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Python TranscriptProviderUtils.infer_variant_type方法代码示例

本文整理汇总了Python中oncotator.TranscriptProviderUtils.TranscriptProviderUtils.infer_variant_type方法的典型用法代码示例。如果您正苦于以下问题:Python TranscriptProviderUtils.infer_variant_type方法的具体用法?Python TranscriptProviderUtils.infer_variant_type怎么用?Python TranscriptProviderUtils.infer_variant_type使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在oncotator.TranscriptProviderUtils.TranscriptProviderUtils的用法示例。


在下文中一共展示了TranscriptProviderUtils.infer_variant_type方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: initializeMutFromAttributes

# 需要导入模块: from oncotator.TranscriptProviderUtils import TranscriptProviderUtils [as 别名]
# 或者: from oncotator.TranscriptProviderUtils.TranscriptProviderUtils import infer_variant_type [as 别名]
    def initializeMutFromAttributes(chr, start, end, ref_allele, alt_allele, build, mutation_data_factory=None):
        mutation_data_factory = MutationDataFactory() if mutation_data_factory is None else mutation_data_factory
        mut = mutation_data_factory.create(str(chr), str(start), str(end), ref_allele, alt_allele, str(build))
        varType = TranscriptProviderUtils.infer_variant_type(mut.ref_allele, mut.alt_allele)

        if TranscriptProviderUtils.is_xnp(varType):  # Snps and other xNPs
            mut.createAnnotation(annotationName=MutUtils.PRECEDING_BASES_ANNOTATION_NAME, annotationValue="")
        if varType == VariantClassification.VT_DEL:  # deletion
            preceding_bases, updated_ref_allele, updated_start, updated_end =\
                MutUtils.retrievePrecedingBasesForDeletions(mut)
            mut.ref_allele = updated_ref_allele
            mut["ref_allele"] = updated_ref_allele
            mut.alt_allele = "-"
            mut["alt_allele"] = "-"
            mut.start = updated_start
            mut["start"] = updated_start
            mut.end = updated_end
            mut["end"] = updated_end
            mut.createAnnotation(annotationName=MutUtils.PRECEDING_BASES_ANNOTATION_NAME,
                                 annotationValue=preceding_bases)
        elif varType == VariantClassification.VT_INS:  # insertion
            preceding_bases, updated_alt_allele, updated_start, updated_end = \
                MutUtils.retrievePrecedingBasesForInsertions(mut)
            mut.ref_allele = "-"
            mut["ref_allele"] = "-"
            mut.alt_allele = updated_alt_allele
            mut["alt_allele"] = updated_alt_allele
            mut.start = updated_start
            mut["start"] = updated_start
            mut.end = updated_end
            mut["end"] = updated_end
            mut.createAnnotation(annotationName=MutUtils.PRECEDING_BASES_ANNOTATION_NAME,
                                 annotationValue=preceding_bases)

        return mut
开发者ID:Tmacme,项目名称:oncotator,代码行数:37,代码来源:MutUtils.py

示例2: annotate_mutation

# 需要导入模块: from oncotator.TranscriptProviderUtils import TranscriptProviderUtils [as 别名]
# 或者: from oncotator.TranscriptProviderUtils.TranscriptProviderUtils import infer_variant_type [as 别名]
    def annotate_mutation(self, mutation):
        chr = mutation.chr
        start = int(mutation.start)
        end = int(mutation.end)
        txs = self.get_transcripts_by_pos(chr, start, end)
        final_annotation_dict = self._create_blank_set_of_annotations()
        final_annotation_dict['variant_type'] = Annotation(value=TranscriptProviderUtils.infer_variant_type(mutation.ref_allele, mutation.alt_allele), datasourceName=self.title)
        chosen_tx = None

        # We have hit IGR if no transcripts come back.  Most annotations can just use the blank set.
        if len(txs) == 0:
            final_annotation_dict['variant_classification'] = self._create_basic_annotation(VariantClassification.IGR)
            nearest_genes = self._get_nearest_genes(chr, int(start), int(end))
            final_annotation_dict['other_transcripts'] = self._create_basic_annotation(value='%s (%s upstream) : %s (%s downstream)' % (nearest_genes[0][0], nearest_genes[0][1], nearest_genes[1][0], nearest_genes[1][1]))
            final_annotation_dict['gene'] = self._create_basic_annotation('Unknown')
            final_annotation_dict['gene_id'] = self._create_basic_annotation('0')
            final_annotation_dict['genome_change'] = self._create_basic_annotation(TranscriptProviderUtils.determine_genome_change(mutation.chr, mutation.start, mutation.end, mutation.ref_allele, mutation.alt_allele, final_annotation_dict['variant_type'].value))
        else:
            # Choose the best effect transcript
            chosen_tx = self._choose_transcript(txs, self.get_tx_mode(), final_annotation_dict['variant_type'].value, mutation.ref_allele, mutation.alt_allele, start, end)
            vcer = VariantClassifier()

            final_annotation_dict['annotation_transcript'] = self._create_basic_annotation(chosen_tx.get_transcript_id())
            final_annotation_dict['genome_change'] = self._create_basic_annotation(TranscriptProviderUtils.determine_genome_change(mutation.chr, mutation.start, mutation.end, mutation.ref_allele, mutation.alt_allele, final_annotation_dict['variant_type'].value))
            final_annotation_dict['strand'] = self._create_basic_annotation(chosen_tx.get_strand())

            final_annotation_dict['transcript_position'] = self._create_basic_annotation(TranscriptProviderUtils.render_transcript_position(int(start), int(end), chosen_tx))

            final_annotation_dict['transcript_id'] = self._create_basic_annotation(chosen_tx.get_transcript_id())

