R : Copyright 2005, The R Foundation for Statistical Computing
Version 2.1.1  (2005-06-20), ISBN 3-900051-07-0

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> ### * <HEADER>
> ###
> attach(NULL, name = "CheckExEnv")
> assign(".CheckExEnv", as.environment(2), pos = length(search())) # base
> ## add some hooks to label plot pages for base and grid graphics
> setHook("plot.new", ".newplot.hook")
> setHook("persp", ".newplot.hook")
> setHook("grid.newpage", ".gridplot.hook")
> 
> assign("cleanEx",
+        function(env = .GlobalEnv) {
+ 	   rm(list = ls(envir = env, all.names = TRUE), envir = env)
+            RNGkind("default", "default")
+ 	   set.seed(1)
+    	   options(warn = 1)
+ 	   delayedAssign("T", stop("T used instead of TRUE"),
+ 		  assign.env = .CheckExEnv)
+ 	   delayedAssign("F", stop("F used instead of FALSE"),
+ 		  assign.env = .CheckExEnv)
+ 	   sch <- search()
+ 	   newitems <- sch[! sch %in% .oldSearch]
+ 	   for(item in rev(newitems))
+                eval(substitute(detach(item), list(item=item)))
+ 	   missitems <- .oldSearch[! .oldSearch %in% sch]
+ 	   if(length(missitems))
+ 	       warning("items ", paste(missitems, collapse=", "),
+ 		       " have been removed from the search path")
+        },
+        env = .CheckExEnv)
> assign("..nameEx", "__{must remake R-ex/*.R}__", env = .CheckExEnv) # for now
> assign("ptime", proc.time(), env = .CheckExEnv)
> grDevices::postscript("permax-Examples.ps")
> assign("par.postscript", graphics::par(no.readonly = TRUE), env = .CheckExEnv)
> options(contrasts = c(unordered = "contr.treatment", ordered = "contr.poly"))
> options(warn = 1)    
> library('permax')
> 
> assign(".oldSearch", search(), env = .CheckExEnv)
> assign(".oldNS", loadedNamespaces(), env = .CheckExEnv)
> cleanEx(); ..nameEx <- "permax"
> 
> ### * permax
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: permax
> ### Title: 2-sample permutation t-tests for high dimensional data
> ### Aliases: permax
> ### Keywords: htest
> 
> ### ** Examples
> 
> #generate make believe data
>    set.seed(1292)
>    ngenes <- 1000
>    m1 <- rnorm(ngenes,4,1)
>    m2 <- rnorm(ngenes,4,1)
>     exp1 <- cbind(matrix(exp(rnorm(ngenes*5,m1,1)),nrow=ngenes),
+                matrix(exp(rnorm(ngenes*10,m2,1)),nrow=ngenes))
>    exp1[exp1<20] <- 20
>    sub <- exp1>20 & exp1<150
>    exp1[sub] <- ifelse(runif(length(sub[sub]))<.5,20,exp1[sub])
>    dimnames(exp1) <- list(paste('x',format(1:ngenes,justify='l'),sep=''),
+                      paste('sample',format(1:ncol(exp1),justify='l'),sep=''))
>    dimnames(exp1) <- list(paste('x',1:ngenes,sep=''),
+                      paste('sample',1:ncol(exp1),sep=''))
>    exp1 <- round(exp1)
> 
>    uu <- permax(exp1,1:5)
statistics will be computed for all 3003 groupings
>   summary(uu,nl=5,nr=5) # 5 most extreme in each direction
        stat  p.lower    m1    m2     s1     s2 np1 np2   mdiff     mrat
x105 -13.928 0.000333 3.102 6.671 0.2373 0.5395   1  10  -766.6 0.028193
x455 -11.646 0.000333 3.191 7.696 0.4358 0.7976   1  10 -2175.2 0.011050
x585 -10.648 0.000666 2.996 8.396 0.0000 1.1129   0  10 -4410.2 0.004515
x104 -10.629 0.000666 2.996 5.462 0.0000 0.5091   0  10  -215.5 0.084909
