Time series analysis using predefined sets of genes
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Guido Hooiveld ★ 3.4k
@guido-hooiveld-2020
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Wageningen University, Wageningen, the …
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lidaof ▴ 450
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Hi, STEM is good, i am using it:) On 8/8/07, Hooiveld, Guido <guido.hooiveld at="" wur.nl=""> wrote: > 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]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Daofeng Li,PhD Candidate China Agricultural University
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Ana Conesa ▴ 130
@ana-conesa-2246
Last seen 8.1 years ago
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 Investigaci?n Pr?ncipe 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]] >> >>_______________________________________________ >>Bioconductor mailing list >>Bioconductor at stat.math.ethz.ch >>https://stat.ethz.ch/mailman/listinfo/bioconductor >>Search the archives: http://news.gmane.org/gmane.science.biology.inf >ormatics.conductor >>
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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 Investigaci?n Pr?ncipe 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]] > >> > >>_______________________________________________ > >>Bioconductor mailing list > >>Bioconductor at stat.math.ethz.ch > >>https://stat.ethz.ch/mailman/listinfo/bioconductor > >>Search the archives: http://news.gmane.org/gmane.science.biology.inf > >ormatics.conductor > >> > >
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> -----Original Message----- > From: Nicoline Yvonne Vanloenen [mailto:vanloen2 at lincoln.ac.nz] > Sent: 08 August 2007 22:44 > To: Hooiveld, Guido > Subject: Re: [BioC] Time series analysis using predefined > sets of genes > > Would you mind putting all the replies on the list? > > Working with time-series I would be very interested in them > and not all of them seem to end up on the list. > Nicoline Sure, though the most informative ones were from you and Ana. :-) Guido > -------------------------------------------------------------------- ------------ > From: Nicoline Yvonne Vanloenen [mailto:vanloen2 at lincoln.ac.nz] > Sent: 07 August 2007 23:43 > To: Hooiveld, Guido > Subject: Re: [BioC] Time series analysis using predefined sets of genes > > > I use STEM to define profiles of genesets and then look for pathways in the different profiles, but you could try these papers > > > Bar-Joseph, Z. (2004). Analyzing time series gene expression data. Bioinformatics (Oxford, England), 20(16), 2493-2503. > > > Maraziotis, I. A., Dragomir, A., & Bezerianos, A. (2007). Gene networks reconstruction and time-series prediction from microarray > data using recurrent neural fuzzy networks. IET systems biology, 1(1), 41-50. > -----Original Message----- > From: Ana Conesa [mailto:aconesa at ochoa.fib.es] > Sent: 07 August 2007 23:50 > To: Hooiveld, Guido > Subject: RE: [BioC] Time series analysis using predefined > sets of genes > > Dear Guido > > Take a look to the maSigPro package and publication (Bioinformatics > 2006 22(9):1096-1102). > > Ana > > -----Original Message----- > From: Daofeng Li [mailto:lidaof at gmail.com] > Sent: 08 August 2007 03:49 > To: Hooiveld, Guido > Cc: bioconductor at stat.math.ethz.ch > Subject: Re: [BioC] Time series analysis using predefined > sets of genes > > Hi, > > STEM is good, i am using it:) > > -----Original Message----- > From: Nicoline Yvonne Vanloenen [mailto:vanloen2 at lincoln.ac.nz] > Sent: 08 August 2007 22:44 > To: Hooiveld, Guido > Subject: Re: [BioC] Time series analysis using predefined > sets of genes > > Would you mind putting all the replies on the list? > > Working with time-series I would be very interested in them > and not all of them seem to end up on the list. > Nicoline > On 8 Aug 2007 at 20:49, Hooiveld, Guido wrote: > > > 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 Investigaci?n Pr?ncipe Felipe Valencia, Spain > > > http://bioinfo.cipf.es ===================================== > > > CAMDA2007 Conference @ CIPF > > > http://camda.bioinfo.cipf.es > > > ===================================== > > >
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This passed under my radar, sorry to intervene so late in the thread. I wrote a package that does just that, it's called rHVDM and downloadable from the Bioconductor website. It uses mechanistic models to predict targets of transcription factors, all is needed is a handful of known targets. The relevant paper is here: http:// www.ncbi.nlm.nih.gov/sites/entrez? cmd=Retrieve&db=PubMed&list_uids=16584535&dopt=AbstractPlus&holding=f1 00 0%2Cf1000m%2Cisrctn. OK, end of shameless self-promotion, but any questions and enquiries are more than welcome. Martino On 9 Aug 2007, at 10:42, Hooiveld, Guido wrote: >> -----Original Message----- >> From: Nicoline Yvonne Vanloenen [mailto:vanloen2 at lincoln.ac.nz] >> Sent: 08 August 2007 22:44 >> To: Hooiveld, Guido >> Subject: Re: [BioC] Time series analysis using predefined >> sets of genes >> >> Would you mind putting all the replies on the list? >> >> Working with time-series I would be very interested in them >> and not all of them seem to end up on the list. >> Nicoline > > Sure, though the most informative ones were from you and Ana. :-) > > Guido > > > >> --------------------------------------------------------------------- >> ----------- >> From: Nicoline Yvonne Vanloenen [mailto:vanloen2 at lincoln.ac.nz] >> Sent: 07 August 2007 23:43 >> To: Hooiveld, Guido >> Subject: Re: [BioC] Time series analysis using predefined sets of >> genes >> >> >> I use STEM to define profiles of genesets and then look for >> pathways in the different profiles, but you could try these papers >> >> >> Bar-Joseph, Z. (2004). Analyzing time series gene expression data. >> Bioinformatics (Oxford, England), 20(16), 2493-2503. >> >> >> Maraziotis, I. A., Dragomir, A., & Bezerianos, A. (2007). Gene >> networks reconstruction and time-series prediction from microarray >> data using recurrent neural fuzzy networks. IET systems biology, 1 >> (1), 41-50. > > >> -----Original Message----- >> From: Ana Conesa [mailto:aconesa at ochoa.fib.es] >> Sent: 07 August 2007 23:50 >> To: Hooiveld, Guido >> Subject: RE: [BioC] Time series analysis using predefined >> sets of genes >> >> Dear Guido >> >> Take a look to the maSigPro package and publication (Bioinformatics >> 2006 22(9):1096-1102). >> >> Ana >> > >> -----Original Message----- >> From: Daofeng Li [mailto:lidaof at gmail.com] >> Sent: 08 August 2007 03:49 >> To: Hooiveld, Guido >> Cc: bioconductor at stat.math.ethz.ch >> Subject: Re: [BioC] Time series analysis using predefined >> sets of genes >> >> Hi, >> >> STEM is good, i am using it:) >> > > >> -----Original Message----- >> From: Nicoline Yvonne Vanloenen [mailto:vanloen2 at lincoln.ac.nz] >> Sent: 08 August 2007 22:44 >> To: Hooiveld, Guido >> Subject: Re: [BioC] Time series analysis using predefined >> sets of genes >> >> Would you mind putting all the replies on the list? >> >> Working with time-series I would be very interested in them >> and not all of them seem to end up on the list. >> Nicoline >> On 8 Aug 2007 at 20:49, Hooiveld, Guido wrote: >> >>> 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 Investigaci?n Pr?ncipe Felipe Valencia, Spain >>>> http://bioinfo.cipf.es ===================================== >>>> CAMDA2007 Conference @ CIPF >>>> http://camda.bioinfo.cipf.es >>>> ===================================== >>>> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/ > gmane.science.biology.informatics.conductor >
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