def prepare_synteny(tourfile, lastfile, odir, p, opts):
"""
Prepare synteny plots for movie().
"""
qbedfile, sbedfile = get_bed_filenames(lastfile, p, opts)
qbedfile = op.abspath(qbedfile)
sbedfile = op.abspath(sbedfile)
qbed = Bed(qbedfile, sorted=False)
contig_to_beds = dict(qbed.sub_beds())
# Create a separate directory for the subplots and movie
mkdir(odir, overwrite=True)
os.chdir(odir)
logging.debug("Change into subdir `{}`".format(odir))
# Make anchorsfile
anchorsfile = ".".join(op.basename(lastfile).split(".", 2)[:2]) \
+ ".anchors"
fw = open(anchorsfile, "w")
for b in Blast(lastfile):
print >> fw, "\t".join((gene_name(b.query), gene_name(b.subject),
str(int(b.score))))
fw.close()
# Symlink sbed
symlink(sbedfile, op.basename(sbedfile))
return anchorsfile, qbedfile, contig_to_beds
def prepare_synteny(tourfile, lastfile, odir, p, opts):
"""
Prepare synteny plots for movie().
"""
qbedfile, sbedfile = get_bed_filenames(lastfile, p, opts)
qbedfile = op.abspath(qbedfile)
sbedfile = op.abspath(sbedfile)
qbed = Bed(qbedfile, sorted=False)
contig_to_beds = dict(qbed.sub_beds())
# Create a separate directory for the subplots and movie
mkdir(odir, overwrite=True)
os.chdir(odir)
logging.debug("Change into subdir `{}`".format(odir))
# Make anchorsfile
anchorsfile = ".".join(op.basename(lastfile).split(".",
2)[:2]) + ".anchors"
fw = open(anchorsfile, "w")
for b in Blast(lastfile):
print >> fw, "\t".join(
(gene_name(b.query), gene_name(b.subject), str(int(b.score))))
fw.close()
# Symlink sbed
symlink(sbedfile, op.basename(sbedfile))
return anchorsfile, qbedfile, contig_to_beds
def iadhore(args):
"""
%prog iadhore athaliana.athaliana.last athaliana.bed
Wrap around iADHoRe.
"""
p = OptionParser(iadhore.__doc__)
opts, args = p.parse_args(args)
if len(args) < 2:
sys.exit(not p.print_help())
lastfile = args[0]
bedfiles = args[1:]
blast_table = "blast_table.txt"
fp = open(lastfile)
seen = set()
for row in fp:
c = BlastLine(row)
a, b = c.query, c.subject
a, b = gene_name(a), gene_name(b)
if a > b:
a, b = b, a
seen.add((a, b))
fw = open(blast_table, "w")
for a, b in seen:
print >> fw, "\t".join((a, b))
fw.close()
logging.debug("A total of {0} pairs written to `{1}`"\
.format(len(seen), blast_table))
fw = open("config.txt", "w")
for bedfile in bedfiles:
pf, stanza = write_lst(bedfile)
print >> fw, "genome={0}".format(pf)
for seqid, fname in stanza:
print >> fw, " ".join((seqid, fname))
print >> fw
print >> fw, "blast_table={0}".format(blast_table)
print >> fw, "cluster_type=colinear"
print >> fw, "tandem_gap=10"
print >> fw, "prob_cutoff=0.001"
print >> fw, "gap_size=20"
print >> fw, "cluster_gap=20"
print >> fw, "q_value=0.9"
print >> fw, "anchor_points=4"
print >> fw, "alignment_method=gg2"
print >> fw, "max_gaps_in_alignment=20"
print >> fw, "output_path=i-adhore_out"
print >> fw, "number_of_threads=4"
fw.close()
def iadhore(args):
"""
%prog iadhore athaliana.athaliana.last athaliana.bed
Wrap around iADHoRe.
