def getCopy( self ):
"""return a new copy.
"""
new_entry = Prediction()
new_entry.mExpand = self.mExpand
new_entry.mPredictionId = self.mPredictionId
new_entry.mQueryToken = self.mQueryToken
new_entry.mQueryFrom = self.mQueryFrom
new_entry.mQueryTo = self.mQueryTo
new_entry.mSbjctToken = self.mSbjctToken
new_entry.mSbjctStrand = self.mSbjctStrand
new_entry.mSbjctFrom = self.mSbjctFrom
new_entry.mSbjctTo = self.mSbjctTo
new_entry.mRank = self.mRank
new_entry.score = self.score
new_entry.mQueryLength = self.mQueryLength
new_entry.mQueryCoverage = self.mQueryCoverage
new_entry.mNGaps = self.mNGaps
new_entry.mNFrameShifts = self.mNFrameShifts
new_entry.mNIntrons = self.mNIntrons
new_entry.mNSplits = self.mNSplits
new_entry.mNStopCodons = self.mNStopCodons
new_entry.mPercentIdentity = self.mPercentIdentity
new_entry.mPercentSimilarity = self.mPercentSimilarity
new_entry.mTranslation = self.mTranslation
new_entry.mSbjctGenomeFrom = self.mSbjctGenomeFrom
new_entry.mSbjctGenomeTo = self.mSbjctGenomeTo
new_entry.mAlignmentString = self.mAlignmentString
new_entry.mQueryAli = self.mQueryAli
new_entry.mSbjctAli = self.mSbjctAli
if self.mExpand:
new_entry.mMapPeptide2Translation = alignlib.makeAlignmentVector()
alignlib.copyAlignment( new_entry.mMapPeptide2Translation, self.mMapPeptide2Translation)
new_entry.mMapPeptide2Genome = Genomics.String2Alignment( new_entry.mAlignmentString)
else:
new_entry.mMapPeptide2Translation = self.mMapPeptide2Translation = None
new_entry.mMapPeptide2Genome = self.mMapPeptide2Genome = None
return new_entry
map_row2col.clear()
alignlib.AlignmentFormatExplicit(link.mQueryFrom, link.mQueryAli, link.mSbjctFrom, link.mSbjctAli).copy(
map_row2col
)
## test all combinations, the alignment might be a suboptimal alignment in case
## of repeats.
for e1 in cds[link.mQueryToken]:
for e2 in cds[link.mSbjctToken]:
tmp_map_row2col.clear()
if param_expand:
alignlib.copyAlignment(
tmp_map_row2col,
map_row2col,
e1.mPeptideFrom + 1,
e1.mPeptideTo,
e2.mPeptideFrom + 1,
e2.mPeptideTo,
)
else:
alignlib.copyAlignment(
tmp_map_row2col,
map_row2col,
e1.mPeptideFrom / 3 + 1,
e1.mPeptideTo / 3 + 1,
e2.mPeptideFrom / 3 + 1,
e2.mPeptideTo / 3 + 1,
)
## in case of split codons, there is an alignment of length 1. Skip that.
if tmp_map_row2col.getLength() > 1:
ref_genome_from -= ref_exons_offset
ref_genome_to -= ref_exons_offset
## get percent identity for exon
exon_percent_identity = 0
exon_percent_similarity = 0
if query_sequence and sbjct_sequence:
tmp_ali = alignlib.makeAlignmentVector()
xquery_from = exon_from / 3
xquery_to = exon_to / 3
alignlib.copyAlignment( tmp_ali, entry.mMapPeptide2Translation, xquery_from, xquery_to )
if tmp_ali.getLength() == 0:
options.stdlog.write( "# WARNING: empty alignment %s\n" % str((ref_from, exon_from, ref_to, exon_to, xquery_from, xquery_to)))
nempty_alignments += 1
else:
if options.loglevel >= 5:
options.stdlog.write( "# %s\n" % str( alignlib.AlignmentFormatExplicit( tmp_ali, query_sequence, sbjct_sequence ) ) )
exon_percent_identity = alignlib.calculatePercentIdentity( tmp_ali,
query_sequence,
sbjct_sequence ) * 100
exon_percent_similarity = alignlib.calculatePercentSimilarity( tmp_ali ) * 100
if exon_percent_identity >= min_pide:
is_good_exon = 1
def main( argv = None ):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv == None: argv = sys.argv
parser = E.OptionParser( version = "%prog version: $Id: gpipe/compare_predictions2exons.py 2011 2008-07-04 10:40:51Z andreas $",
usage = globals()["__doc__"] )
parser.add_option( "-g", "--genome-file", dest="genome_file", type="string",
help="filename with genome." )
parser.add_option( "-b", "--boundaries", dest="filename_boundaries", type="string",
help="filename with exon boundaries." )
parser.add_option( "-e", "--exons", dest="filename_exons", type="string",
help="filename with exons (output)." )
parser.add_option( "-p", "--peptides", dest="filename_peptides", type="string",
help="filename with peptide sequences." )
parser.add_option( "-w", "--write-notfound", dest="write_notfound", action="store_true",
help="print exons for predictions not found in reference." )
parser.add_option( "-q", "--quality-pide", dest="quality_threshold_pide", type="int",
help="quality threshold (pide) for exons." )
