[BioC] GSVA questions
Joe [guest]
guest at bioconductor.org
Fri Sep 6 07:46:56 CEST 2013
Dear Markus,
I do it as you said, âc2BroadSetsâsource from package, and "C5allBraodSets" is load from GMT file that download from broadinstitute.
as:
> c2BroadSets
GeneSetCollection
names: NAKAMURA_CANCER_MICROENVIRONMENT_UP, NAKAMURA_CANCER_MICROENVIRONMENT_DN, ..., ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY (3272 total)
unique identifiers: 5167, 100288400, ..., 57191 (29340 total)
types in collection:
geneIdType: EntrezIdentifier (1 total)
collectionType: BroadCollection (1 total)
> C5allBroadSets
GeneSetCollection
names: NUCLEOPLASM, EXTRINSIC_TO_PLASMA_MEMBRANE, ..., INOSITOL_OR_PHOSPHATIDYLINOSITOL_KINASE_ACTIVITY (1454 total)
unique identifiers: HNRPK, XRCC6, ..., PGM1 (8299 total)
types in collection:
geneIdType: NullIdentifier (1 total)
collectionType: NullCollection (1 total)
when I use "c2BroadSets" GeneSetCollection, it works, and "NSCLC_norm_GSE32474_rma_Filter" is ExpressionSet, Because of customized CDF, unique gene ID used in the file, so I adjust the min.sz to 1
>NSCLC_gsva_c2 <- gsva(NSCLC_norm_GSE32474_rma_Filter, c2BroadSets,min.sz=1, max.sz=500, verbose=TRUE)$es.obs
when I use "C5allBroadSets", report error, as
>NSCLC_gsva_c5 <- gsva(NSCLC_norm_GSE32474_rma_Filter, C5allBroadSets,min.sz=1, max.sz=500, verbose=TRUE)$es.obs
Mapping identifiers between gene sets and feature names
Error in GSVA:::.gsva(Biobase::exprs(expr), mapped.gset.idx.list, method, :
The gene set list is empty! Filter may be too stringent.
SO, how could I set parameters and make gsva work.................
Thanks,
Joe
-- output of sessionInfo():
R version 3.0.1 (2013-05-16)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=Chinese (Simplified)_People's Republic of China.936
[2] LC_CTYPE=Chinese (Simplified)_People's Republic of China.936
[3] LC_MONETARY=Chinese (Simplified)_People's Republic of China.936
[4] LC_NUMERIC=C
[5] LC_TIME=Chinese (Simplified)_People's Republic of China.936
attached base packages:
[1] splines grid parallel stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] GSVA_1.8.0 GSVAdata_0.99.10
[3] hgu95a.db_2.9.0 hgu133plus2hsentrezgprobe_17.1.0
[5] hgu133plus2hsentrezgcdf_17.1.0 hgu133plus2hsentrezg.db_17.1.0
[7] hgu95av2.db_2.9.0 a4Classif_1.8.0
[9] varSelRF_0.7-3 randomForest_4.6-7
[11] pamr_1.54.1 survival_2.37-4
[13] ROCR_1.0-5 gplots_2.11.3
[15] KernSmooth_2.23-10 caTools_1.14
[17] gdata_2.13.2 gtools_3.0.0
[19] MLInterfaces_1.40.0 sfsmisc_1.0-24
[21] cluster_1.14.4 rda_1.0.2-2
[23] rpart_4.1-3 MASS_7.3-29
[25] a4Preproc_1.8.0 a4Core_1.8.0
[27] glmnet_1.9-5 Matrix_1.0-12
[29] lattice_0.20-23 GSEABase_1.22.0
[31] affy_1.38.1 GOstats_2.26.0
[33] graph_1.38.3 Category_2.26.0
[35] VennDiagram_1.6.5 pheatmap_0.7.6
[37] statmod_1.4.17 limma_3.16.7
[39] biomaRt_2.16.0 annotate_1.38.0
[41] genefilter_1.42.0 primeviewhsentrezgprobe_17.1.0
[43] primeviewhsentrezg.db_17.1.0 org.Hs.eg.db_2.9.0
[45] RSQLite_0.11.4 DBI_0.2-7
[47] primeviewhsentrezgcdf_17.1.0 AnnotationDbi_1.22.6
[49] Biobase_2.20.1 BiocGenerics_0.6.0
[51] rj_1.1.3-1
loaded via a namespace (and not attached):
[1] affyio_1.28.0 AnnotationForge_1.2.2 BiocInstaller_1.10.3
[4] bitops_1.0-6 GO.db_2.9.0 IRanges_1.18.3
[7] mboost_2.2-2 preprocessCore_1.22.0 RBGL_1.36.2
[10] RCurl_1.95-4.1 rj.gd_1.1.3-1 stats4_3.0.1
[13] tools_3.0.1 XML_3.98-1.1 xtable_1.7-1
[16] zlibbioc_1.6.0
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