x734  -8.328 0.003663 3.228 6.616 0.5202 0.8225   1  10  -721.9 0.033779
      stat  p.upper    m1    m2     s1      s2 np1 np2 mdiff   mrat
x225 19.17 0.001332 5.131 3.046 0.3017 0.12841   5   2 148.1  8.042
x460 17.28 0.001998 6.467 3.075 0.5267 0.24933   5   1 621.6 29.725
x25  14.37 0.002331 6.210 3.014 0.7269 0.05766   5   1 477.3 24.432
x668 13.54 0.003330 6.493 3.049 0.7984 0.16780   5   1 639.3 31.315
x217 12.88 0.004329 5.956 3.092 0.6395 0.23738   5   2 363.9 17.523
> 
> 
> 
> cleanEx(); ..nameEx <- "permcor"
> 
> ### * permcor
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: permcor
> ### Title: permutation tests for correlations in high dimensional data
> ### Aliases: permcor
> ### Keywords: htest
> 
> ### ** Examples
> 
>    set.seed(1292)
>    ngenes <- 1000
>    m1 <- rnorm(ngenes,4,1)
>    m2 <- rnorm(ngenes,4,1)
>     exp1 <- cbind(matrix(exp(rnorm(ngenes*5,m1,1)),nrow=ngenes),
+                matrix(exp(rnorm(ngenes*10,m2,1)),nrow=ngenes))
>    exp1[exp1<20] <- 20
>    sub <- exp1>20 & exp1<150
>    exp1[sub] <- ifelse(runif(length(sub[sub]))<.5,20,exp1[sub])
>    dimnames(exp1) <- list(paste('x',format(1:ngenes,justify='l'),sep=''),
+                      paste('sample',format(1:ncol(exp1),justify='l'),sep=''))
>    dimnames(exp1) <- list(paste('x',1:ngenes,sep=''),
+                      paste('sample',1:ncol(exp1),sep=''))
>    exp1 <- round(exp1)
> 
> #see the permax help file for the definition of exp1
>   u8 <- permcor(exp1,1:15)
>  summary(u8,nr=4,nl=4)
        stat p.lower np
x246 -0.8792   0.009  9
x487 -0.8461   0.023  9
x54  -0.8256   0.046  7
x362 -0.8109   0.071  6
       stat p.upper np
x930 0.8560   0.017  9
x275 0.8317   0.037  9
x683 0.8300   0.040 10
x104 0.8148   0.073 10
>  u10 <- permcor(exp1[,c(1:3,5:8)],c(1,1,1,0,0,0,0),nperm=0)
statistics will be computed for all 5040 permutationss
> 
>  summary(u10,nl=4,nr=4)
        stat p.lower np
x774 -0.9960 0.05714  4
x498 -0.9686 0.31429  4
x421 -0.9230 0.77143  4
x773 -0.9227 0.77143  5
       stat p.upper np
x247 0.9995 0.02857  3
x110 0.9990 0.05714  3
x165 0.9909 0.37143  4
x101 0.9853 0.45714  3
> 
> 
> 
> 
> cleanEx(); ..nameEx <- "permsep"
> 
> ### * permsep
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: permsep
> ### Title: Permutation analysis for complete separation
> ### Aliases: permsep
> ### Keywords: htest
> 
> ### ** Examples
> 
>    ngenes <- 1000
>    m1 <- rnorm(ngenes,4,1)
>    m2 <- rnorm(ngenes,4,1)
>     exp1 <- cbind(matrix(exp(rnorm(ngenes*5,m1,1)),nrow=ngenes),
+                matrix(exp(rnorm(ngenes*10,m2,1)),nrow=ngenes))
>    exp1[exp1<20] <- 20
>    sub <- exp1>20 & exp1<150
>    exp1[sub] <- ifelse(runif(length(sub[sub]))<.5,20,exp1[sub])
>    dimnames(exp1) <- list(paste('x',format(1:ngenes,justify='l'),sep=''),
+                      paste('sample',format(1:ncol(exp1),justify='l'),sep=''))
>    dimnames(exp1) <- list(paste('x',1:ngenes,sep=''),
+                      paste('sample',1:ncol(exp1),sep=''))
>    exp1 <- round(exp1)
> 
>  uuu <- permsep(exp1,1:5)
statistics will be computed for all 3003 groupings
# comp sep; prop perm with more; ave # per perm; prop perm with any
[1] 4.100000e+01 3.330003e-04 3.523144e-01 2.564103e-01
> 
> 
> 
> 
> cleanEx(); ..nameEx <- "plot.expr"
