def covfilter(args):
"""
%prog covfilter blastfile fastafile
Fastafile is used to get the sizes of the queries. Two filters can be
applied, the id% and cov%.
"""
from jcvi.algorithms.supermap import supermap
from jcvi.utils.range import range_union
allowed_iterby = ("query", "query_sbjct")
p = OptionParser(covfilter.__doc__)
p.set_align(pctid=95, pctcov=50)
p.add_option("--scov",
default=False,
action="store_true",
help="Subject coverage instead of query [default: %default]")
p.add_option("--supermap",
action="store_true",
help="Use supermap instead of union")
p.add_option("--ids",
dest="ids",
default=None,
help="Print out the ids that satisfy [default: %default]")
p.add_option("--list",
dest="list",
default=False,
action="store_true",
help="List the id% and cov% per gene [default: %default]")
p.add_option(
"--iterby",
dest="iterby",
default="query",
choices=allowed_iterby,
help="Choose how to iterate through BLAST [default: %default]")
p.set_outfile(outfile=None)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
blastfile, fastafile = args
pctid = opts.pctid
pctcov = opts.pctcov
union = not opts.supermap
scov = opts.scov
sz = Sizes(fastafile)
sizes = sz.mapping
iterby = opts.iterby
qspair = iterby == "query_sbjct"
if not union:
querysupermap = blastfile + ".query.supermap"
if not op.exists(querysupermap):
supermap(blastfile, filter="query")
blastfile = querysupermap
assert op.exists(blastfile)
covered = 0
mismatches = 0
gaps = 0
alignlen = 0
queries = set()
valid = set()
blast = BlastSlow(blastfile)
iterator = blast.iter_hits_pair if qspair else blast.iter_hits
covidstore = {}
for query, blines in iterator():
blines = list(blines)
queries.add(query)
# per gene report
this_covered = 0
this_alignlen = 0
this_mismatches = 0
this_gaps = 0
this_identity = 0
ranges = []
for b in blines:
if scov:
s, start, stop = b.subject, b.sstart, b.sstop
else:
s, start, stop = b.query, b.qstart, b.qstop
cov_id = s
if b.pctid < pctid:
continue
if start > stop:
start, stop = stop, start
this_covered += stop - start + 1
this_alignlen += b.hitlen
this_mismatches += b.nmismatch
this_gaps += b.ngaps
ranges.append(("1", start, stop))
if ranges:
this_identity = 100. - (this_mismatches +
this_gaps) * 100. / this_alignlen
if union:
this_covered = range_union(ranges)
this_coverage = this_covered * 100. / sizes[cov_id]
covidstore[query] = (this_identity, this_coverage)
if this_identity >= pctid and this_coverage >= pctcov:
valid.add(query)
covered += this_covered
mismatches += this_mismatches
gaps += this_gaps
alignlen += this_alignlen
if opts.list:
if qspair:
allpairs = defaultdict(list)
for (q, s) in covidstore:
allpairs[q].append((q, s))
allpairs[s].append((q, s))
for id, size in sz.iter_sizes():
if id not in allpairs:
print "\t".join((id, "na", "0", "0"))
else:
for qs in allpairs[id]:
this_identity, this_coverage = covidstore[qs]
print "{0}\t{1:.1f}\t{2:.1f}".format(
"\t".join(qs), this_identity, this_coverage)
else:
for query, size in sz.iter_sizes():
this_identity, this_coverage = covidstore.get(query, (0, 0))
print "{0}\t{1:.1f}\t{2:.1f}".format(query, this_identity,
this_coverage)
mapped_count = len(queries)
valid_count = len(valid)
cutoff_message = "(id={0.pctid}% cov={0.pctcov}%)".format(opts)
m = "Identity: {0} mismatches, {1} gaps, {2} alignlen\n".\
format(mismatches, gaps, alignlen)
total = len(sizes.keys())
m += "Total mapped: {0} ({1:.1f}% of {2})\n".\
format(mapped_count, mapped_count * 100. / total, total)
m += "Total valid {0}: {1} ({2:.1f}% of {3})\n".\
format(cutoff_message, valid_count, valid_count * 100. / total, total)
m += "Average id = {0:.2f}%\n".\
format(100 - (mismatches + gaps) * 100. / alignlen)
queries_combined = sz.totalsize
m += "Coverage: {0} covered, {1} total\n".\
format(covered, queries_combined)
m += "Average coverage = {0:.2f}%".\
format(covered * 100. / queries_combined)
logfile = blastfile + ".covfilter.log"
fw = open(logfile, "w")
for f in (sys.stderr, fw):
print >> f, m
fw.close()
if opts.ids:
filename = opts.ids
fw = must_open(filename, "w")
for id in valid:
print >> fw, id
logging.debug("Queries beyond cutoffs {0} written to `{1}`.".\
format(cutoff_message, filename))
outfile = opts.outfile
if not outfile:
return
fw = must_open(outfile, "w")
blast = Blast(blastfile)
for b in blast:
query = (b.query, b.subject) if qspair else b.query
if query in valid:
print >> fw, b
def covfilter(args):
"""
%prog covfilter blastfile fastafile
Fastafile is used to get the sizes of the queries. Two filters can be
applied, the id% and cov%.
