@files( ((PARAMS["ensembl_filename_gtf"], "gene2omim.load"),))
def loadGene2Omim( infile, outfile ):

    tablename = P.toTable( outfile )

    columns = {
        "ensembl_gene_id" : "gene_id",
        "mim_gene_accession" : "mim_gene_id",
        "mim_morbid_accession" : "mim_morbid_id",
        "mim_morbid_description" : "mim_morbid_description",
        }

    data = PBiomart.biomart_iterator( columns.keys()
                                      , biomart = "ensembl"
                                      , dataset = "hsapiens_gene_ensembl" )

    def transform_data( data ):
        for result in data:
            for x in ("mim_gene_accession", "mim_morbid_accession"):
                result[x] = ("", result[x])[result[x] >= 0]
            yield result

    PDatabase.importFromIterator( outfile
                                  , tablename
                                  , transform_data(data)
                                  , columns = columns 
                                  , indices = ("gene_id", ) )
Returns the results name for this token expression.
dataset/ETHPy150Open CGATOxford/cgat/obsolete/pipeline_snps.py/loadGene2Omim--crossover with--dataset/ETHPy150Open ipython/ipython-py3k/IPython/external/pyparsing/_pyparsing.py/ParseResults.getName