本文整理汇总了Python中oncotator.TranscriptProviderUtils.TranscriptProviderUtils.render_transcript_position方法的典型用法代码示例。如果您正苦于以下问题：Python TranscriptProviderUtils.render_transcript_position方法的具体用法？Python TranscriptProviderUtils.render_transcript_position怎么用？Python TranscriptProviderUtils.render_transcript_position使用的例子？那么恭喜您, 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类oncotator.TranscriptProviderUtils.TranscriptProviderUtils的用法示例。
在下文中一共展示了TranscriptProviderUtils.render_transcript_position方法的1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: annotate_mutation
# 需要导入模块: from oncotator.TranscriptProviderUtils import TranscriptProviderUtils [as 别名]
# 或者: from oncotator.TranscriptProviderUtils.TranscriptProviderUtils import render_transcript_position [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