parser.set_defaults(
genome_file = "genome",
filename_boundaries = None,
filename_exons = None,
filename_peptides = None,
quality_threshold_pide = 0,
write_notfound = False,
## allowed number of nucleotides for exon boundaries to
## be considered equivalent.
slipping_exon_boundary = 9,
## stop codons to search for
stop_codons = ("TAG", "TAA", "TGA"), )
(options, args) = E.Start( parser, add_pipe_options = True )
if len(args) > 0:
print USAGE, "no arguments required."
sys.exit(2)
reference_exon_boundaries = {}
if options.filename_boundaries:
reference_exon_boundaries = Exons.ReadExonBoundaries( open( options.filename_boundaries, "r"),
do_invert = 1,
remove_utr = 1)
E.info( "read exon boundaries for %i queries" % len(reference_exon_boundaries) )
if options.filename_exons:
outfile_exons = open( options.filename_exons, "w")
outfile_exons.write( "%s\n" % "\t".join( (
"prediction_id",
"exon_id",
"exon_from",
"exon_to",
"exon_frame",
"reference_id",
"reference_from",
"reference_to",
"reference_phase",
"pidentity",
"psimilarity",
"nframeshifts",
"ngaps",
"nstopcodons",
"is_ok",
"genome_exon_from",
"genome_exon_to") ) )
else:
outfile_exons = None
if options.filename_peptides:
peptide_sequences = Genomics.ReadPeptideSequences( open(options.filename_peptides, "r") )
E.info("read peptide sequences for %i queries" % len(peptide_sequences) )
else:
peptide_sequences = {}
entry = PredictionParser.PredictionParserEntry()
last_filename_genome = None
nfound, nmissed_exons, nmissed_length = 0, 0, 0
nempty_alignments = 0
fasta = IndexedFasta.IndexedFasta( options.genome_file )
options.stdout.write( "%s\n" % "\t".join( (
"prediction_id",
"number",
"dubious_exons",
"boundaries_sum",
"boundaries_max",
"identical_exons",
"inserted_exons",
"deleted_exons",
"inserted_introns",
"deleted_introns",
"truncated_Nterminus",
"truncated_Cterminus",
"deleted_Nexons",
"deleted_Cexons",
"inserted_Nexons",
"inserted_Cexons" ) ) )
for line in sys.stdin:
if line[0] == "#": continue
try:
entry.Read(line)
except ValueError, msg:
print "# parsing failed with msg %s in line %s" % (msg, line[:-1])
sys.exit(1)
exons = Genomics.Alignment2ExonBoundaries( entry.mMapPeptide2Genome,
query_from = entry.mQueryFrom,
sbjct_from = entry.mSbjctGenomeFrom,
add_stop_codon = 0 )
if exons[-1][4] != entry.mSbjctGenomeTo:
print "# WARNING: discrepancy in exon calculation!!!"
