[BioC] SAM for R

[Cappola, Thomas]

Thanks for your replies.  If the code is reposted, please let us know!
Tom

Thomas Cappola, M.D.
Assistant Professor of Medicine
Heart Failure and Transplantation
University of Pennsylvania School of Medicine
6 Penn Tower
3400 Spruce Street
Philadelphia, PA 19104
Tel 215-615-0805  Fax 215-615-0828
thomas.cappola at uphs.upenn.edu 



-----Original Message-----
From: James MacDonald [mailto:jmacdon at med.umich.edu] 
Sent: Wednesday, June 04, 2003 7:23 AM
To: stephen at inf.ed.ac.uk; thomas.cappola at uphs.upenn.edu
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] SAM for R


You will not be able to download the scripts from that page any longer.
Holger took them down after being counseled that he may be in legal trouble
given that there are patents pending on the SAM algorithms. 

My understanding is that he contacted Rob Tibshirani for permission to post
the scripts but has not received an answer.

Jim



James W. MacDonald
UMCCC Microarray Core Facility
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623

>>> Stephen Eglen <stephen at inf.ed.ac.uk> 06/04/03 05:41AM >>>

 > I have been using the affy package to summarize and filter .cel files
into  > expression sets, then exporting these sets into SAM (Significance
Analysis  > of Microarrays) to select differentially expressed genes.  
 > This is getting cumbersome; it would be more straightforward to do  >
everything in R.  > Does anyone have functions for SAM in R, or can I use
any of the existing  > bioconductor packages to select differentially
expressed genes in a way  > similar to SAM?


hi Thomas, and others,
See the announcement below by Holger Schwender -- the R code works fine.

Stephen
----------------------------------------------------------------------
 because of the large number of requests I uploaded my functions  that can
perform the SAM analysis and the Empirical Bayes Analysis  described in the
JASA-Paper of Efron to the internet. You can  download the S-Plus functions
from
  
 http://de.geocities.com/holgerschw/GENE-SIG.ZIP 
  
 A short description you will find under
  
 http://de.geocities.com/holgerschw/gene-sig.pdf 
  
 An older version of the R functions is available at
  
 http://de.geocities.com/holgerschw/r.zip 
  
 These R functions cannot handle a very large number of permutations  (let's
say B larger than 500 or 1000). There is a newer version of  these functions
that can handle this number of permutations. I will  post these functions as
soon as I am back home (Sunday or Monday).

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