On 10/08/2013 08:21 PM, Ipsita Sinha wrote: > Thanks for the tip. Seems to be working. > > I have now have the nested list for the GOids now for the plasmodium falciparum. > I am now looking at summarizing them and have two questions. > > Is there a go slim database for plasmodium falciparum? Doesn't appear to have one. > There are multiple evidence levels for each GoID for each gene, and at this > point it is difficult to divide them. I am trying to get the CC part of the Go > database and bin the genes based on location and I am thinking the GO slim will > reduce the granularity? I'm not sure which evidence codes would be useful (they are enumerated here http://www.geneontology.org/GO.evidence.shtml); in general after having mapped your ids to GO mapped = select(org.Pf.plasmo.db, ids, "GO", keytype="SYMBOL") you can subset the map to have things you're interested in with something like codesILike = c("EXP", "IDA", "IPI", "IMP", "IGI", "IEP") good = subset(mapped, (ONTOLOGY %in% "CC") & (EVIDENCE %in% codesILike)) I'm not sure what your 'nested list' looks like or where you're aiming for, but with(good, split(SYMBOL, GO)) would give you a list of GO ids with their corresponding SYMBOL. I don't have any special insight into P. falciparum GO slims. Martin > > Thank you for your help. Again sorry for the confusion. Its a steep learning > curve for me as I have only been looking at bioinformatics in general for the > past month. > > Ipsita > > > On 8 October 2013 19:14, Martin Morgan <mtmorgan at="" fhcrc.org=""> <mailto:mtmorgan at="" fhcrc.org="">> wrote: > > On 10/08/2013 01:09 AM, Maintainer wrote: > > > I have a list of genenames - plasmodium falciparum gotten from the > plasmodb website. > > I am trying to get the associated GO:IDs in order to bin the genes into > housekeeping versus non-housekeeping genes. > And also in terms of functional and process. > > I have installed the org.Pf.plasmo.db using biocLite. > > > I'm guessing you have keys like > > > ids <- head(keys(org.Pf.plasmo.db, "SYMBOL")) > > ids > [1] "PF3D7_0100100" "PF3D7_0100200" "PF3D7_0100300" "PF3D7_0100400" > [5] "PF3D7_0100500" "PF3D7_0100600" > > and what you want to do is create your own vector 'ids' and then > > select(org.Pf.plasmo.db, ids, "GO", keytype="SYMBOL") > > Martin > > > I have tried to use this example: > > x <- org.Pf.plasmoGO > # Get the ORF identifiers that are mapped to a GO ID > mapped_genes <- mappedkeys(x) > # Convert to a list > xx <- as.list(x[mapped_genes]) > if(length(xx) > 0) { > # Try the first one > got <- xx[[1]] > got[[1]][["GOID"]] > got[[1]][["Ontology"]] > got[[1]][["Evidence"]] > } > > It doesnt provide an opportunity to create a column and enter my own > gene names. It appears to be a premapped set of genenames. As a result I > decided to use the example to get all mappings in the list xx > > Unfortunately, I am unable to iterate through the list to generate it in > a dataframe to meaningfully divide up the data. > > Secondly is there a way to actually query a database directly via R to > get the associated GO:ID where the input would be a genename. > > Sorry to sound confused. I am pretty new to R and bioconductor. > > > -- output of sessionInfo(): > > R version 3.0.1 (2013-05-16) > 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] parallel stats graphics grDevices utils datasets methods > base > > other attached packages: > [1] org.Pf.plasmo.db_2.9.0 BiocInstaller_1.10.3 GO.db_2.9.0 > hgu95av2.db_2.9.0 org.Hs.eg.db_2.9.0 > [6] RSQLite_0.11.4 DBI_0.2-7 > AnnotationDbi_1.22.6 Biobase_2.20.1 BiocGenerics_0.6.0 > > loaded via a namespace (and not attached): > [1] digest_0.6.3 grid_3.0.1 gtable_0.1.2 > IRanges_1.18.4 plyr_1.8 proto_0.3-10 > [7] RColorBrewer_1.0-5 reshape2_1.2.2 stats4_3.0.1 > stringr_0.6.2 tools_3.0.1 > > -- > Sent via the guest posting facility at bioconductor.org > <http: bioconductor.org="">. > > ____________________________________________________________ ________________ > devteam-bioc mailing list > To unsubscribe from this mailing list send a blank email to > devteam-bioc-leave at lists.__fhcrc.org > <mailto:devteam-bioc-leave at="" lists.fhcrc.org=""> > You can also unsubscribe or change your personal options at > https://lists.fhcrc.org/__mailman/listinfo/devteam-bioc > <https: lists.fhcrc.org="" mailman="" listinfo="" devteam-bioc=""> > > > > -- > Computational Biology / Fred Hutchinson Cancer Research Center > 1100 Fairview Ave. N. > PO Box 19024 Seattle, WA 98109 > > Location: Arnold Building M1 B861 > Phone: (206) 667-2793 > > -- Computational Biology / Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109 Location: Arnold Building M1 B861 Phone: (206) 667-2793