for e in exons:
print "#", str(e)
print "#", str(entry)
if options.loglevel >= 5:
for e in exons:
print "#", str(e)
genomic_fragment = fasta.getSequence( entry.mSbjctToken, entry.mSbjctStrand,
entry.mSbjctGenomeFrom, entry.mSbjctGenomeTo )
skip = False
if peptide_sequences.has_key( entry.mQueryToken ):
query_sequence = alignlib.makeSequence(peptide_sequences[entry.mQueryToken])
sbjct_sequence = alignlib.makeSequence(entry.mTranslation)
percent_similarity, percent_identity = 0, 0
if query_sequence.getLength() < entry.mMapPeptide2Translation.getRowTo():
print "# WARNING: query sequence %s is too short: %i %i" % ( entry.mQueryToken,
query_sequence.getLength(),
entry.mMapPeptide2Translation.getRowTo())
sys.stdout.flush()
nmissed_length += 1
skip = True
elif sbjct_sequence.getLength() < entry.mMapPeptide2Translation.getColTo():
print "# WARNING: sbjct sequence %s is too short: %i %i" % ( entry.mSbjctToken,
sbjct_sequence.getLength(),
entry.mMapPeptide2Translation.getColTo())
sys.stdout.flush()
nmissed_length += 1
skip = True
else:
alignlib.rescoreAlignment( entry.mMapPeptide2Translation,
query_sequence,
sbjct_sequence,
alignlib.makeScorer( query_sequence, sbjct_sequence ) )
percent_identity = alignlib.calculatePercentIdentity( entry.mMapPeptide2Translation,
query_sequence,
sbjct_sequence ) * 100
percent_similarity = alignlib.calculatePercentSimilarity( entry.mMapPeptide2Translation ) * 100
E.debug( "prediction %s: percent identity/similarity: before=%5.2f/%5.2f, realigned=%5.2f/%5.2f" % (
str(entry.mPredictionId),
entry.mPercentSimilarity,
entry.mPercentIdentity,
percent_similarity,
percent_identity ) )
else:
query_sequence = None
sbjct_sequence = None
# default values
exons_num_exons = "na"
exons_boundaries_sum = "na"
exons_boundaries_max = "na"
dubious_exons = "na"
ndeleted_exons, ninserted_exons, ndeleted_introns, ninserted_introns, nidentical_exons = 0,0,0,0,0
truncated_Nterminal_exon, truncated_Cterminal_exon = 0,0
ndeleted_Nexons, ndeleted_Cexons = 0, 0
ninserted_Nexons, ninserted_Cexons = 0, 0
exons_offset = exons[0][3]
if not reference_exon_boundaries.has_key( entry.mQueryToken ):
print "# WARNING: sequence %s has no exon boundaries" % ( entry.mQueryToken )
sys.stdout.flush()
nmissed_exons += 1
skip = True
if not skip:
nfound += 1
ref_exons = reference_exon_boundaries[entry.mQueryToken]
ref_exons_offset = ref_exons[0].mGenomeFrom
exons_num_exons = len(ref_exons) - len(exons)
exons_boundaries_sum = 0
exons_phase = 0
exons_boundaries_max = 0
dubious_exons = 0
inserted_exons = 0
temp_inserted_exons = 0
if options.loglevel >= 3:
for e in exons:
options.stdlog.write( "# %s\n" % str(e) )
for e in ref_exons:
options.stdlog.write( "# %s\n" % str(e) )
min_pide = entry.mPercentIdentity * options.quality_threshold_pide / 100
in_sync = 0
e,r = 0,0
while e < len(exons) and r < len(ref_exons):
this_e, this_r = e+1, r+1
percent_identity = 0
percent_similarity = 0
is_good_exon = 0
if options.loglevel >= 4:
options.stdlog.write( "# current exons: %i and %i\n" % (e, r) )
sys.stdout.flush()
exon_from, exon_to, exon_phase, exon_genome_from, exon_genome_to, exon_ali = exons[e][0:6]
ref_from, ref_to, ref_phase, ref_genome_from, ref_genome_to = (ref_exons[r].mPeptideFrom,
ref_exons[r].mPeptideTo,
ref_exons[r].frame,
ref_exons[r].mGenomeFrom,
ref_exons[r].mGenomeTo)
ref_genome_from -= ref_exons_offset
ref_genome_to -= ref_exons_offset
## get percent identity for exon
exon_percent_identity = 0
exon_percent_similarity = 0
if query_sequence and sbjct_sequence:
tmp_ali = alignlib.makeAlignmentVector()
xquery_from = exon_from / 3
xquery_to = exon_to / 3
alignlib.copyAlignment( tmp_ali, entry.mMapPeptide2Translation, xquery_from, xquery_to )
if tmp_ali.getLength() == 0:
options.stdlog.write( "# WARNING: empty alignment %s\n" % str((ref_from, exon_from, ref_to, exon_to, xquery_from, xquery_to)))
nempty_alignments += 1
else:
if options.loglevel >= 5:
options.stdlog.write( "# %s\n" % str( alignlib.AlignmentFormatExplicit( tmp_ali, query_sequence, sbjct_sequence ) ) )
exon_percent_identity = alignlib.calculatePercentIdentity( tmp_ali,
query_sequence,
sbjct_sequence ) * 100
exon_percent_similarity = alignlib.calculatePercentSimilarity( tmp_ali ) * 100
if exon_percent_identity >= min_pide:
is_good_exon = 1
else:
is_good_exon = 0
if e < len(exons) -1 :
(next_exon_from, next_exon_to, next_exon_phase,
next_exon_genome_from, next_exon_genome_to, next_exon_ali) = exons[e+1][0:6]
else:
(next_exon_from, next_exon_to, next_exon_phase,
next_exon_genome_from, next_exon_genome_to, next_exon_ali) = 0, 0, 0, 0, 0, []
if r < len(ref_exons) - 1:
next_ref_from, next_ref_to, next_ref_phase = (ref_exons[r+1].mPeptideFrom,
ref_exons[r+1].mPeptideTo,
ref_exons[r+1].frame)
else:
next_ref_from, next_ref_to, next_ref_phase = 0, 0, 0
if options.loglevel >= 2:
options.stdlog.write( "# %s\n" % "\t".join( map(str, (entry.mQueryToken,
exon_from, exon_to, exon_phase,
exon_genome_from, exon_genome_to,
ref_from, ref_to, ref_phase ))))
sys.stdout.flush()
