hi again,
thanks for your patience, the problem below has been fixed in GSVA
release and development versions 1.10.2 and 1.11.3, respectively. You
can specifically update GSVA from R with the following two instructions:
library(BiocInstaller)
update.packages(oldPkgs="GSVA", repos=biocinstallRepos(), ask=FALSE)
note that when passing a LumiBatch object as input the output is going
to be an ExpressionSet object because the resulting pathway-level
summaries of expression have no distinctive features of the illumina
platform. The phenotypic data in the LumiBatch object, however, will
continue to be part of the resulting object.
cheers,
robert.
On 12/30/2013 10:11 PM, Markus Riester wrote:
Hi Justin,
GSVA does not work correctly with LumiBatch objects. It does all the
calculations, but then returns the original input data object, not
the pathway collapsed version of the input data.
library(lumi) library(GSVA) library(GSVAdata)
library(lumiHumanAll.db)
data(example.lumi) data(c2BroadSets)
res.eset<- gsva(example.lumi, c2BroadSets)$es.obs
res.matrix<- gsva(exprs(example.lumi), c2BroadSets,
annotation=annotation(example.lumi))$es.obs
dim(res.eset)
Features Samples 8000 4
dim(res.matrix)
[1] 2986 4
sessionInfo()
R version 3.0.2 (2013-09-25) 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 [8] base
other attached packages: [1] lumiHumanAll.db_1.22.0 GSVAdata_0.99.11
hgu95a.db_2.10.1 [4] org.Hs.eg.db_2.10.1 RSQLite_0.11.4
DBI_0.2-7 [7] GSVA_1.10.1 GSEABase_1.24.0
graph_1.40.1 [10] annotate_1.40.0 AnnotationDbi_1.24.0
lumi_2.14.1 [13] Biobase_2.22.0 BiocGenerics_0.8.0
knitr_1.5
loaded via a namespace (and not attached): [1] affy_1.40.0
affyio_1.30.0 base64_1.1 [4] beanplot_1.1
BiocInstaller_1.12.0 biomaRt_2.18.0 [7] Biostrings_2.30.1
bitops_1.0-6 BSgenome_1.30.0 [10] bumphunter_1.2.0
codetools_0.2-8 colorspace_1.2-4 [13] digest_0.6.4
doRNG_1.5.5 evaluate_0.5.1 [16] foreach_1.4.1
formatR_0.10 genefilter_1.44.0 [19] GenomicFeatures_1.14.2
GenomicRanges_1.14.4 grid_3.0.2 [22] illuminaio_0.4.0
IRanges_1.20.6 iterators_1.0.6 [25] itertools_0.1-1
KernSmooth_2.23-10 lattice_0.20-24 [28] limma_3.18.7
locfit_1.5-9.1 MASS_7.3-29 [31] Matrix_1.1-0
matrixStats_0.8.12 mclust_4.2 [34] methylumi_2.8.0
mgcv_1.7-27 minfi_1.8.9 [37] multtest_2.18.0
nleqslv_2.1 nlme_3.1-113 [40] nor1mix_1.1-4
pkgmaker_0.17.4 preprocessCore_1.24.0 [43] R.methodsS3_1.5.2
RColorBrewer_1.0-5 RCurl_1.95-4.1 [46] registry_0.2
reshape_0.8.4 rngtools_1.2.3 [49] Rsamtools_1.14.2
rtracklayer_1.22.0 siggenes_1.36.0 [52] splines_3.0.2
stats4_3.0.2 stringr_0.6.2 [55] survival_2.37-4
tools_3.0.2 XML_3.95-0.2 [58] xtable_1.7-1
XVector_0.2.0 zlibbioc_1.8.0
Cheers, Markus
-- DFCI Biostatistics& Computational Biology Office Location: Center
for Life Science Building, Room 11052
Phone: +1-617-582-7586
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Universitat Pompeu Fabra (UPF)
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