"""
p = OptionParser(covfilter.__doc__)
p.add_option("--pctid", dest="pctid", default=90, type="int",
help="Percentage identity cutoff [default: %default]")
p.add_option("--pctcov", dest="pctcov", default=50, type="int",
help="Percentage identity cutoff [default: %default]")
p.add_option("--ids", dest="ids", default=None,
help="Print out the ids that satisfy [default: %default]")
p.add_option("--list", dest="list", default=False, action="store_true",
help="List the id% and cov% per gene [default: %default]")
set_outfile(p, outfile=None)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
from jcvi.algorithms.supermap import supermap
blastfile, fastafile = args
sizes = Sizes(fastafile).mapping
querysupermap = blastfile + ".query.supermap"
if not op.exists(querysupermap):
supermap(blastfile, filter="query")
blastfile = querysupermap
assert op.exists(blastfile)
covered = 0
mismatches = 0
gaps = 0
alignlen = 0
queries = set()
valid = set()
blast = BlastSlow(querysupermap)
for query, blines in blast.iter_hits():
blines = list(blines)
queries.add(query)
# per gene report
this_covered = 0
this_alignlen = 0
this_mismatches = 0
this_gaps = 0
for b in blines:
this_covered += abs(b.qstart - b.qstop + 1)
this_alignlen += b.hitlen
this_mismatches += b.nmismatch
this_gaps += b.ngaps
this_identity = 100. - (this_mismatches + this_gaps) * 100. / this_alignlen
this_coverage = this_covered * 100. / sizes[query]
if opts.list:
print "{0}\t{1:.1f}\t{2:.1f}".format(query, this_identity, this_coverage)
if this_identity >= opts.pctid and this_coverage >= opts.pctcov:
valid.add(query)
covered += this_covered
mismatches += this_mismatches
gaps += this_gaps
alignlen += this_alignlen
mapped_count = len(queries)
valid_count = len(valid)
cutoff_message = "(id={0.pctid}% cov={0.pctcov}%)".format(opts)
print >> sys.stderr, "Identity: {0} mismatches, {1} gaps, {2} alignlen".\
format(mismatches, gaps, alignlen)
total = len(sizes.keys())
print >> sys.stderr, "Total mapped: {0} ({1:.1f}% of {2})".\
format(mapped_count, mapped_count * 100. / total, total)
print >> sys.stderr, "Total valid {0}: {1} ({2:.1f}% of {3})".\
format(cutoff_message, valid_count, valid_count * 100. / total, total)
print >> sys.stderr, "Average id = {0:.2f}%".\
format(100 - (mismatches + gaps) * 100. / alignlen)
queries_combined = sum(sizes[x] for x in queries)
print >> sys.stderr, "Coverage: {0} covered, {1} total".\
format(covered, queries_combined)
print >> sys.stderr, "Average coverage = {0:.2f}%".\
format(covered * 100. / queries_combined)
if opts.ids:
filename = opts.ids
fw = must_open(filename, "w")
for id in valid:
print >> fw, id
logging.debug("Queries beyond cutoffs {0} written to `{1}`.".\
format(cutoff_message, filename))
outfile = opts.outfile
if not outfile:
return
fp = open(blastfile)
fw = must_open(outfile, "w")
blast = Blast(blastfile)
for b in blast.iter_line():
if b.query in valid:
print >> fw, b
def covfilter(args):
"""
%prog covfilter blastfile fastafile
Fastafile is used to get the sizes of the queries. Two filters can be
applied, the id% and cov%.
