metabolomics data analysis
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Dear Users, Do you know any package is designed for metabolomics data? or any package can be used to analyze metabolomics data? I have no experience analyze metabolomics data, it should be quite different from microarray. Thanks, -- output of sessionInfo(): > 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] splines parallel stats graphics grDevices utils datasets methods base other attached packages: [1] WGCNA_1.27-1 doParallel_1.0.3 iterators_1.0.6 foreach_1.4.1 [5] MASS_7.3-27 reshape_0.8.4 plyr_1.8 Hmisc_3.12-2 [9] Formula_1.1-1 survival_2.37-4 flashClust_1.01-2 dynamicTreeCut_1.60 [13] impute_1.34.0 affy_1.38.1 cluster_1.14.4 preprocessCore_1.22.0 [17] BiocInstaller_1.10.3 pd.hugene.2.0.st_3.8.0 oligo_1.24.2 oligoClasses_1.22.0 [21] hugene20sttranscriptcluster.db_2.12.1 org.Hs.eg.db_2.9.0 RSQLite_0.11.4 DBI_0.2-7 [25] AnnotationDbi_1.22.6 Biobase_2.20.1 BiocGenerics_0.6.0 limma_3.16.7 loaded via a namespace (and not attached): [1] affxparser_1.32.3 affyio_1.28.0 Biostrings_2.28.0 bit_1.1-10 codetools_0.2-8 ff_2.2-11 GenomicRanges_1.12.5 [8] grid_3.0.1 IRanges_1.18.3 lattice_0.20-15 rpart_4.1-1 stats4_3.0.1 tools_3.0.1 zlibbioc_1.6.0 -- Sent via the guest posting facility at bioconductor.org.
Metabolomics Metabolomics • 1.1k views
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@james-w-macdonald-5106
Last seen 2 days ago
United States
On Wednesday, September 04, 2013 10:29:33 AM, guest [guest] wrote: > > Dear Users, > > Do you know any package is designed for metabolomics data? or any package can be used to analyze metabolomics data? I have no experience analyze metabolomics data, it should be quite different from microarray. You need to be more clear in what you are asking for. What exactly do you mean by metabolomics data? Is this mass spectrometry data? In addition, what do you mean by analyze? If MS data, I suppose analyze could be peak detection, or it could be statistical analysis of the metabolomics data (e.g., testing for differences in metabolite levels). Best, Jim > > Thanks, > > > -- output of sessionInfo(): > >> 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] splines parallel stats graphics grDevices utils datasets methods base > > other attached packages: > [1] WGCNA_1.27-1 doParallel_1.0.3 iterators_1.0.6 foreach_1.4.1 > [5] MASS_7.3-27 reshape_0.8.4 plyr_1.8 Hmisc_3.12-2 > [9] Formula_1.1-1 survival_2.37-4 flashClust_1.01-2 dynamicTreeCut_1.60 > [13] impute_1.34.0 affy_1.38.1 cluster_1.14.4 preprocessCore_1.22.0 > [17] BiocInstaller_1.10.3 pd.hugene.2.0.st_3.8.0 oligo_1.24.2 oligoClasses_1.22.0 > [21] hugene20sttranscriptcluster.db_2.12.1 org.Hs.eg.db_2.9.0 RSQLite_0.11.4 DBI_0.2-7 > [25] AnnotationDbi_1.22.6 Biobase_2.20.1 BiocGenerics_0.6.0 limma_3.16.7 > > loaded via a namespace (and not attached): > [1] affxparser_1.32.3 affyio_1.28.0 Biostrings_2.28.0 bit_1.1-10 codetools_0.2-8 ff_2.2-11 GenomicRanges_1.12.5 > [8] grid_3.0.1 IRanges_1.18.3 lattice_0.20-15 rpart_4.1-1 stats4_3.0.1 tools_3.0.1 zlibbioc_1.6.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, M.S. Biostatistician University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099
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@james-w-macdonald-5106
Last seen 2 days ago
United States
