[BioC] Time series analysis using predefined sets of genes

[Hooiveld, Guido]

Thanks all for your feed-back; I certainly got some suggestions to go after.

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
 

> -----Original Message-----
> From: Ana Conesa [mailto:aconesa at ochoa.fib.es] 
> Sent: 08 August 2007 12:55
> To: Hooiveld, Guido; bioconductor at stat.math.ethz.ch
> Cc: aconesa at cipf.es
> Subject: RE: [BioC] Time series analysis using predefined 
> sets of genes
> 
> 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
> >>
> >>
> >>	[[alternative HTML version deleted]]
> >>
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> >ormatics.conductor
> >>
> 
>