Python Annotator.retrieve_transcripts_by_region方法代码示例

# 需要导入模块: from oncotator.Annotator import Annotator [as 别名]
# 或者: from oncotator.Annotator.Annotator import retrieve_transcripts_by_region [as 别名]
    def test_simple_genes_by_region_annotation(self):
        """Test web api backend call /genes/ """
        # http://www.broadinstitute.org/oncotator/genes/chr22_22112223_22312558/
        # Two genes: chr22:22,112,223-22,312,558
        datasource_list = DatasourceFactory.createDatasources(self._determine_db_dir(), "hg19", isMulticore=False)
        annotator = Annotator()
        for ds in datasource_list:
            annotator.addDatasource(ds)

        # Here is what the API would call....
        txs = annotator.retrieve_transcripts_by_region("22", 22112223, 22312558)
        self.assertTranscriptsFound(txs)

        mut_dict = annotator.annotate_genes_given_txs(txs)

        # Each mut will be for a separate gene
        for gene in mut_dict.keys():
            mut = mut_dict[gene]
            alt_accessions = mut["UniProt_alt_uniprot_accessions"].split("|")
            tcgascape_amp_peaks = mut["TCGAScape_Amplification_Peaks"].split("|")
            tcgascape_del_peaks = mut["TCGAScape_Deletion_Peaks"].split("|")
            tumorscape_amp_peaks = mut["TUMORScape_Amplification_Peaks"].split("|")
            tumorscape_del_peaks = mut["TUMORScape_Deletion_Peaks"].split("|")
            full_name = mut["HGNC_Approved Name"]
            cosmic = {
                "tissue_types_affected": mut["COSMIC_Tissue_tissue_types_affected"],
                "total_alterations_in_gene": mut["COSMIC_Tissue_tissue_types_affected"],
            }
            alt_aliases = list(
                itertools.chain([mut["HGNC_Previous Symbols"].split(", "), mut["HGNC_Synonyms"].split(", ")])
            )
            location = mut["HGNC_Chromosome"]
            uniprot_accession = mut["UniProt_uniprot_accession"]
            transcripts = mut["transcripts"]
            self.assertTrue(transcripts is not None)
            self.assertTrue(len(transcripts) > 0)
            self.assertTrue(transcripts.startswith("ENST"))
            strand = mut["strand"]
            klass = mut["class"]
            uniprot_experimentals = mut["UniProt_AA_experimental_info"].split("|")
            self.assertTrue(uniprot_experimentals is not None)
            uniprot_natural_variations = mut["UniProt_AA_natural_variation"].split("|")
            uniprot_regions = mut["UniProt_AA_region"].split("|")
            uniprot_sites = mut["UniProt_AA_site"].split("|")
            uniprot_go_biological_processes = mut["UniProt_GO_Biological_Process"].split("|")
            uniprot_go_cellular_components = mut["UniProt_GO_Cellular_Component"].split("|")
            self.assertTrue(uniprot_go_cellular_components is not None)
            uniprot_go_molecular_functions = mut["UniProt_GO_Molecular_Function"].split("|")
            pass

# 需要导入模块: from oncotator.Annotator import Annotator [as 别名]
# 或者: from oncotator.Annotator.Annotator import retrieve_transcripts_by_region [as 别名]
    def test_querying_transcripts_by_region(self):
        """Test web api backend call /transcripts/.... """
        datasource_list = DatasourceFactory.createDatasources(self._determine_db_dir(), "hg19", isMulticore=False)
        annotator = Annotator()
        for ds in datasource_list:
            annotator.addDatasource(ds)
        txs = annotator.retrieve_transcripts_by_region("4", 50164411, 60164411)
        self.assertTranscriptsFound(txs)

        ## Here is an example of getting enough data to populate the json in doc/transcript_json_commented.json.txt
        # None of these values are validated.
        for tx in txs:
            transcript_id = tx.get_transcript_id()
            tx_start = tx.determine_transcript_start()
            tx_end = tx.determine_transcript_stop()
            gene = tx.get_gene()
            chr = tx.get_contig()
            n_exons = len(tx.get_exons())
            strand = tx.get_strand()
            footprint_start, footprint_end = tx.determine_cds_footprint()
            klass = tx.get_gene_type()
            cds_start = tx.determine_cds_start()
            cds_end = tx.determine_cds_stop()
            id = tx.get_gene_id()
            genomic_coords = [[exon[0], exon[1]] for exon in tx.get_exons()]
            transcript_coords = [
                [TranscriptProviderUtils.convert_genomic_space_to_exon_space(exon[0] + 1, exon[1], tx)]
                for exon in tx.get_exons()
            ]
            code_len = int(cds_end) - int(cds_start) + 1

            # If refseq datasources are not available, this will fail.
            # Step 2 annotate the transcript, which produces a dummy mutation with the refseq annotations.
            dummy_mut = annotator.annotate_transcript(tx)
            refseq_mRNA_id = dummy_mut["gencode_xref_refseq_mRNA_id"]
            refseq_prot_id = dummy_mut["gencode_xref_refseq_prot_acc"]

            # Description is unavailable right now
            description = ""

            self.assertTrue(refseq_mRNA_id is not None)
            self.assertTrue(refseq_prot_id is not None)
            self.assertTrue(len(transcript_coords) == n_exons)