# beware of small exons.
# if less than options.slipping_exon_boundary: boundary is 0
# check if end is more than options.splipping_exon_boundary apart as well.
if exon_to - exon_from <= options.slipping_exon_boundary or \
ref_to - ref_from <= options.slipping_exon_boundary:
boundary = 0
else:
boundary = options.slipping_exon_boundary
if ref_to <= exon_from + boundary and \
ref_to <= exon_to - options.slipping_exon_boundary:
## no overlap
is_good_exon = 0
if e == 0:
ndeleted_Nexons += 1
else:
ndeleted_exons += 1
r += 1
exon_from, exon_to, exon_phase, exon_genome_from, exon_genome_to = 0, 0, 0, 0, 0
overlap = 0
elif exon_to <= ref_from + boundary and \
exon_to <= ref_to - options.slipping_exon_boundary:
## no overlap
is_good_exon = 0
if r == 0:
ninserted_Nexons += 1
else:
ninserted_exons += 1
e += 1
ref_from, ref_to, ref_phase = 0, 0, 0
overlap = 0
else:
## overlap
overlap = 1
dfrom = int(math.fabs(exon_from - ref_from))
dto = int(math.fabs(exon_to - ref_to))
## get percent identity for overlapping fragment
if query_sequence and sbjct_sequence:
## this the problem
tmp_ali = alignlib.makeAlignmentVector()
xquery_from = max( ref_from / 3, exon_from / 3)
xquery_to = min(ref_to / 3, exon_to / 3)
alignlib.copyAlignment( tmp_ali, entry.mMapPeptide2Translation, xquery_from, xquery_to )
if tmp_ali.getLength() == 0:
options.stdlog.write( "# warning: empty alignment %s\n" % str((ref_from, exon_from, ref_to, exon_to, xquery_from, xquery_to )))
percent_identity = 0
percent_similarity = 0
else:
if options.loglevel >= 5:
print str( alignlib.AlignmentFormatExplicit( tmp_ali, query_sequence, sbjct_sequence ) )
percent_identity = alignlib.calculatePercentIdentity( tmp_ali,
query_sequence,
sbjct_sequence ) * 100
percent_similarity = alignlib.calculatePercentSimilarity( tmp_ali ) * 100
if percent_identity >= min_pide:
is_good_exon = 1
else:
is_good_exon = 0
dubious_exons += 1
## adjust regions for terminal exons
if e == 0 and r == 0 and dfrom <= (entry.mQueryFrom - 1) * 3 and dfrom > 0:
if is_good_exon:
truncated_Nterminal_exon = dfrom
dfrom = 0
## truncated terminal exons
if e == len(exons)-1 and r == len(ref_exons)-1 and dto <= (entry.mQueryLength - entry.mQueryTo) * 3 and dto > 0:
if is_good_exon:
truncated_Cterminal_exon = dto
dto = 0
## do not count deviations for terminal query exons
if e == 0 and dfrom <= entry.mQueryFrom * 3 and dfrom > 0:
dfrom = 0
if e == len(exons)-1 and dto <= (entry.mQueryLength - entry.mQueryTo) * 3 and dto > 0:
dto = 0
## permit difference of one codon (assumed to be stop)
if e == len(exons)-1 and r == len(ref_exons)-1 and dto == 3:
dto = 0
## deal with different boundary conditions:
if dfrom == 0 and dto == 0:
if is_good_exon: nidentical_exons += 1
e += 1
r += 1
## next exon within this ref_exon
elif exon_to < ref_to and next_exon_to and next_exon_to <= ref_to + options.slipping_exon_boundary:
if is_good_exon: ninserted_introns += 1
e += 1
in_sync = 1
dto = 0
## next ref_exon within this exon
elif ref_to < exon_to and next_ref_to and next_ref_to <= exon_to + options.slipping_exon_boundary:
if is_good_exon: ndeleted_introns += 1
r += 1
in_sync = 1
dto = 0