            variant_classfication = vcer.variant_classify(tx=chosen_tx, variant_type=final_annotation_dict['variant_type'].value,
                                             ref_allele=mutation.ref_allele, alt_allele=mutation.alt_allele, start=mutation.start, end=mutation.end)
            final_annotation_dict['transcript_exon'] = self._create_basic_annotation(str(variant_classfication.get_exon_i()+1))
            final_annotation_dict['variant_classification'] = self._create_basic_annotation(variant_classfication.get_vc())
            final_annotation_dict['secondary_variant_classification'] = self._create_basic_annotation(variant_classfication.get_secondary_vc())
            final_annotation_dict['protein_change'] = self._create_basic_annotation(vcer.generate_protein_change_from_vc(variant_classfication))
            final_annotation_dict['codon_change'] = self._create_basic_annotation(vcer.generate_codon_change_from_vc(chosen_tx, start, end, variant_classfication))
            final_annotation_dict['transcript_change'] = self._create_basic_annotation(vcer.generate_transcript_change_from_tx(chosen_tx, final_annotation_dict['variant_type'].value, variant_classfication, start, end, mutation.ref_allele, mutation.alt_allele))

            final_annotation_dict['transcript_strand'] = self._create_basic_annotation(chosen_tx.get_strand())
            final_annotation_dict['gene'] = self._create_basic_annotation(chosen_tx.get_gene())
            final_annotation_dict['gene_type'] = self._create_basic_annotation(chosen_tx.get_gene_type())
            final_annotation_dict['gencode_transcript_tags'] = self._create_basic_annotation(self._retrieve_gencode_tag_value(chosen_tx, 'tag'))
            final_annotation_dict['gencode_transcript_status'] = self._create_basic_annotation(self._retrieve_gencode_tag_value(chosen_tx, 'transcript_status'))
            final_annotation_dict['havana_transcript'] = self._create_basic_annotation(self._retrieve_gencode_tag_value(chosen_tx, 'havana_transcript'))
            final_annotation_dict['ccds_id'] = self._create_basic_annotation(self._retrieve_gencode_tag_value(chosen_tx, 'ccdsid'))
            final_annotation_dict['gencode_transcript_type'] = self._create_basic_annotation(self._retrieve_gencode_tag_value(chosen_tx, 'transcript_type'))
            final_annotation_dict['gencode_transcript_name'] = self._create_basic_annotation(self._retrieve_gencode_tag_value(chosen_tx, 'transcript_name'))

            other_transcript_value = self._render_other_transcripts(txs, [txs.index(chosen_tx)], final_annotation_dict['variant_type'].value, mutation.ref_allele, mutation.alt_allele, mutation.start, mutation.end)
            final_annotation_dict['other_transcripts'] = self._create_basic_annotation(other_transcript_value)
            # final_annotation_dict['gene_id'].value

        mutation.addAnnotations(final_annotation_dict)

        # Add the HGVS annotations ... setting to "" if not available.
        hgvs_dict_annotations = self._create_hgvs_annotation_dict(mutation, chosen_tx)
        mutation.addAnnotations(hgvs_dict_annotations)

        return mutation
开发者ID:alexramos,项目名称:oncotator,代码行数:62,代码来源:EnsemblTranscriptDatasource.py

示例3: _add

# 需要导入模块: from oncotator.TranscriptProviderUtils import TranscriptProviderUtils [as 别名]
# 或者: from oncotator.TranscriptProviderUtils.TranscriptProviderUtils import infer_variant_type [as 别名]
 def _add(self, mutation):
     variant_type = TranscriptProviderUtils.infer_variant_type(mutation.ref_allele, mutation.alt_allele)
     # only combine ONPs, not indels
     if not TranscriptProviderUtils.is_xnp(variant_type):
         self.indel_queue.append(mutation)
     else:
         self.queue[self.sns.getSampleName(mutation)].append(mutation)
开发者ID:Yixf-Self,项目名称:oncotator,代码行数:9,代码来源:OnpQueue.py

示例4: annotate_mutation

# 需要导入模块: from oncotator.TranscriptProviderUtils import TranscriptProviderUtils [as 别名]
# 或者: from oncotator.TranscriptProviderUtils.TranscriptProviderUtils import infer_variant_type [as 别名]
    def annotate_mutation(self, mutation, upstream_padding=3000, downstream_padding=0):
        mutation.createAnnotation('variant_type', TranscriptProviderUtils.infer_variant_type(mutation.ref_allele, mutation.alt_allele), self.title)
        data = [mutation]
        data = gaf_annotation.find_mut_in_gaf(data, self)
        data = gaf_annotation.identify_best_effect_transcript(data, self)
        data = gaf_annotation.identify_best_canonical_transcript(data, self)
        data = gaf_annotation.correct_transcript_coordinates(data, self)
        data = gaf_annotation.infer_output_fields(data, self)

        data = self._annotateMutationFromTranscripts(data)

        annotated_mutation = data.next()
        return annotated_mutation
开发者ID:Tmacme,项目名称:oncotator,代码行数:15,代码来源:Gaf.py

示例5: test_infer_variant_type

# 需要导入模块: from oncotator.TranscriptProviderUtils import TranscriptProviderUtils [as 别名]
# 或者: from oncotator.TranscriptProviderUtils.TranscriptProviderUtils import infer_variant_type [as 别名]
 def test_infer_variant_type(self,ref,alt,vt_gt):
     """test that we can tell a snp from an indel"""
     self.assertEqual(TranscriptProviderUtils.infer_variant_type(ref, alt), vt_gt)
开发者ID:Tmacme,项目名称:oncotator,代码行数:5,代码来源:TranscriptProviderUtilsTest.py


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