[BioC] about running gsva on mac
Dan Tenenbaum
dtenenba at fhcrc.org
Fri Aug 2 00:24:52 CEST 2013
On Thu, Aug 1, 2013 at 3:10 PM, Ed <edforum at gmail.com> 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
>>
>
I can't reproduce this on a Mac with similar sessionInfo. The
differences in sessionInfo() suggest things to try:
update the XML package:
library(BiocInstaller)
biocLite("XML")
Locale is also different so that would be another thing to explore if
these don't work.
Also, you have packages loaded that I do not have loaded. So try
starting R as follows:
R --vanilla
Here is my sessionInfo():
> sessionInfo()
R version 3.0.1 (2013-05-16)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] limma_3.16.7 GSVA_1.8.0 GSEABase_1.22.0
[4] graph_1.38.3 annotate_1.38.0 AnnotationDbi_1.22.6
[7] Biobase_2.20.1 BiocGenerics_0.6.0
loaded via a namespace (and not attached):
[1] DBI_0.2-7 IRanges_1.18.2 RSQLite_0.11.4 XML_3.98-1.1 stats4_3.0.1
[6] tools_3.0.1 xtable_1.7-1
Dan
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>
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