"""
from jcvi.algorithms.supermap import supermap
from jcvi.utils.range import range_union
allowed_iterby = ("query", "query_sbjct")
p = OptionParser(covfilter.__doc__)
p.set_align(pctid=95, pctcov=50)
p.add_option("--scov", default=False, action="store_true",
help="Subject coverage instead of query [default: %default]")
p.add_option("--supermap", action="store_true",
help="Use supermap instead of union")
p.add_option("--ids", dest="ids", default=None,
help="Print out the ids that satisfy [default: %default]")
p.add_option("--list", dest="list", default=False, action="store_true",
help="List the id% and cov% per gene [default: %default]")
p.add_option("--iterby", dest="iterby", default="query", choices=allowed_iterby,
help="Choose how to iterate through BLAST [default: %default]")
p.set_outfile(outfile=None)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
blastfile, fastafile = args
pctid = opts.pctid
pctcov = opts.pctcov
union = not opts.supermap
scov = opts.scov
sz = Sizes(fastafile)
sizes = sz.mapping
iterby = opts.iterby
qspair = iterby == "query_sbjct"
if not union:
querysupermap = blastfile + ".query.supermap"
if not op.exists(querysupermap):
supermap(blastfile, filter="query")
blastfile = querysupermap
assert op.exists(blastfile)
covered = 0
mismatches = 0
gaps = 0
alignlen = 0
queries = set()
valid = set()
blast = BlastSlow(blastfile)
iterator = blast.iter_hits_pair if qspair else blast.iter_hits
covidstore = {}
for query, blines in iterator():
blines = list(blines)
queries.add(query)
# per gene report
this_covered = 0
this_alignlen = 0
this_mismatches = 0
this_gaps = 0
this_identity = 0
ranges = []
for b in blines:
if scov:
s, start, stop = b.subject, b.sstart, b.sstop
else:
s, start, stop = b.query, b.qstart, b.qstop
cov_id = s
if b.pctid < pctid:
continue
if start > stop:
start, stop = stop, start
this_covered += stop - start + 1
this_alignlen += b.hitlen
this_mismatches += b.nmismatch
this_gaps += b.ngaps
ranges.append(("1", start, stop))
if ranges:
this_identity = 100. - (this_mismatches + this_gaps) * 100. / this_alignlen
if union:
this_covered = range_union(ranges)
this_coverage = this_covered * 100. / sizes[cov_id]
covidstore[query] = (this_identity, this_coverage)
if this_identity >= pctid and this_coverage >= pctcov:
valid.add(query)
covered += this_covered
mismatches += this_mismatches
gaps += this_gaps
alignlen += this_alignlen
if opts.list:
if qspair:
allpairs = defaultdict(list)
for (q, s) in covidstore:
allpairs[q].append((q, s))
allpairs[s].append((q, s))
for id, size in sz.iter_sizes():
if id not in allpairs:
print "\t".join((id, "na", "0", "0"))
else:
for qs in allpairs[id]:
this_identity, this_coverage = covidstore[qs]
print "{0}\t{1:.1f}\t{2:.1f}".format("\t".join(qs), this_identity, this_coverage)
else:
for query, size in sz.iter_sizes():
this_identity, this_coverage = covidstore.get(query, (0, 0))
print "{0}\t{1:.1f}\t{2:.1f}".format(query, this_identity, this_coverage)
mapped_count = len(queries)
valid_count = len(valid)
cutoff_message = "(id={0.pctid}% cov={0.pctcov}%)".format(opts)
m = "Identity: {0} mismatches, {1} gaps, {2} alignlen\n".\
format(mismatches, gaps, alignlen)
total = len(sizes.keys())
m += "Total mapped: {0} ({1:.1f}% of {2})\n".\
format(mapped_count, mapped_count * 100. / total, total)
m += "Total valid {0}: {1} ({2:.1f}% of {3})\n".\
format(cutoff_message, valid_count, valid_count * 100. / total, total)
m += "Average id = {0:.2f}%\n".\
format(100 - (mismatches + gaps) * 100. / alignlen)
queries_combined = sz.totalsize
m += "Coverage: {0} covered, {1} total\n".\
format(covered, queries_combined)
m += "Average coverage = {0:.2f}%".\
format(covered * 100. / queries_combined)
logfile = blastfile + ".covfilter.log"
fw = open(logfile, "w")
for f in (sys.stderr, fw):
print >> f, m
fw.close()
if opts.ids:
filename = opts.ids
fw = must_open(filename, "w")
for id in valid:
print >> fw, id
logging.debug("Queries beyond cutoffs {0} written to `{1}`.".\
format(cutoff_message, filename))
outfile = opts.outfile
if not outfile:
return
fw = must_open(outfile, "w")
blast = Blast(blastfile)
for b in blast:
query = (b.query, b.subject) if qspair else b.query
if query in valid:
print >> fw, b
def rnaseq(args):
"""
%prog rnaseq blastfile ref.fasta
Evaluate de-novo RNA-seq assembly against a reference gene set (same or
closely related organism). Ideally blatfile needs to be supermap'd.
