本文整理汇总了Python中Bio.SeqFeature.SeqFeature.qualifiers['acc_average']方法的典型用法代码示例。如果您正苦于以下问题：Python SeqFeature.qualifiers['acc_average']方法的具体用法？Python SeqFeature.qualifiers['acc_average']怎么用？Python SeqFeature.qualifiers['acc_average']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Bio.SeqFeature.SeqFeature的用法示例。
在下文中一共展示了SeqFeature.qualifiers['acc_average']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: hmmsearch_genome
# 需要导入模块: from Bio.SeqFeature import SeqFeature [as 别名]
# 或者: from Bio.SeqFeature.SeqFeature import qualifiers['acc_average'] [as 别名]
def hmmsearch_genome(self, hmm, genome, table='Standard', decorate=False, **kwargs):
#get genes
genes = get_indexes_of_genes(genome)
if not genes: return None
for gene_id, gi in enumerate(genes):
genome.features[gi].qualifiers['feature_id'] = gi
genome.features[gi].qualifiers['gene_id'] = gene_id
#translate genes
with user_message('Translating genes/CDS of %s' % genome.description, '\n'):
translator = Translator(self._abort_event)
translation = translator.translate(genome, genes, table)
if not translation: return None
with user_message('Performing hmm search.'):
results = self.hmmsearch_recs(hmm, translation)
if not results: return None
with user_message('Parsing search results...'):
#get hit_ids of hmm matches
hits = dict()
for result in results:
for hit in result.iterhits():
hits[hit.id] = hit
#get indexes of features where hmm hit
hit_features = dict()
for t in translation:
if t.id in hits:
fid = t.features[0].qualifiers.get('feature_id')
if fid is None: continue
hit_features[fid] = hits[t.id], t
#decorate genome
if decorate:
with user_message('Adding results as annotations...'):
hmm_name = os.path.basename(hmm)
for f in hit_features:
feature = genome.features[f]
for hsp in hit_features[f][0]:
if feature.strand == 1:
hmm_location = FeatureLocation(feature.location.start+hsp.hit_start*3,
feature.location.start+hsp.hit_end*3,
feature.strand)
else:
hmm_location = FeatureLocation(feature.location.end-hsp.hit_end*3,
feature.location.end-hsp.hit_start*3,
feature.strand)
hmm_feature = SeqFeature(hmm_location, type='misc_feature')
hmm_feature.qualifiers['hmm_model'] = hmm_name
hmm_feature.qualifiers['bitscore'] = hsp.bitscore
hmm_feature.qualifiers['psi_evalue'] = hsp.psi_evalue
hmm_feature.qualifiers['evalue_cond'] = hsp.evalue_cond
hmm_feature.qualifiers['acc_average'] = hsp.acc_avg
hmm_feature.qualifiers['bias'] = hsp.bias
genome.features.append(hmm_feature)
print 'Done.\n'
return hit_features