本文整理汇总了Python中Bio.SearchIO._model.HSP.query_is_protein方法的典型用法代码示例。如果您正苦于以下问题：Python HSP.query_is_protein方法的具体用法？Python HSP.query_is_protein怎么用？Python HSP.query_is_protein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.SearchIO._model.HSP的用法示例。
在下文中一共展示了HSP.query_is_protein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: _create_hsp
# 需要导入模块: from Bio.SearchIO._model import HSP [as 别名]
# 或者: from Bio.SearchIO._model.HSP import query_is_protein [as 别名]
def _create_hsp(hid, qid, psl):
# protein flag
is_protein = _is_protein(psl)
# strand
#if query is protein, strand is 0
if is_protein:
qstrand = 0
else:
qstrand = 1 if psl['strand'][0] == '+' else -1
# try to get hit strand, if it exists
try:
hstrand = 1 if psl['strand'][1] == '+' else -1
except IndexError:
hstrand = 1 # hit strand defaults to plus
# query block starts
qstarts = _reorient_starts(psl['qstarts'], \
psl['blocksizes'], psl['qsize'], qstrand)
# hit block starts
if len(psl['strand']) == 2:
hstarts = _reorient_starts(psl['tstarts'], \
psl['blocksizes'], psl['tsize'], hstrand)
else:
hstarts = psl['tstarts']
# set query and hit coords
# this assumes each block has no gaps (which seems to be the case)
assert len(qstarts) == len(hstarts) == len(psl['blocksizes'])
query_range_all = zip(qstarts, [x + y for x, y in \
zip(qstarts, psl['blocksizes'])])
hit_range_all = zip(hstarts, [x + y for x, y in \
zip(hstarts, psl['blocksizes'])])
# check length of sequences and coordinates, all must match
if 'tseqs' in psl and 'qseqs' in psl:
assert len(psl['tseqs']) == len(psl['qseqs']) == \
len(query_range_all) == len(hit_range_all)
else:
assert len(query_range_all) == len(hit_range_all)
frags = []
# iterating over query_range_all, but hit_range_all works just as well
for idx, qcoords in enumerate(query_range_all):
hseqlist = psl.get('tseqs')
hseq = '' if not hseqlist else hseqlist[idx]
qseqlist = psl.get('qseqs')
qseq = '' if not qseqlist else qseqlist[idx]
frag = HSPFragment(hid, qid, hit=hseq, query=qseq)
# set alphabet
frag.alphabet = generic_dna
# set coordinates
frag.query_start = qcoords[0]
frag.query_end = qcoords[1]
frag.hit_start = hit_range_all[idx][0]
frag.hit_end = hit_range_all[idx][1]
# and strands
frag.query_strand = qstrand
frag.hit_strand = hstrand
frags.append(frag)
# create hsp object
hsp = HSP(frags)
# check if start and end are set correctly
assert hsp.query_start == psl['qstart']
assert hsp.query_end == psl['qend']
assert hsp.hit_start == psl['tstart']
assert hsp.hit_end == psl['tend']
# and check block spans as well
assert hsp.query_span_all == hsp.hit_span_all == psl['blocksizes']
# set its attributes
hsp.match_num = psl['matches']
hsp.mismatch_num = psl['mismatches']
hsp.match_rep_num = psl['repmatches']
hsp.n_num = psl['ncount']
hsp.query_gapopen_num = psl['qnuminsert']
hsp.query_gap_num = psl['qbaseinsert']
hsp.hit_gapopen_num = psl['tnuminsert']
hsp.hit_gap_num = psl['tbaseinsert']
hsp.ident_num = psl['matches'] + psl['repmatches']
hsp.gapopen_num = psl['qnuminsert'] + psl['tnuminsert']
hsp.gap_num = psl['qbaseinsert'] + psl['tbaseinsert']
hsp.query_is_protein = is_protein
hsp.ident_pct = 100.0 - _calc_millibad(psl, is_protein) * 0.1
hsp.score = _calc_score(psl, is_protein)
# helper flag, for writing
hsp._has_hit_strand = len(psl['strand']) == 2
return hsp