Following metric is used (Martin et al. 2010, Rnnotator paper):
Accuracy: % of contigs share >=95% identity with ref genome (TODO)
Completeness: % of ref genes covered by contigs to >=80% of their lengths
Contiguity: % of ref genes covered by a *single* contig >=80% of lengths
Chimer: % of contigs that contain two or more annotated genes >= 50bp
"""
from jcvi.algorithms.supermap import supermap
p = OptionParser(rnaseq.__doc__)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(p.print_help())
blastfile, reffasta = args
sizes = Sizes(reffasta).mapping
known_genes = len(sizes)
querysupermap = blastfile + ".query.supermap"
refsupermap = blastfile + ".ref.supermap"
if not op.exists(querysupermap):
supermap(blastfile, filter="query")
if not op.exists(refsupermap):
supermap(blastfile, filter="ref")
blast = Blast(querysupermap)
chimers = 0
goodctg80 = set()
goodctg50 = set()
for ctg, hits in blast.iter_hits():
bps = defaultdict(int)
for x in hits:
bps[x.subject] += abs(x.sstop - x.sstart) + 1
valid_hits = bps.items()
for vh, length in valid_hits:
rsize = sizes[vh]
ratio = length * 100. / rsize
if ratio >= 80:
goodctg80.add(ctg)
if ratio >= 50:
goodctg50.add(ctg)
# Chimer
if len(valid_hits) > 1:
chimers += 1
blast = Blast(refsupermap)
goodref80 = set()
goodref50 = set()
bps = defaultdict(int)
for x in blast.iter_line():
bps[x.subject] += abs(x.sstop - x.sstart) + 1
for vh, length in bps.items():
rsize = sizes[vh]
ratio = length * 100. / rsize
if ratio >= 80:
goodref80.add(vh)
if ratio >= 50:
goodref50.add(vh)
print >> sys.stderr, "Reference set: `{0}`, # of transcripts {1}".\
format(reffasta, known_genes)
print >> sys.stderr, "A total of {0} contigs map to 80% of a reference"\
" transcript".format(len(goodctg80))
print >> sys.stderr, "A total of {0} contigs map to 50% of a reference"\
" transcript".format(len(goodctg50))
print >> sys.stderr, "A total of {0} reference transcripts ({1:.1f}%) have 80% covered" \
.format(len(goodref80), len(goodref80) * 100. / known_genes)
def covfilter(args):
"""
%prog covfilter blastfile fastafile
Fastafile is used to get the sizes of the queries. Two filters can be
applied, the id% and cov%.
"""
p = OptionParser(covfilter.__doc__)
p.add_option("--pctid",
dest="pctid",
default=90,
type="int",
help="Percentage identity cutoff [default: %default]")
p.add_option("--pctcov",
dest="pctcov",
default=50,
type="int",
help="Percentage identity cutoff [default: %default]")
p.add_option("--ids",
dest="ids",
default=None,
help="Print out the ids that satisfy [default: %default]")
p.add_option("--list",
dest="list",
default=False,
action="store_true",
help="List the id% and cov% per gene [default: %default]")
set_outfile(p, outfile=None)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
from jcvi.algorithms.supermap import supermap
blastfile, fastafile = args
sizes = Sizes(fastafile).mapping
querysupermap = blastfile + ".query.supermap"
if not op.exists(querysupermap):
supermap(blastfile, filter="query")
blastfile = querysupermap
assert op.exists(blastfile)
covered = 0
mismatches = 0
gaps = 0
alignlen = 0
queries = set()
valid = set()
blast = BlastSlow(querysupermap)
for query, blines in blast.iter_hits():
blines = list(blines)
queries.add(query)
# per gene report
this_covered = 0
this_alignlen = 0
this_mismatches = 0
this_gaps = 0
for b in blines:
this_covered += abs(b.qstart - b.qstop + 1)
this_alignlen += b.hitlen
this_mismatches += b.nmismatch
this_gaps += b.ngaps
this_identity = 100. - (this_mismatches +
this_gaps) * 100. / this_alignlen
this_coverage = this_covered * 100. / sizes[query]
if opts.list:
print "{0}\t{1:.1f}\t{2:.1f}".format(query, this_identity,