"""
p = OptionParser(iadhore.__doc__)
opts, args = p.parse_args(args)
if len(args) < 2:
sys.exit(not p.print_help())
lastfile = args[0]
bedfiles = args[1:]
blast_table = "blast_table.txt"
fp = open(lastfile)
seen = set()
for row in fp:
c = BlastLine(row)
a, b = c.query, c.subject
a, b = gene_name(a), gene_name(b)
if a > b:
a, b = b, a
seen.add((a, b))
fw = open(blast_table, "w")
for a, b in seen:
print("\t".join((a, b)), file=fw)
fw.close()
logging.debug("A total of {0} pairs written to `{1}`"\
.format(len(seen), blast_table))
fw = open("config.txt", "w")
for bedfile in bedfiles:
pf, stanza = write_lst(bedfile)
print("genome={0}".format(pf), file=fw)
for seqid, fname in stanza:
print(" ".join((seqid, fname)), file=fw)
print(file=fw)
print("blast_table={0}".format(blast_table), file=fw)
print("cluster_type=colinear", file=fw)
print("tandem_gap=10", file=fw)
print("prob_cutoff=0.001", file=fw)
print("gap_size=20", file=fw)
print("cluster_gap=20", file=fw)
print("q_value=0.9", file=fw)
print("anchor_points=4", file=fw)
print("alignment_method=gg2", file=fw)
print("max_gaps_in_alignment=20", file=fw)
print("output_path=i-adhore_out", file=fw)
print("number_of_threads=4", file=fw)
fw.close()
def __init__(self, row, strip_names=False):
args = row.strip().split(",")
self.name = args[0]
self.yn_ks = self.get_float(args[1])
self.yn_ka = self.get_float(args[2])
self.ng_ks = self.get_float(args[3])
self.ng_ka = self.get_float(args[4])
self.ks = self.ng_ks
if ";" in self.name:
self.gene_a, self.gene_b = self.name.split(";")
if strip_names:
self.gene_a = gene_name(self.gene_a)
self.gene_b = gene_name(self.gene_b)
def __init__(self, row, strip_names=False):
args = row.strip().split(",")
self.name = args[0]
self.yn_ks = self.get_float(args[1])
self.yn_ka = self.get_float(args[2])
self.ng_ks = self.get_float(args[3])
self.ng_ka = self.get_float(args[4])
self.ks = self.ng_ks
if ";" in self.name:
self.gene_a, self.gene_b = self.name.split(";")
if strip_names:
self.gene_a = gene_name(self.gene_a)
self.gene_b = gene_name(self.gene_b)
def read_ks_file(ks_file, strip_names=False):
from jcvi.utils.cbook import gene_name
reader = csv.reader(open(ks_file, "rb"))
data = []
for row in reader:
if row[0] == "name": # header
continue
for i, a in enumerate(row):
if i == 0:
if strip_names:
row[i] = ";".join(gene_name(x) for x in row[i].split(";"))
continue
try:
row[i] = float(row[i])
except:
row[i] = -1
data.append(KsLine._make(row))
logging.debug('File `{0}` contains a total of {1} gene pairs'.\
format(ks_file, len(data)))
return data
def read_blast(blast_file, qorder, sorder, is_self=False, ostrip=True):
"""
read the blast and convert name into coordinates
"""
filtered_blast = []
seen = set()
bl = Blast(blast_file)
for b in bl:
query, subject = b.query, b.subject
if query == subject:
continue
if ostrip:
query, subject = gene_name(query), gene_name(subject)
if query not in qorder or subject not in sorder:
continue
qi, q = qorder[query]
si, s = sorder[subject]
if is_self:
# remove redundant a<->b to one side when doing self-self BLAST
if qi > si:
query, subject = subject, query
qi, si = si, qi
q, s = s, q
# Too close to diagonal! possible tandem repeats
if q.seqid == s.seqid and si - qi < 40:
continue
key = query, subject
if key in seen:
continue
seen.add(key)
b.qseqid, b.sseqid = q.seqid, s.seqid
b.qi, b.si = qi, si
b.query, b.subject = query, subject
filtered_blast.append(b)
logging.debug("A total of {0} BLAST imported from `{1}`.".\
format(len(filtered_blast), blast_file))
return filtered_blast
def read_blast(blast_file, qorder, sorder, is_self=False, ostrip=True):
"""
read the blast and convert name into coordinates
"""
filtered_blast = []
seen = set()
bl = Blast(blast_file)
for b in bl:
query, subject = b.query, b.subject
if query == subject:
continue