else:
e += 1
r += 1
if in_sync:
dfrom = 0
if is_good_exon:
exons_boundaries_sum += dfrom + dto
exons_boundaries_max = max( dfrom, exons_boundaries_max )
exons_boundaries_max = max( dto, exons_boundaries_max )
###########################################################
## count inserted/deleted introns and misplaced boundaries
##
## if exon and next_exon in ref_exon: inserted intron
## if ref_exon and next_ref_exon in exon: deleted intron
if outfile_exons:
if genomic_fragment and exon_genome_to:
nintrons, nframeshifts, ngaps, nsplits, nstopcodons, disruptions = Genomics.CountGeneFeatures( exon_genome_from - entry.mSbjctGenomeFrom,
exon_ali,
genomic_fragment,
border_stop_codon = 0
)
else:
nintrons, nframeshifts, ngaps, nsplits, nstopcodons = 0, 0, 0, 0, 0
if exon_to == 0: this_e = 0
if ref_to == 0: this_r = 0
outfile_exons.write( string.join( map(str, (entry.mPredictionId,
this_e, exon_from, exon_to, exon_phase,
this_r, ref_from, ref_to, ref_phase,
percent_identity, percent_similarity,
nframeshifts, ngaps, nstopcodons,
is_good_exon,
exon_genome_from, exon_genome_to,
)), "\t") + "\n")
while e < len(exons):
exon_from, exon_to, exon_phase, exon_genome_from, exon_genome_to = exons[e][0:5]
e += 1
ninserted_Cexons += 1
if outfile_exons:
outfile_exons.write( string.join( map(str, (entry.mPredictionId,
e, exon_from, exon_to, exon_phase,
0, 0, 0, 0,
0, 0,
0, 0, 0,
1,
exon_genome_from, exon_genome_to,
)), "\t") + "\n")
while r < len(ref_exons):
ref_from, ref_to, ref_phase, ref_genome_from, ref_genome_to = (ref_exons[r].mPeptideFrom,
ref_exons[r].mPeptideTo,
ref_exons[r].frame,
ref_exons[r].mGenomeFrom,
ref_exons[r].mGenomeTo)
ndeleted_Cexons += 1
ref_genome_from -= ref_exons_offset
ref_genome_to -= ref_exons_offset
r += 1
if outfile_exons:
outfile_exons.write( string.join( map(str, (entry.mPredictionId,
0, 0, 0, 0,
r, ref_from, ref_to, ref_phase,
0, 0,
0, 0, 0,
0,
0, 0,
)), "\t") + "\n")
else:
if options.write_notfound:
this_e = 0
## use prediction's identity/similarity for exons.
## This will still then flag stop-codons in later analysis
percent_identity = entry.mPercentIdentity
percent_similarity = entry.mPercentSimilarity
for exon in exons:
this_e += 1
exon_from, exon_to, exon_phase, exon_genome_from, exon_genome_to, exon_ali = exon[0:6]
if genomic_fragment:
nintrons, nframeshifts, ngaps, nsplits, nstopcodons, disruptions = Genomics.CountGeneFeatures( exon_genome_from - entry.mSbjctGenomeFrom,
exon_ali,
genomic_fragment )
outfile_exons.write( string.join( map(str, (entry.mPredictionId,
this_e, exon_from, exon_to, exon_phase,
0, 0, 0, 0,
percent_identity, percent_similarity,
nframeshifts, ngaps, nstopcodons,
1,
exon_genome_from, exon_genome_to,
)), "\t") + "\n")
options.stdout.write( "\t".join(map(str,
(entry.mPredictionId,
exons_num_exons,
dubious_exons,
exons_boundaries_sum,
exons_boundaries_max,
nidentical_exons,
ninserted_exons, ndeleted_exons,
ninserted_introns, ndeleted_introns,
truncated_Nterminal_exon, truncated_Cterminal_exon,
ndeleted_Nexons, ndeleted_Cexons,
ninserted_Nexons, ninserted_Cexons))) + "\n" )
def pslMap( options ):
"""thread psl alignments using intervals.