On Wednesday, September 04, 2013 10:29:33 AM, guest [guest] wrote: > > Dear Users, > > Do you know any package is designed for metabolomics data? or any package can be used to analyze metabolomics data? I have no experience analyze metabolomics data, it should be quite different from microarray. You need to be more clear in what you are asking for. What exactly do you mean by metabolomics data? Is this mass spectrometry data? In addition, what do you mean by analyze? If MS data, I suppose analyze could be peak detection, or it could be statistical analysis of the metabolomics data (e.g., testing for differences in metabolite levels). Best, Jim > > Thanks, > > > -- output of sessionInfo(): > >> 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] splines parallel stats graphics grDevices utils datasets methods base > > other attached packages: > [1] WGCNA_1.27-1 doParallel_1.0.3 iterators_1.0.6 foreach_1.4.1 > [5] MASS_7.3-27 reshape_0.8.4 plyr_1.8 Hmisc_3.12-2 > [9] Formula_1.1-1 survival_2.37-4 flashClust_1.01-2 dynamicTreeCut_1.60 > [13] impute_1.34.0 affy_1.38.1 cluster_1.14.4 preprocessCore_1.22.0 > [17] BiocInstaller_1.10.3 pd.hugene.2.0.st_3.8.0 oligo_1.24.2 oligoClasses_1.22.0 > [21] hugene20sttranscriptcluster.db_2.12.1 org.Hs.eg.db_2.9.0 RSQLite_0.11.4 DBI_0.2-7 > [25] AnnotationDbi_1.22.6 Biobase_2.20.1 BiocGenerics_0.6.0 limma_3.16.7 > > loaded via a namespace (and not attached): > [1] affxparser_1.32.3 affyio_1.28.0 Biostrings_2.28.0 bit_1.1-10 codetools_0.2-8 ff_2.2-11 GenomicRanges_1.12.5 > [8] grid_3.0.1 IRanges_1.18.3 lattice_0.20-15 rpart_4.1-1 stats4_3.0.1 tools_3.0.1 zlibbioc_1.6.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, M.S. Biostatistician University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099
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@laurent-gatto-5645
Last seen 4 days ago
Belgium
A good start might be to have a look at the metabolomics biocView: http://bioconductor.org/packages/release/BiocViews.html#___Metabolomic s Best wishes, Laurent On 4 September 2013 15:29, guest [guest] <guest at="" bioconductor.org=""> wrote: > > Dear Users, > > Do you know any package is designed for metabolomics data? or any package can be used to analyze metabolomics data? I have no experience analyze metabolomics data, it should be quite different from microarray. > > Thanks, > > > -- output of sessionInfo(): > >> 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] splines parallel stats graphics grDevices utils datasets methods base > > other attached packages: > [1] WGCNA_1.27-1 doParallel_1.0.3 iterators_1.0.6 foreach_1.4.1 > [5] MASS_7.3-27 reshape_0.8.4 plyr_1.8 Hmisc_3.12-2 > [9] Formula_1.1-1 survival_2.37-4 flashClust_1.01-2 dynamicTreeCut_1.60 > [13] impute_1.34.0 affy_1.38.1 cluster_1.14.4 preprocessCore_1.22.0 > [17] BiocInstaller_1.10.3 pd.hugene.2.0.st_3.8.0 oligo_1.24.2 oligoClasses_1.22.0 > [21] hugene20sttranscriptcluster.db_2.12.1 org.Hs.eg.db_2.9.0 RSQLite_0.11.4 DBI_0.2-7 > [25] AnnotationDbi_1.22.6 Biobase_2.20.1 BiocGenerics_0.6.0 limma_3.16.7 > > loaded via a namespace (and not attached): > [1] affxparser_1.32.3 affyio_1.28.0 Biostrings_2.28.0 bit_1.1-10 codetools_0.2-8 ff_2.2-11 GenomicRanges_1.12.5 > [8] grid_3.0.1 IRanges_1.18.3 lattice_0.20-15 rpart_4.1-1 stats4_3.0.1 tools_3.0.1 zlibbioc_1.6.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Laurent Gatto - http://proteome.sysbiol.cam.ac.uk/lgatto/ Cambridge Centre for Proteomics - http://www.bio.cam.ac.uk/proteomics Using R/Bioconductor for proteomics data analysis - http://lgatto.github.io/RforProteomics/
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