> 
> ### * plot.expr
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: plot.expr
> ### Title: Color image plot of gene expression levels
> ### Aliases: plot.expr
> ### Keywords: hplot
> 
> ### ** Examples
> 
>    set.seed(1292)
>    ngenes <- 1000
>    m1 <- rnorm(ngenes,4,1)
>    m2 <- rnorm(ngenes,4,1)
>     exp1 <- cbind(matrix(exp(rnorm(ngenes*5,m1,1)),nrow=ngenes),
+                matrix(exp(rnorm(ngenes*10,m2,1)),nrow=ngenes))
>    exp1[exp1<20] <- 20
>    sub <- exp1>20 & exp1<150
>    exp1[sub] <- ifelse(runif(length(sub[sub]))<.5,20,exp1[sub])
>    dimnames(exp1) <- list(paste('x',format(1:ngenes,justify='l'),sep=''),
+                      paste('sample',format(1:ncol(exp1),justify='l'),sep=''))
>    dimnames(exp1) <- list(paste('x',1:ngenes,sep=''),
+                      paste('sample',1:ncol(exp1),sep=''))
>    exp1 <- round(exp1)
> 
>   plot.expr(exp1[1:20,])
> 
> 
> 
> cleanEx(); ..nameEx <- "plot.permax"
> 
> ### * plot.permax
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: plot.permax
> ### Title: Image plot of the most significant genes (attributes) from a
> ###   permax analysis
> ### Aliases: plot.permax
> ### Keywords: hplot
> 
> ### ** Examples
> 
>  set.seed(1292)
>    ngenes <- 1000
>    m1 <- rnorm(ngenes,4,1)
>    m2 <- rnorm(ngenes,4,1)
>     exp1 <- cbind(matrix(exp(rnorm(ngenes*5,m1,1)),nrow=ngenes),
+                matrix(exp(rnorm(ngenes*10,m2,1)),nrow=ngenes))
>    exp1[exp1<20] <- 20
>    sub <- exp1>20 & exp1<150
>    exp1[sub] <- ifelse(runif(length(sub[sub]))<.5,20,exp1[sub])
>    dimnames(exp1) <- list(paste('x',format(1:ngenes,justify='l'),sep=''),
+                      paste('sample',format(1:ncol(exp1),justify='l'),sep=''))
>    dimnames(exp1) <- list(paste('x',1:ngenes,sep=''),
+                      paste('sample',1:ncol(exp1),sep=''))
>    exp1 <- round(exp1)
> 
>   uu <- permax(exp1,1:5)
statistics will be computed for all 3003 groupings
>   plot(uu,exp1,ig1=1:5,cex=.7)
> 
> 
> 
> cleanEx(); ..nameEx <- "rowperm"
> 
> ### * rowperm
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: rowperm
> ### Title: Generates random permutations within rows of a matrix
> ### Aliases: rowperm
> ### Keywords: utilities
> 
> ### ** Examples
> 
>  x <- matrix(1:12,3)
>  x
     [,1] [,2] [,3] [,4]
[1,]    1    4    7   10
[2,]    2    5    8   11
[3,]    3    6    9   12
> #     [,1] [,2] [,3] [,4] 
> #[1,]    1    4    7   10
> #[2,]    2    5    8   11
> #[3,]    3    6    9   12
>   rowperm(x)
     [,1] [,2] [,3] [,4]
[1,]    4    7   10    1
[2,]   11    5    2    8
[3,]   12    9    3    6
> #     [,1] [,2] [,3] [,4] 
> #[1,]   10    7    1    4
> #[2,]    8   11    2    5
> #[3,]    6   12    9    3
> 
> 
> 
> 
> cleanEx(); ..nameEx <- "summary.permax"
> 
> ### * summary.permax
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: summary.permax
> ### Title: Summarizes the output of permax
> ### Aliases: summary.permax print.summary.permax
> ### Keywords: print
> 
> ### ** Examples
> 
> # An example is given in the permax help file
> 
> 
> 
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", env = .CheckExEnv),"\n")
Time elapsed:  1.42 0.12 1.55 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')