[BioC] Package on clinical data analysis
vilanew at gmail.com
Tue Jan 19 16:54:27 CET 2010
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).
>> -----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
>> 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 ?
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