[BioC] Time series analysis using predefined sets of genes

[Ana Conesa]

Hi Guido,

I am not sure if you got my early reply.
You can have a look to the maSigPro package (Bioinformatics 2006
22(9):1096-1102). This will give you the gene expression pattern
along time and tell you is there are significant changes. If you want
to look for specific sets of genes you can use these as input data.
I have recently developed a number of scripts (modifications of
maSigPro functions) to assess significant changes for genes that
share a common annotation. This I think resembles your question. You
only need to indicate the grouping of your genes (or
annotations),load the modified versions and run the program. I am
enclosing you the modified functions in case you are interested.
There is aslo a maSigProfunScript.R includes which tells a bit how to
proceed. I might include this functions in a next maSigPro version...

Hope this helps

Ana

-------------------------------------
Ana Conesa, PhD
Bioinformatics Department
Centro de Investigación Príncipe Felipe
Valencia, Spain
http://bioinfo.cipf.es
=====================================
CAMDA2007 Conference @ CIPF
http://camda.bioinfo.cipf.es
=====================================



>
>
>---- Mensaje Original ----
>De: Guido.Hooiveld at wur.nl
>Para: bioconductor at stat.math.ethz.ch
>Asunto: RE: [BioC] Time series analysis using predefined sets of
>genes
>Fecha: Tue, 7 Aug 2007 23:22:56 +0200
>
>>Dear list,
>>
>>Not a 'core' BioC question, but I was wondering whether someone
>could point me to a paper/tool that allows the analysis of time
>series microarray experiments on the basis of predefined sets of
>genes. 
>>In other words, I would like to know how predefined sets of genes
>(not indivual genes) behave during in a time course; e.g. pathway x
>rapidly goes up and then decreases, pathway y is not changed etc.
>>
>>I came across STEM [Short Time-series Expression Miner]
>(www.cs.cmu.edu/~jernst/stem/) that seems to do such analyses, but I
>was wondering whether other approaches exist as well.
>>
>>TIA,
>>Guido
>>
>> 
>>------------------------------------------------
>>Guido Hooiveld, PhD
>>Nutrition, Metabolism & Genomics Group
>>Division of Human Nutrition
>>Wageningen University
>>Biotechnion, Bomenweg 2
>>NL-6703 HD Wageningen
>>the Netherlands
>>
>>tel: (+)31 317 485788
>>fax: (+)31 317 483342
>>
>>internet:   http://nutrigene.4t.com
>>email:      guido.hooiveld at wur.nl
>>
>>
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