[BioC] retrieveGenomicFeatureAnnotation.R file supplied with Ringo
paulgeeleher at gmail.com
Thu Mar 4 18:10:51 CET 2010
Ah that's exactly what I was looking for, thank you for you're help.
For the record:
ensembl <- useMart("ensembl_mart_51", dataset="hsapiens_gene_ensembl",
will get you the hg18(NCBI36) genome build.
On Thu, Mar 4, 2010 at 1:15 PM, Joern Toedling <Joern.Toedling at curie.fr> wrote:
> by default, the biomaRt functions listed in the script query the current
> version of Ensembl, and the genome assemblies thus are those used in the
> current Ensembl release.
> However, it is possible to connect to an archived version of Ensembl which may
> contain a previous version of your respective genome build.
> For a table of available archived marts, you can use
> and then connect to one of those by specifying for example
>> ensembl <- useMart("ensembl_mart_43", dataset="hsapiens_gene_ensembl",
> and then you should be able to use the rest of the script as with the current
> one. There might be minor problems because sometimes attributes get renamed
> between Ensembl releases, but usually one can resolve these by looking at
> For checking assembly versions in Ensembl releases, however, I think that you
> first need to consult the Ensembl archive pages before picking one. I am not
> aware of a more automated way to select the mart based on the desired genome
> On Thu, 4 Mar 2010 12:10:25 +0000, Paul Geeleher wrote
>> I've been following the instructions in the Ringo manual and using
>> this file to associate my Chip Enriched regions with genomic
>> features. Thing is it seems that in
>> retrieveGenomicFeatureAnnotation.R biomaRt is querying the HG19
>> genome build. I haven't been able to find a way of changing this to
>> HG18, having searched the web I don't think it's possible? If there
>> is no way of explicitly specifying the genome build maybe it would
>> be worth noting somewhere in the file or documentation that biomaRt
>> is using HG19? Just that I guess the fast majority of people will be
>> using microarrays based on HG18?
>> As an alternative I think I'm just going to try reading gene
>> locations from a BED file on the UCSC site.
School of Mathematics, Statistics and Applied Mathematics
National University of Ireland
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