version 1.0.2

CHANGES

@@ -1,4 +1,18 @@
 
+                   Release History of "st" Package
+               ========================================
+
+
+		CHANGES IN `st' PACKAGE VERSION 1.0.2
+
+
+- some corrections and extensions have been made in the documentation,
+  in particular, how to compute q-values and local FDR values
+- shrinkt() now returns a proper vector (one for which is.vector() is TRUE).
+- the license was changed from "GNU GPL 2 or later" to "GNU GPL 3 or later".
+
+
+
 		CHANGES IN `st' PACKAGE VERSION 1.0.1
 
 - reference to Opgen-Rhein and Strimmer (2007) updated.

DESCRIPTION

@@ -1,15 +1,15 @@
 Package: st
-Version: 1.0.1
-Date: 2007-02-28
+Version: 1.0.2
+Date: 2007-10-21
 Title: Shrinkage t Statistic
 Author: Rainer Opgen-Rhein and Korbinian Strimmer.
 Maintainer: Korbinian Strimmer <strimmer@uni-leipzig.de>
-Depends: R (>= 2.2.1), corpcor (>= 1.4.4)
+Depends: R (>= 2.2.1), corpcor (>= 1.4.7), fdrtool (>= 1.2.0)
 Suggests: limma, samr
 Description: This package implements the "shrinkage t" statistic 
    described in Opgen-Rhein and Strimmer (2007).  It also offers
    a convenient interface to a number of other regularized t-type 
    statistics often used in high-dimensional case-control studies.    
-License: GPL version 2 or newer
+License: GPL (>= 3)
 URL: http://www.strimmerlab.org/software/st/
-Packaged: Wed Feb 28 00:01:13 2007; ksold
+Packaged: Sun Oct 21 15:42:04 2007; strimmer

R/shrink.R → R/shrinkt.R

@@ -1,4 +1,4 @@
-### shrinkt.R  (2006-08-30)
+### shrinkt.R  (2006-10-21)
 ###
 ###    Shrinkage t Statistic
 ###
@@ -58,7 +58,7 @@ shrinkt.fun <- function (L, var.equal=TRUE, verbose=TRUE)
         xc1 = sweep(X[L==1,], 2, tmp$mu1)
         xc2 = sweep(X[L==2,], 2, tmp$mu2)
 
-        v <- var.shrink(rbind(xc1, xc2), verbose=verbose)*(n-1)/(n-2)
+        v <- as.vector( var.shrink(rbind(xc1, xc2), verbose=verbose)*(n-1)/(n-2) )
 
         # standard error of diff    
         sd = sqrt( (1/n1 + 1/n2)*v )
@@ -67,8 +67,8 @@ shrinkt.fun <- function (L, var.equal=TRUE, verbose=TRUE)
       {
         X1 = X[L==1,]
         X2 = X[L==2,]
-        v1 = var.shrink(X1, verbose=verbose)
-        v2 = var.shrink(X2, verbose=verbose)
+        v1 = as.vector(var.shrink(X1, verbose=verbose))
+        v2 = as.vector(var.shrink(X2, verbose=verbose))
 
         # standard error of diff 
         sd = sqrt( v1/n1 + v2/n2 )

man/regularizedt.Rd

@@ -62,7 +62,7 @@ by B. Wu.
 Note that this requires the additional installation of the ``limma'' package.
 
 All the above statistics are compared relative to each other 
-(and relative to the shrinkage t statistic) in Opgen-Rhein and Strimmer (2006).
+and relative to the shrinkage t statistic in Opgen-Rhein and Strimmer (2007).
 }
 \value{
   The *.stat functions directly return the respective statistic for each variable.
@@ -72,13 +72,11 @@ All the above statistics are compared relative to each other
 }
 
 \references{
-
- Opgen-Rhein, R., and K. Strimmer. 2006. Accurate ranking of 
+ Opgen-Rhein, R., and K. Strimmer. 2007. Accurate ranking of 
  differentially expressed genes by a distribution-free shrinkage 
  approach.  
- 
- A preprint is available at 
- \url{http://strimmerlab.org/publications/shrinkt2006.pdf}.
+ Statist. Appl. Genet. Mol. Biol. \bold{6}:9.
+ (\url{http://www.bepress.com/sagmb/vol6/iss1/art9/})  
 }
 \author{
   Rainer Opgen-Rhein (\url{http://opgen-rhein.de})
@@ -98,11 +96,22 @@ dim(X) # 6 11475
 L <- choe2.L
 L
 
+
 # student t statistic
 score = studentt.stat(X, L)
 order(abs(score), decreasing=TRUE)[1:10]
 # [1] 11068   724  9990 11387 11310  9985  9996 11046    43    50
 
+# compute q-values and local false discovery rates
+# note the procedure automatically estimates the degree of freedom 
+# so any statistic following a t distribution may be supplied
+library("fdrtool")
+fdr.out = fdrtool(score, statistic="studentt") 
+sum( fdr.out$qval < 0.05 )
+sum( fdr.out$lfdr < 0.2 )
+fdr.out$param
+
+
 # difference of means /fold change statistic
 score = diffmean.stat(X, L)
 order(abs(score), decreasing=TRUE)[1:10]

man/shrinkt.stat.Rd

@@ -83,5 +83,16 @@ order(abs(score), decreasing=TRUE)[1:10]
 # [1] 11068    50 10979   724    43  1022  5762 10936  9939  9769
 #  lambda.var (variance vector):  0.3673   0.3362
 
+
+# compute q-values and local false discovery rates
+# note the procedure automatically estimates the degree of freedom 
+# so any statistic following a t distribution may be supplied
+library("fdrtool")
+fdr.out = fdrtool(score, statistic="studentt") 
+sum( fdr.out$qval < 0.05 )
+sum( fdr.out$lfdr < 0.2 )
+fdr.out$param
+
+ 
 }
 \keyword{univar}