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", archive=TRUE) 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: > Hello, > > 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 However, it is possible to connect to an archived version of Ensembl which may 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 > >> listMarts(archive=TRUE) > > and then connect to one of those by specifying for example > >> ensembl <- useMart("ensembl_mart_43", dataset="hsapiens_gene_ensembl", > archive=TRUE) > > 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 > >> listAttributes(ensembl) > > 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 > assembly. > > Regards, > Joern > > On Thu, 4 Mar 2010 12:10:25 +0000, Paul Geeleher wrote >> Hi, >> >> 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. >> >> Sincerely, >> >> Paul > -- Paul Geeleher School of Mathematics, Statistics and Applied Mathematics National University of Ireland Galway Ireland -- www.bioinformaticstutorials.com