>
> This takes a little bit of programming.  The following
> is far from an ideal design, but gives some of the flavor
> of how you can use the RBGL layout functions.  As far
> as I can tell there are three: circle.layout,
> kamada.kawai.spring.layout, and fruchtermanReingoldForceDirectedLayout.
> I am not sure the latter is behaving correctly, but the first
> two are.

The latter (fruchtermanReingoldForceDirectedLayout) is a lot more
sensitive to input parameters, sometimes, it does make one wonder if it
works correctly.  It will be discussed in more details in the vignette.

Li
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Sean Davis | 1 Feb 2006 12:41
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Re: ad hoc tools for affy tiling arrays?

Dario,

I'll second this opinion.  The design of the array, hypotheses being tested,
sample characteristics, genomic features and how they relate to the features
on the array, experimental design, and tiling array technology all play a
VERY LARGE part in defining what can and should be done in terms of
normalization and analysis.  I'm not sure that relying on any "canned"
solution for tiling arrays is possible at this time given the diverse nature
of experiments that can be performed with them.

Sean

On 2/1/06 12:35 AM, "Kasper Daniel Hansen" <khansen@...>
wrote:

> In a a sense tiling arrays are more general tools than expression
> arrays. What you are looking for (and hence your method of analysis)
> is (or at least should be) dependent on your research question. In
> comparison, with an expression array you are interested in genes that
> are DE between different experimental conditions.
> 
> /Kasper
> 
> On Jan 26, 2006, at 1:36 AM, Dario Greco wrote:
> 
>> hi all,
>> we are probably going to use affymetrix tiling arrays for human.
>> i have understood that in some ways it is possible to use gcrma for
>> image
>> preprocessing and that the quantile normalization might be a
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Dario Greco | 1 Feb 2006 13:11
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Re: ad hoc tools for affy tiling arrays?

hello,
thanks a lot for your messages.
actually, in case we will approach to the tiling arrays, we would like to 
screen the transcriptome, and not the genome.
we would actually like to find non coding (novel ?!?!) RNAs having a 
different expresison pattern in several samples...or at least this would 
be the ultimate dream!
so, in this situation, what would be the best analytical approach, in your 
opinion?
thanks again,
yours
d

--

-- 

Dario Greco

Institute of Biotechnology - University of Helsinki
Building Cultivator II
P.O.Box 56	Viikinkaari 4
FIN-00014	Finland

Office: +358 9 191 58951
Fax: +358 9 191 58952
Mobile: +358 44 023 5780

Lab WebPage: http://www.biocenter.helsinki.fi/bi/dna-microarray/
Personal WebPage: http://www.biocenter.helsinki.fi/bi/dna-
microarray/dario.htm
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Sean Davis | 1 Feb 2006 13:38
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Re: ad hoc tools for affy tiling arrays?


On 2/1/06 7:11 AM, "Dario Greco" <dario.greco@...> wrote:

> hello,
> thanks a lot for your messages.
> actually, in case we will approach to the tiling arrays, we would like to
> screen the transcriptome, and not the genome.

On tiling arrays, there is no distinction between transcriptome and
genome--you are measuring every probe along the genome.  Some will have
signal and may represent transcription, while some will not.  You will have
to map each probe to genomic features (or lack thereof) before you know what
you are measuring.

> we would actually like to find non coding (novel ?!?!) RNAs having a
> different expresison pattern in several samples...or at least this would
> be the ultimate dream!

You will likely find many novel transcripts, based on our experience and
from that of others in the literature.  Determining differential expression
is potentially a very difficult problem.  You are measuring at discrete
probes, so you have to first determine what constitutes transcription, then
whether it is represents a novel transcript, and finally if you are seeing
differential expression.  Each of these is an area of research
in-and-of-itself.  

> so, in this situation, what would be the best analytical approach, in your
> opinion?

This cannot be summarized in any meaningful way in an email.  There are just
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Thomas Litman | 1 Feb 2006 16:49

microarray database

I would like to setup a microarray management system and database for spotted ararys. Is there any
particular software (either public domain or commercial) that you would recommend? 
Thank you very much for your advice 

- Thomas Litman, Ph.D.

	[[alternative HTML version deleted]]
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Sean Davis | 1 Feb 2006 18:15
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Re: microarray database

Thomas,

There is a list here:

http://ihome.cuhk.edu.hk/~b400559/arraysoft_database.html
http://ihome.cuhk.edu.hk/~b400559/arraysoft_public.html

Also, GMOD has an expression component.  Finally, have you looked at maDB
(the bioconductor package)?

Sean

On 2/1/06 10:49 AM, "Thomas Litman" <THL@...> wrote:

> I would like to setup a microarray management system and database for spotted
> ararys. Is there any particular software (either public domain or commercial)
> that you would recommend?
> Thank you very much for your advice
> 
> - Thomas Litman, Ph.D.
> 
> 
> [[alternative HTML version deleted]]
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@...
> https://stat.ethz.ch/mailman/listinfo/bioconductor
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Saurin D. Jani | 1 Feb 2006 18:30
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Re: microarray database

Dear Dr. Litman,

Here is MUSC DNA Microarray Database and Project Management System at Medical
University of South Carolina, Charleston, SC. This system is also integrated
with microarray anlaysis system ArrayQuest. Both systems are web-based.

Pubmed Reference for MUSC DNA Microarray Database(Argraves et al., 2003).
(http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=14668234&dopt=Abstract)

Pubmed Reference for ArrayQuest. ArrayQuest is a web-accessible program 
for the
analysis of DNA microarray data (Argraves et al., 2005)
(http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=16321157&query_hl=1)

URL for Microarray Database:
http://proteogenomics.musc.edu/ma/musc_madb.php?page=home&act=manage

URL for on-line DNA microarray anlaysis system:
http://proteogenomics.musc.edu/arrayquest.html

Saurin

--

-- 
|------------------------------------------------
| Saurin D. Jani,MS
| Statistical and Research Analyst
|
| Department of Cell Biology and Anatomy
| Medical  University of South Carolina (MUSC)
| 173 Ashley Ave
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