Hi, I am hoping to find an R package/downloadable resource for validated (and predicted) miRNA targets. I have already investigated a few sites : miRWalk (which is not downloadable in its entirety and has a limit on the number of miRNA you can feed into it's web form), tarBase (which does not seem to have been updated in a while) and miRecords. miRecords does have a downloadable excel spreadsheet with validated target information (and pubmed ID) - and has 2112 miRId -> Gene pairs. Which is usually the methodology of choice for working with predicted/validated targets? I am concerned with using resources that may not be updated regularly -- or in downloading a file which may be a snapshot at a certain time. Any guidance would be greatly appreciated. Thanks, Ranjani -- output of sessionInfo(): R version 2.15.2 (2012-10-26) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C LC_TIME=English_United States.1252 attached base packages: [1] grid stats graphics grDevices utils datasets methods base other attached packages: [1] VennDiagram_1.6.0 edgeR_3.0.8 limma_3.14.4 DESeq_1.10.1 lattice_0.20-15 locfit_1.5-9.1 [7] Biobase_2.18.0 BiocGenerics_0.4.0 loaded via a namespace (and not attached): [1] annotate_1.36.0 AnnotationDbi_1.20.7 DBI_0.2-7 genefilter_1.40.0 geneplotter_1.36.0 [6] IRanges_1.16.6 parallel_2.15.2 RColorBrewer_1.0-5 RSQLite_0.11.4 splines_2.15.2 [11] stats4_2.15.2 survival_2.37-4 tools_2.15.2 XML_3.98-1.1 xtable_1.7-1 -- Sent via the guest posting facility at bioconductor.org.

Hi Ranjani, On 7/8/2013 4:04 PM, Ranjani R [guest] wrote: > Hi, > I am hoping to find an R package/downloadable resource for validated (and predicted) miRNA targets. I have already investigated a few sites : miRWalk (which is not downloadable in its entirety and has a limit on the number of miRNA you can feed into it's web form), tarBase (which does not seem to have been updated in a while) and miRecords. miRecords does have a downloadable excel spreadsheet with validated target information (and pubmed ID) - and has 2112 miRId -> Gene pairs. > Which is usually the methodology of choice for working with predicted/validated targets? I am concerned with using resources that may not be updated regularly -- or in downloading a file which may be a snapshot at a certain time. I am not sure exactly what your point here is (aren't all annotation data by definition a snapshot in time?). But in general BioC is released every 6 months, and I would in general expect the various annotation data to be updated as well. However, all the annotation in BioC are just pass-through (e.g., we just take extant annotations and repackage in easier to use formats), so the updating is dependent to a certain extent on others. Anyway, there is the mirbase.db package as well as the RmiR.Hs.miRNA package. The latter seems more to your liking. Best, Jim > Any guidance would be greatly appreciated. > Thanks, > Ranjani > > -- output of sessionInfo(): > > R version 2.15.2 (2012-10-26) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 > [4] LC_NUMERIC=C LC_TIME=English_United States.1252 > > attached base packages: > [1] grid stats graphics grDevices utils datasets methods base > > other attached packages: > [1] VennDiagram_1.6.0 edgeR_3.0.8 limma_3.14.4 DESeq_1.10.1 lattice_0.20-15 locfit_1.5-9.1 > [7] Biobase_2.18.0 BiocGenerics_0.4.0 > > loaded via a namespace (and not attached): > [1] annotate_1.36.0 AnnotationDbi_1.20.7 DBI_0.2-7 genefilter_1.40.0 geneplotter_1.36.0 > [6] IRanges_1.16.6 parallel_2.15.2 RColorBrewer_1.0-5 RSQLite_0.11.4 splines_2.15.2 > [11] stats4_2.15.2 survival_2.37-4 tools_2.15.2 XML_3.98-1.1 xtable_1.7-1 > > -- > 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