def blastx_results(ofile, srcDB, destDB, xformSrc=True, xformDest=False,
**kwargs):
'''store blastx or tblastx results as a list of individual hits.
Each hit is stored as the usual NLMSASlice interface (e.g.
use its edges() method to get src,dest,edgeInfo tuples'''
p = BlastHitParser()
alignedIvals = read_aligned_coords(p.parse_file(ofile), srcDB, destDB,
dict(id='src_id', start='src_start',
stop='src_end', ori='src_ori',
idDest='dest_id',
startDest='dest_start',
stopDest='dest_end',
oriDest='dest_ori'))
l = []
for t in generate_tblastn_ivals(alignedIvals, xformSrc, xformDest):
if isinstance(t, CoordsGroupStart):
al = cnestedlist.NLMSA('blasthits', 'memory', pairwiseMode=True)
elif isinstance(t, CoordsGroupEnd): # process all ivals in this hit
al.build()
l.append(al[queryORF]) # save NLMSASlice view of this hit
else: # just keep accumulating all the ivals for this hit
al += t[0]
al[t[0]][t[1]] = None # save their alignment
queryORF = t[0].path
return l
def read_blast_alignment(ofile, srcDB, destDB, al=None, pipeline=None,
translateSrc=False, translateDest=False):
"""Apply sequence of transforms to read input from 'ofile'.
srcDB: database for finding query sequences from the blast input;
destDB: database for finding subject sequences from the blast input;
al, if not None, must be a writeable alignment object in which to
store the alignment intervals;
translateSrc=True forces creation of a TranslationDB representing
the possible 6-frames of srcDB (for blastx, tblastx);
translateDest=True forces creation of a TranslationDB representing
the possible 6-frames of destDB (for tblastn, tblastx).
If pipeline is not None, it must be a list of filter functions each
taking a single argument and returning an iterator or iterable result
object.
"""
p = BlastHitParser()
d = dict(id='src_id',
start='src_start',
stop='src_end',
ori='src_ori',
idDest='dest_id',
startDest='dest_start',
stopDest='dest_end',
oriDest='dest_ori')
if translateSrc:
srcDB = translationDB.get_translation_db(srcDB)
if translateDest:
destDB = translationDB.get_translation_db(destDB)
cti = CoordsToIntervals(srcDB, destDB, d)
alignedIvals = cti(p.parse_file(ofile))
if pipeline is None:
result = save_interval_alignment(alignedIvals, al)
else: # apply all the filters in our pipeline one by one
result = alignedIvals
for f in pipeline:
result = f(result)
return result
def read_interval_alignment(ofile, srcDB, destDB, al=None, **kwargs):
"Read tab-delimited interval mapping between seqs from the 2 sets of seqs"
needToBuild = False
if al is None:
import cnestedlist
al = cnestedlist.NLMSA('blasthits', 'memory', pairwiseMode=True)
needToBuild = True
p = BlastHitParser()
al.add_aligned_intervals(p.parse_file(ofile), srcDB, destDB,
alignedIvalsAttrs=
dict(id='src_id', start='src_start',
stop='src_end', ori='src_ori',
idDest='dest_id', startDest='dest_start',
stopDest='dest_end', oriDest='dest_ori'),
**kwargs)
if p.nline == 0: # NO BLAST OUTPUT??
raise IOError('no BLAST output. Check that blastall is in your PATH')
if needToBuild:
al.build()
return al
def read_blast_alignment(ofile, srcDB, destDB, al=None, pipeline=None):
"""Apply sequence of transforms to read input from 'ofile'.
BlastHitParser; CoordsToIntervals; save_interval_alignment OR [pipeline]
If pipeline is not None, it must be a list of filter functions each
taking a single argument and returning an iterator or iterable result
object.
"""
p = BlastHitParser()
d = dict(id='src_id', start='src_start', stop='src_end', ori='src_ori',
idDest='dest_id', startDest='dest_start',
stopDest='dest_end', oriDest='dest_ori')
cti = CoordsToIntervals(srcDB, destDB, d)
alignedIvals = cti(p.parse_file(ofile))
if pipeline is None:
result = save_interval_alignment(alignedIvals, al)
else: # apply all the filters in our pipeline one by one
result = alignedIvals
for f in pipeline:
result = f(result)
return result
def __init__(self, ofile, srcDB, destDB, xformSrc=True, xformDest=False,
**kwargs):
import cnestedlist
p = BlastHitParser()
alignedIvals = read_aligned_coords(p.parse_file(ofile), srcDB, destDB,
dict(id='src_id', start='src_start',
stop='src_end', ori='src_ori',
idDest='dest_id',
startDest='dest_start',
stopDest='dest_end',
oriDest='dest_ori'))
l = []
for t in generate_tblastn_ivals(alignedIvals, xformSrc, xformDest):
if isinstance(t, CoordsGroupStart):
al = cnestedlist.NLMSA('blasthits', 'memory', pairwiseMode=True)
elif isinstance(t, CoordsGroupEnd): # process all ivals in this hit
al.build()
l.append(al[queryORF]) # save NLMSASlice view of this hit
else: # just keep accumulating all the ivals for this hit
al += t[0]
al[t[0]][t[1]] = None # save their alignment
queryORF = t[0].path
self.hits = l
