How to get started with bioconductor ?
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@luke-whitaker-408
Last seen 9.6 years ago
Hello, I need to do some straightforward analysis on two-dye microarray data. I want to be able to estimate fold-regulation for each gene between two conditions (eg treated/untreated etc). The first chips I had to analyse had 200 genes and I "rolled my own" analysis using lm() etc. which seemed to work OK, but I now have chips with aprox 1,700 genes and the method I was using (essentially ANOVA with one level of explanatory factor per gene) now runs out of memory. I would like to use Bioconductor, but looking at the documentation, I cannot see the forest for the trees. I have had a look at limma, and think it may do what I want, but it seems to use quite a sophisticated bayesian analysis which I do not completely understand, and I would prefer to start at least with something fairly simple. As usual, I have much less time than I would like to do this. Is there one basic bioconductor function for estimating fold regulation in a two dye experiment ? Thanks, Luke Whitaker Inpharmatica
Bayesian limma Bayesian limma • 1.2k views
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@michael-watson-iah-c-378
Last seen 9.6 years ago
Luke For basic data reading and normalisation functions, look at the marray* and limma classes (they both have very good documentation) For simple t tests between two conditions, look at multtest And for ANOVA style models, look outside of Bioconductor at Gary Churchills MAANOVA library (http://www.jax.org/staff/churchill/labsite/software/anova/rmaanova/) (I know, I know, heresy...) Mick -----Original Message----- From: Luke Whitaker [mailto:luke@inpharmatica.co.uk] Sent: 10 September 2003 10:26 To: bioconductor@stat.math.ethz.ch Subject: [BioC] How to get started with bioconductor ? Hello, I need to do some straightforward analysis on two-dye microarray data. I want to be able to estimate fold-regulation for each gene between two conditions (eg treated/untreated etc). The first chips I had to analyse had 200 genes and I "rolled my own" analysis using lm() etc. which seemed to work OK, but I now have chips with aprox 1,700 genes and the method I was using (essentially ANOVA with one level of explanatory factor per gene) now runs out of memory. I would like to use Bioconductor, but looking at the documentation, I cannot see the forest for the trees. I have had a look at limma, and think it may do what I want, but it seems to use quite a sophisticated bayesian analysis which I do not completely understand, and I would prefer to start at least with something fairly simple. As usual, I have much less time than I would like to do this. Is there one basic bioconductor function for estimating fold regulation in a two dye experiment ? Thanks, Luke Whitaker Inpharmatica _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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rgentleman ★ 5.5k
@rgentleman-7725
Last seen 8.9 years ago
United States
On Wed, Sep 10, 2003 at 03:12:24PM +0100, michael watson (IAH-C) wrote: > Luke > > For basic data reading and normalisation functions, look at the marray* and limma classes (they both have very good documentation) > For simple t tests between two conditions, look at multtest > And for ANOVA style models, look outside of Bioconductor at Gary Churchills MAANOVA library (http://www.jax.org/staff/churchill/labsite/software/anova/rmaanova/) (I know, I know, heresy...) > Not heresy, there is lots of good software that is not in Bioconductor, but I'm not entirely sure why you want to ignore the stuff that is in it - there are several options there, including simple basic built in R functions, limma and hopefully some new offerings in the next few weeks. It is good to look around at what is available, but one shouldn't miss what is under one's nose either. Robert > Mick > > -----Original Message----- > From: Luke Whitaker [mailto:luke@inpharmatica.co.uk] > Sent: 10 September 2003 10:26 > To: bioconductor@stat.math.ethz.ch > Subject: [BioC] How to get started with bioconductor ? > > > > Hello, > > I need to do some straightforward analysis on two-dye microarray > data. I want to be able to estimate fold-regulation for each gene > between two conditions (eg treated/untreated etc). > > The first chips I had to analyse had 200 genes and I "rolled > my own" analysis using lm() etc. which seemed to work OK, but I > now have chips with aprox 1,700 genes and the method I was using > (essentially ANOVA with one level of explanatory factor per gene) > now runs out of memory. > > I would like to use Bioconductor, but looking at the documentation, > I cannot see the forest for the trees. I have had a look at limma, > and think it may do what I want, but it seems to use quite a > sophisticated bayesian analysis which I do not completely understand, > and I would prefer to start at least with something fairly simple. As > usual, I have much less time than I would like to do this. > > Is there one basic bioconductor function for estimating fold > regulation in a two dye experiment ? > > Thanks, > > Luke Whitaker > Inpharmatica > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor -- +--------------------------------------------------------------------- ------+ | Robert Gentleman phone : (617) 632-5250 | | Associate Professor fax: (617) 632-2444 | | Department of Biostatistics office: M1B20 | | Harvard School of Public Health email: rgentlem@jimmy.harvard.edu | +--------------------------------------------------------------------- ------+
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Hi all, I'm using R and ARB both for a while right now. I'm programming some functions to do phylogenetic microarray analysis. As far as I know, there are no packages for (microarray) probe design in BioConductor nor for phylogenetic microarray analysis. I just wondered if anyone feels like helping me making ARB more accessible from R, e.g. for the reading the phylogeny (without exporting data), or even better, using the PT_SERVER from R. This would make it possible to use ARB from an R interface, and even better, from a web interface, doing all analysis. This would be of great help for our lab, for internal use, but I'm sure many other would benefit from this possibility to do almost 'everything' (from microarray probe design up to microarray analysis) using R. It would be a great step to have one large system for a complete (phylogenetic) microarray design and analysis. So, are there people out here who are willingly to help me out with this? tnx, Kurt.
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@gordon-smyth
Last seen 1 hour ago
WEHI, Melbourne, Australia
At 07:25 PM 10/09/2003, Luke Whitaker wrote: >Hello, > >I need to do some straightforward analysis on two-dye microarray >data. I want to be able to estimate fold-regulation for each gene >between two conditions (eg treated/untreated etc). > >The first chips I had to analyse had 200 genes and I "rolled >my own" analysis using lm() etc. which seemed to work OK, but I >now have chips with aprox 1,700 genes and the method I was using >(essentially ANOVA with one level of explanatory factor per gene) >now runs out of memory. > >I would like to use Bioconductor, but looking at the documentation, >I cannot see the forest for the trees. I have had a look at limma, >and think it may do what I want, but it seems to use quite a >sophisticated bayesian analysis which I do not completely understand, >and I would prefer to start at least with something fairly simple. As >usual, I have much less time than I would like to do this. > >Is there one basic bioconductor function for estimating fold >regulation in a two dye experiment ? Well, I would have thought that limma is the natural package for you to use. When you fit a model in limma, using any of the linear model functions lmFit, lm.series. rlm.series or gls.series, you get a fit object. The estimated log-fold changes are in the component fit$coefficients. Limma doesn't calculate ordinary t-statistics for you, because these are demonstrably bad. But if you want them you can get them from ordinary.t <- fit$coef / fit$stdev / fit$sigma The corresponding degrees of freedom are in fit$df. I am not quite clear what else it might be that you would like limma to provide that it doesn't. If you can explain further we would be interested to hear and possibly respond. It doesn't quite make sense to me to be asking for a package which is *less* capable. Since you are capable of rolling your own analysis, I suspect that ease of use is not the problem. Regards Gordon >Thanks, > >Luke Whitaker >Inpharmatica > >_______________________________________________ >Bioconductor mailing list >Bioconductor@stat.math.ethz.ch >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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