"""
if options.format == "gtf":
use_copy = False
else:
use_copy = True
ninput, noutput, ndiscarded, nskipped, nskipped_small_queries = 0, 0, 0, 0, 0
min_length = options.min_aligned
for match, qx, tx in iterator_psl_intervals( options ):
map_query2target = match.getMapQuery2Target()
ninput += 1
## if no filter on qx or tx, use full segment
if qx == None:
qx = [ (match.mQueryFrom,match.mQueryTo,0) ]
elif tx == None:
tx = [ (match.mSbjctFrom,match.mSbjctTo,0) ]
## if no overlap: return
if not qx or not tx:
nskipped += 1
continue
for query in qx:
qstart, qend, qval = query
# skip elements that are too small
if qend - qstart < min_length:
E.debug( "query too small - skipped at %s:%i-%i" % (match.mQueryId, qstart, qend) )
nskipped_small_queries += 1
continue
E.debug( "working on query %s:%i-%i" % (match.mQueryId, qstart, qend) )
mqstart, mqend = ( map_query2target.mapRowToCol(qstart,
alignlib.RIGHT),
map_query2target.mapRowToCol(qend,
alignlib.LEFT) )
if match.strand == "-":
qstart, qend = match.mQueryLength - qend, match.mQueryLength - qstart
for target in tx:
tstart, tend, tval = target
if tstart >= mqend or tend <= mqstart: continue
if tend - tstart < min_length: continue
new = alignlib.makeAlignmentBlocks()
if use_copy:
# do copy with range filter
if options.loglevel >= 3:
mtstart, mtend = map_query2target.mapColToRow(tstart), map_query2target.mapColToRow(tend)
E.debug( "query: %i-%i (len=%i)-> %i-%i(len=%i); target: %i-%i (len=%i)-> %i-%i (len=%i)" % \
(qstart, qend,
qend - qstart,
mqstart, mqend,
mqend - mqstart,
tstart, tend,
tend - tstart,
mtstart, mtend,
mtend - mtstart ) )
alignlib.copyAlignment(
new,
map_query2target,
qstart, qend,
tstart, tend )
else:
# do copy with alignment filter
map_query = qval
if map_query:
tmp = alignlib.makeAlignmentBlocks()
alignlib.copyAlignment( tmp, map_query2target, map_query, alignlib.RR )
if options.loglevel >= 5:
options.stdlog.write( "######## mapping query ###########\n" )
options.stdlog.write( "# %s\n" % str(alignlib.AlignmentFormatEmissions( map_query2target ) ))
options.stdlog.write( "# %s\n" % str(alignlib.AlignmentFormatEmissions( map_query ) ))
options.stdlog.write( "# %s\n" % str(alignlib.AlignmentFormatEmissions( tmp ) ))
else:
tmp = map_query2target
map_target = tval
if map_target:
new = alignlib.makeAlignmentBlocks()
alignlib.copyAlignment( new, tmp, map_target, alignlib.CR )
if options.loglevel >= 5:
options.stdlog.write( "######## mapping target ###########\n" )
options.stdlog.write( "# before: %s\n" % str(alignlib.AlignmentFormatEmissions( tmp ) ))
options.stdlog.write( "# map : %s\n" % str(alignlib.AlignmentFormatEmissions( map_target ) ))
options.stdlog.write( "# after : %s\n" % str(alignlib.AlignmentFormatEmissions( new ) ))
else:
new = tmp
if options.loglevel >= 4:
E.debug("putative match with intervals: %s and %s: %i-%i" % \
(str(query), str(target), qstart, qend ))
if options.loglevel >= 5:
E.debug( "input : %s" % str(alignlib.AlignmentFormatEmissions( map_query2target ) ))
E.debug( "final : %s" % str(alignlib.AlignmentFormatEmissions( new ) ) )
if new.getLength() > 0:
n = match.copy()
n.fromMap( new, use_strand = True )
E.info( "match : %s" % (str(n)))
if new.getNumAligned() > options.min_aligned:
n = match.copy()
n.fromMap( new, use_strand = True )
options.stdout.write( str(n) + "\n" )
noutput += 1
else:
ndiscarded += 1
E.info( "map: ninput=%i, noutput=%i, nskipped=%i, ndiscarded=%i, nsmall_queries=%i" % \
(ninput, noutput, nskipped, ndiscarded, nskipped_small_queries) )