this_coverage)
if this_identity >= opts.pctid and this_coverage >= opts.pctcov:
valid.add(query)
covered += this_covered
mismatches += this_mismatches
gaps += this_gaps
alignlen += this_alignlen
mapped_count = len(queries)
valid_count = len(valid)
cutoff_message = "(id={0.pctid}% cov={0.pctcov}%)".format(opts)
print >> sys.stderr, "Identity: {0} mismatches, {1} gaps, {2} alignlen".\
format(mismatches, gaps, alignlen)
total = len(sizes.keys())
print >> sys.stderr, "Total mapped: {0} ({1:.1f}% of {2})".\
format(mapped_count, mapped_count * 100. / total, total)
print >> sys.stderr, "Total valid {0}: {1} ({2:.1f}% of {3})".\
format(cutoff_message, valid_count, valid_count * 100. / total, total)
print >> sys.stderr, "Average id = {0:.2f}%".\
format(100 - (mismatches + gaps) * 100. / alignlen)
queries_combined = sum(sizes[x] for x in queries)
print >> sys.stderr, "Coverage: {0} covered, {1} total".\
format(covered, queries_combined)
print >> sys.stderr, "Average coverage = {0:.2f}%".\
format(covered * 100. / queries_combined)
if opts.ids:
filename = opts.ids
fw = must_open(filename, "w")
for id in valid:
print >> fw, id
logging.debug("Queries beyond cutoffs {0} written to `{1}`.".\
format(cutoff_message, filename))
outfile = opts.outfile
if not outfile:
return
fp = open(blastfile)
fw = must_open(outfile, "w")
blast = Blast(blastfile)
for b in blast.iter_line():
if b.query in valid:
print >> fw, b
def rnaseq(args):
"""
%prog rnaseq blastfile ref.fasta
Evaluate de-novo RNA-seq assembly against a reference gene set (same or
closely related organism). Ideally blatfile needs to be supermap'd.
Following metric is used (Martin et al. 2010, Rnnotator paper):
Accuracy: % of contigs share >=95% identity with ref genome (TODO)
Completeness: % of ref genes covered by contigs to >=80% of their lengths
Contiguity: % of ref genes covered by a *single* contig >=80% of lengths
Chimer: % of contigs that contain two or more annotated genes >= 50bp
"""
from jcvi.algorithms.supermap import supermap
p = OptionParser(rnaseq.__doc__)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(p.print_help())
blastfile, reffasta = args
sizes = Sizes(reffasta).mapping
known_genes = len(sizes)
querysupermap = blastfile + ".query.supermap"
refsupermap = blastfile + ".ref.supermap"
if not op.exists(querysupermap):
supermap(blastfile, filter="query")
if not op.exists(refsupermap):
supermap(blastfile, filter="ref")
blast = Blast(querysupermap)
chimers = 0
goodctg80 = set()
goodctg50 = set()
for ctg, hits in blast.iter_hits():
bps = defaultdict(int)
for x in hits:
bps[x.subject] += abs(x.sstop - x.sstart) + 1
valid_hits = bps.items()
for vh, length in valid_hits:
rsize = sizes[vh]
ratio = length * 100. / rsize
if ratio >= 80:
goodctg80.add(ctg)
if ratio >= 50:
goodctg50.add(ctg)
# Chimer
if len(valid_hits) > 1:
chimers += 1
blast = Blast(refsupermap)
goodref80 = set()
goodref50 = set()
bps = defaultdict(int)
for x in blast.iter_line():
bps[x.subject] += abs(x.sstop - x.sstart) + 1
for vh, length in bps.items():
rsize = sizes[vh]
ratio = length * 100. / rsize
if ratio >= 80:
goodref80.add(vh)
if ratio >= 50:
goodref50.add(vh)
print >> sys.stderr, "Reference set: `{0}`, # of transcripts {1}".\
format(reffasta, known_genes)
print >> sys.stderr, "A total of {0} contigs map to 80% of a reference"\
" transcript".format(len(goodctg80))
print >> sys.stderr, "A total of {0} contigs map to 50% of a reference"\
" transcript".format(len(goodctg50))
print >> sys.stderr, "A total of {0} reference transcripts ({1:.1f}%) have 80% covered" \
.format(len(goodref80), len(goodref80) * 100. / known_genes)