clustering of microarray time-series data
1
0
Entering edit mode
boczniak767 ▴ 740
@maciej-jonczyk-3945
Last seen 25 days ago
Poland
>Message: 13 >Date: Fri, 15 Oct 2010 14:47:44 -0400 >From: avehna <avhena at="" gmail.com=""> >To: "bioconductor at stat.math.ethz.ch" <bioconductor at="" stat.math.ethz.ch=""> >Subject: [BioC] clustering of microarray time-series data >Message-ID: ><aanlktim6kiep+heaxqwj27cl9a-vsoqmpladl_a87==l at="" mail.gmail.com=""> >Content-Type: text/plain > >Dear All, > >I have a time series data from two different samples (treatment A and >treatment B) at 3 different time points (0 hr, 6 hr and 24 hr) , the control >is time = 0 hr. Both datasets have three replicates. > >I have already analyzed these data using limma, just to have an idea of >regulated genes at 6 hr and 24 hr, but now I would like to cluster the data >across the time points to group the genes according to their expression >profile. > >My question is: what method should I use in order to do this? I have checked >already the timecourse<http: www.bioconductor.org="" packages="" release="" bioc="" html="" time="" course.html="">package, >but I'm afraid it includes a different method for defining >differentially expressed genes (and I would like to be consistent with >limma's results). Any clue? > You can try analyse your data using MaSigPro package. It compares treatment profiles, draws plots of profiles and also clusters data. It don't give you contrasts between time points, but compare whole time profiles. Personally I don't use it for clustering, I tried pvclust R package but most probably I'll use JMP Genomics for this. Nevertheless I strongly recommend MaSigPro. > > Maciej Jo?czyk, MSc Department of Plant Molecular Ecophysiology Institute of Plant Experimental Biology Faculty of Biology, University of Warsaw 02-096 Warszawa, Miecznikowa 1 ___________________________________ NOCC, http://nocc.sourceforge.net
Microarray Clustering limma maSigPro Microarray Clustering limma maSigPro • 1.3k views
ADD COMMENT
0
Entering edit mode
avehna ▴ 240
@avehna-3930
Last seen 10.2 years ago
Thank you Maciej. I will try it and let you know. Avhena 2010/10/16 Maciej Jończyk <mjonczyk@biol.uw.edu.pl> > >Message: 13 > >Date: Fri, 15 Oct 2010 14:47:44 -0400 > >From: avehna <avhena@gmail.com> > >To: "bioconductor@stat.math.ethz.ch" <bioconductor@stat.math.ethz.ch> > >Subject: [BioC] clustering of microarray time-series data > >Message-ID: > ><aanlktim6kiep+heaxqwj27cl9a-vsoqmpladl_a87==l@mail.gmail.com> > >Content-Type: text/plain > > > >Dear All, > > > >I have a time series data from two different samples (treatment A and > >treatment B) at 3 different time points (0 hr, 6 hr and 24 hr) , the > control > >is time = 0 hr. Both datasets have three replicates. > > > >I have already analyzed these data using limma, just to have an idea of > >regulated genes at 6 hr and 24 hr, but now I would like to cluster the > data > >across the time points to group the genes according to their expression > >profile. > > > >My question is: what method should I use in order to do this? I have > checked > >already the > timecourse< > http://www.bioconductor.org/packages/release/bioc/html/timecourse.html > >package, > >but I'm afraid it includes a different method for defining > >differentially expressed genes (and I would like to be consistent with > >limma's results). Any clue? > > > > You can try analyse your data using MaSigPro package. > It compares treatment profiles, draws plots of profiles and also > clusters data. > > It don't give you contrasts between time points, but compare whole time > profiles. > > Personally I don't use it for clustering, I tried pvclust R package but > most probably I'll use JMP Genomics for this. Nevertheless I strongly > recommend MaSigPro. > > > > > > > > Maciej Jończyk, MSc > Department of Plant Molecular Ecophysiology > Institute of Plant Experimental Biology > Faculty of Biology, University of Warsaw > 02-096 Warszawa, Miecznikowa 1 > > > > ___________________________________ > NOCC, http://nocc.sourceforge.net > > > > [[alternative HTML version deleted]]
ADD COMMENT

Login before adding your answer.

Traffic: 541 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6