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?

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@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.
>>
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>>
>
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