Hi there,

I used the examples in ?gsva and got the following errors on my mac.
However, I run it also on the linux and it worked.

Please suggest.

Thanks,

Weiwei

> library(limma)
>
> p <- 10 ## number of genes
> n <- 30 ## number of samples
> nGrp1 <- 15 ## number of samples in group 1
> nGrp2 <- n - nGrp1 ## number of samples in group 2
>
> ## consider three disjoint gene sets
> geneSets <- list(set1=paste("g", 1:3, sep=""),
+                  set2=paste("g", 4:6, sep=""),
+                  set3=paste("g", 7:10, sep=""))
>
> ## sample data from a normal distribution with mean 0 and st.dev. 1
> y <- matrix(rnorm(n*p), nrow=p, ncol=n,
+             dimnames=list(paste("g", 1:p, sep="") , paste("s", 1:n,
sep="")))
>
> ## genes in set1 are expressed at higher levels in the last 10 samples
> y[geneSets$set1, (nGrp1+1):n] <- y[geneSets$set1, (nGrp1+1):n] + 2
>
> ## build design matrix
> design <- cbind(sampleGroup1=1, sampleGroup2vs1=c(rep(0, nGrp1), rep(1,
nGrp2)))
>
> ## fit linear model
> fit <- lmFit(y, design)
>
> ## estimate moderated t-statistics
> fit <- eBayes(fit)
>
> ## genes in set1 are differentially expressed
> topTable(fit, coef="sampleGroup2vs1")
    ID       logFC           t      P.Value    adj.P.Val         B
2   g2  2.43865785  6.79741169 1.490585e-09 1.490585e-08 11.467181
1   g1  1.81349993  5.04733755 2.590932e-06 1.295466e-05  4.218446
3   g3  1.68971708  4.54930258 1.812937e-05 6.043122e-05  2.348424
5   g5  0.25263973  0.65201092 5.161890e-01 9.308575e-01 -6.688660
10 g10  0.16766254  0.49082930 6.248376e-01 9.308575e-01 -6.780571
9   g9  0.13478444  0.40143265 6.891295e-01 9.308575e-01 -6.820434
8   g8 -0.12067327 -0.32614302 7.451340e-01 9.308575e-01 -6.847833
7   g7 -0.08002351 -0.23401984 8.155437e-01 9.308575e-01 -6.873660
4   g4  0.07875803  0.20538583 8.377717e-01 9.308575e-01 -6.879960
6   g6 -0.03196719 -0.08251146 9.344379e-01 9.344379e-01 -6.897676
>
> ## estimate GSVA enrichment scores for the three sets
> gsva_es <- gsva(y, geneSets, mx.diff=1)$es.obs
  |
              |   0%The process has forked and you cannot use this
CoreFoundation functionality safely. You MUST exec().
Break on
__THE_PROCESS_HAS_FORKED_AND_YOU_CANNOT_USE_THIS_COREFOUNDATION_FUNCTIONALITY___YOU_MUST_EXEC__()
to debug.
The process has forked and you can



> version
               _
platform       x86_64-apple-darwin10.8.0
arch           x86_64
os             darwin10.8.0
system         x86_64, darwin10.8.0
status
major          3
minor          0.1
year           2013
month          05
day            16
svn rev        62743
language       R
version.string R version 3.0.1 (2013-05-16)
nickname       Good Sport
> sessionInfo()
R version 3.0.1 (2013-05-16)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods
base

other attached packages:
[1] limma_3.16.7         GSVA_1.8.0           GSEABase_1.22.0
 graph_1.38.3
[5] annotate_1.38.0      AnnotationDbi_1.22.6 Biobase_2.20.1
BiocGenerics_0.6.0
[9] BiocInstaller_1.10.3

loaded via a namespace (and not attached):
 [1] DBI_0.2-7       grid_3.0.1      IRanges_1.18.2  lattice_0.20-15
Matrix_1.0-12
 [6] RSQLite_0.11.4  stats4_3.0.1    tools_3.0.1     XML_3.95-0.2
 xtable_1.7-1
>

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