Package on clinical data analysis
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David ▴ 860
@david-3335
Last seen 6.1 years ago
Hi, I would like to know if there is a package to analyse gene expression and correlate with a clinical variable ? Limma does all sort of gene expression analysis but is there any package to correlate that with clinical variables ? thanks, david
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@vincent-j-carey-jr-4
Last seen 6 weeks ago
United States
You need to scroll to the bottom of the first page at Bioconductor.org -- there are pictures of books at the bottom and you can click on the images of the Springer volumes to find out about the books that address the topic of your question in great detail. In the ALL experimental data package there is a very terse vignette that shows how an ExpressionSet unites expression and clinical information, and shows how to build a simple tree structured classifier relating expression to leukemia type. The books have numerous chapters devoted to your concern. On Fri, Jan 15, 2010 at 5:47 AM, David martin <vilanew at="" gmail.com=""> wrote: > Hi, > I would like to know if there is a package to analyse gene expression and > correlate with a clinical variable ? > > Limma does all sort of gene expression analysis but is there any package to > correlate that with clinical variables ? > > thanks, > david > > _______________________________________________ > 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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Claus Mayer ▴ 340
@claus-mayer-1179
Last seen 9.6 years ago
European Union
Hi David! I haven't had many data sets like that but as far as I can see limma is not only capable of comparing groups but you can also have continuous measurements as explanatory variables, i.e. fit a multiple regression type of model by defining the design as Design<- model.matrix(~ var1 + var2 +..+ varn), where var1-varn are n clinical variables. The question is, whether that is the type of analysis you have in mind. You say "correlate" in your e-mail. Correlation treats gene expression and clinical variable as equal, whereas in regression you choose one of them as explanatory the other one as response. The model above has gene expression as response (separately for each gene). It is very well possible though that you rather want to explain the clinical variables by the gene expression profile, i.e reverse the roles. Limma wouldn't be the right tool for that. Or perhaps one of your variables is survival time and you want to conduct a cox regression type of analsyis... etc.. I think your message contains too little information to direct you to the right tool, but if it is indeed a multiple regression you looking for, you could still use limma (see above). Claus > -----Original Message----- > From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor- > bounces at stat.math.ethz.ch] On Behalf Of David martin > Sent: 15 January 2010 10:47 > To: bioconductor at stat.math.ethz.ch > Subject: [BioC] Package on clinical data analysis > > Hi, > I would like to know if there is a package to analyse gene expression > and correlate with a clinical variable ? > > Limma does all sort of gene expression analysis but is there any package > to correlate that with clinical variables ? > > thanks, > david > > _______________________________________________ > 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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thanks, I'm interested in Cox regression type analysis on one side !!! On 01/15/2010 04:38 PM, Claus Mayer wrote: > Hi David! > > I haven't had many data sets like that but as far as I can see limma is not > only capable of comparing groups but you can also have continuous > measurements as explanatory variables, i.e. fit a multiple regression type > of model by defining the design as > > Design<- model.matrix(~ var1 + var2 +..+ varn), > > where var1-varn are n clinical variables. The question is, whether that is > the type of analysis you have in mind. You say "correlate" in your e-mail. > Correlation treats gene expression and clinical variable as equal, whereas > in regression you choose one of them as explanatory the other one as > response. The model above has gene expression as response (separately for > each gene). It is very well possible though that you rather want to explain > the clinical variables by the gene expression profile, i.e reverse the > roles. Limma wouldn't be the right tool for that. Or perhaps one of your > variables is survival time and you want to conduct a cox regression type of > analsyis... etc.. > > I think your message contains too little information to direct you to the > right tool, but if it is indeed a multiple regression you looking for, you > could still use limma (see above). > > Claus > >> -----Original Message----- >> From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor- >> bounces at stat.math.ethz.ch] On Behalf Of David martin >> Sent: 15 January 2010 10:47 >> To: bioconductor at stat.math.ethz.ch >> Subject: [BioC] Package on clinical data analysis >> >> Hi, >> I would like to know if there is a package to analyse gene expression >> and correlate with a clinical variable ? >> >> Limma does all sort of gene expression analysis but is there any package >> to correlate that with clinical variables ? >> >> thanks, >> david >> >> _______________________________________________ >> 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 > > _______________________________________________ > 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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