[BioC] about running gsva on mac

[Devon Ryan]

Are you running this in R.app or R from the terminal? If the former, try running things from the terminal and see if the problem persists. Some parallel computing related packages (e.g. doMC) will give this error in a GUI.

Devon

____________________________________________
Devon Ryan, Ph.D.
Email: dpryan at dpryan.com
Molecular and Cellular Cognition Lab
German Centre for Neurodegenerative Diseases (DZNE)
Ludwig-Erhard-Allee 2
53175 Bonn, Germany

On Aug 2, 2013, at 12:10 AM, Ed wrote:

> 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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