if ostrip:
query, subject = gene_name(query), gene_name(subject)
if query not in qorder or subject not in sorder:
continue
qi, q = qorder[query]
si, s = sorder[subject]
if is_self:
# remove redundant a<->b to one side when doing self-self BLAST
if qi > si:
query, subject = subject, query
qi, si = si, qi
q, s = s, q
# Too close to diagonal! possible tandem repeats
if q.seqid == s.seqid and si - qi < 40:
continue
key = query, subject
if key in seen:
continue
seen.add(key)
b.qseqid, b.sseqid = q.seqid, s.seqid
b.qi, b.si = qi, si
b.query, b.subject = query, subject
filtered_blast.append(b)
logging.debug("A total of {0} BLAST imported from `{1}`.".\
format(len(filtered_blast), blast_file))
return filtered_blast
def main(blast_file, cds_file, bed_file, N=3):
# get the sizes for the CDS first
f = Fasta(cds_file)
sizes = dict(f.itersizes())
# retrieve the locations
bed = Bed(bed_file).order
# filter the blast file
g = Grouper()
fp = open(blast_file)
for row in fp:
b = BlastLine(row)
query_len = sizes[b.query]
subject_len = sizes[b.subject]
if b.hitlen < min(query_len, subject_len) / 2:
continue
query, subject = gene_name(b.query), gene_name(b.subject)
qi, q = bed[query]
si, s = bed[subject]
if q.seqid == s.seqid and abs(qi - si) <= N:
g.join(query, subject)
# dump the grouper
ngenes, nfamilies = 0, 0
families = []
for group in sorted(g):
if len(group) >= 2:
print ",".join(sorted(group))
ngenes += len(group)
nfamilies += 1
families.append(sorted(group))
longest_family = max(families, key=lambda x: len(x))
# generate reports
print >> sys.stderr, "Proximal paralogues (dist=%d):" % N
print >> sys.stderr, "Total %d genes in %d families" % (ngenes, nfamilies)
print >> sys.stderr, "Longest families (%d): %s" % (
len(longest_family), ",".join(longest_family))
def main(blast_file, cds_file, bed_file, N=3):
# get the sizes for the CDS first
f = Fasta(cds_file)
sizes = dict(f.itersizes())
# retrieve the locations
bed = Bed(bed_file).order
# filter the blast file
g = Grouper()
fp = open(blast_file)
for row in fp:
b = BlastLine(row)
query_len = sizes[b.query]
subject_len = sizes[b.subject]
if b.hitlen < min(query_len, subject_len) / 2:
continue
query, subject = gene_name(b.query), gene_name(b.subject)
qi, q = bed[query]
si, s = bed[subject]
if q.seqid == s.seqid and abs(qi - si) <= N:
g.join(query, subject)
# dump the grouper
ngenes, nfamilies = 0, 0
families = []
for group in sorted(g):
if len(group) >= 2:
print ",".join(sorted(group))
ngenes += len(group)
nfamilies += 1
families.append(sorted(group))
longest_family = max(families, key=lambda x: len(x))
# generate reports
print >>sys.stderr, "Proximal paralogues (dist=%d):" % N
print >>sys.stderr, "Total %d genes in %d families" % (ngenes, nfamilies)
print >>sys.stderr, "Longest families (%d): %s" % (len(longest_family),
",".join(longest_family))
def read_blast(blast_file, qorder, sorder, is_self=False, ostrip=True):
"""
read the blast and convert name into coordinates
"""
fp = open(blast_file)
filtered_blast = []
seen = set()
for row in fp:
b = BlastLine(row)
query, subject = b.query, b.subject
if query == subject:
continue
if ostrip:
query, subject = gene_name(query), gene_name(subject)
if query not in qorder or subject not in sorder:
continue
qi, q = qorder[query]
si, s = sorder[subject]
if is_self and qi > si:
# remove redundant a<->b to one side when doing self-self BLAST
query, subject = subject, query
qi, si = si, qi
q, s = s, q
key = query, subject
if key in seen:
continue
seen.add(key)
b.qseqid, b.sseqid = q.seqid, s.seqid
b.qi, b.si = qi, si
b.query, b.subject = query, subject
filtered_blast.append(b)
logging.debug("A total of {0} BLAST imported from `{1}`.".\
format(len(filtered_blast), blast_file))
return filtered_blast
def read_blast(blast_file, qorder, sorder, is_self=False, ostrip=True):
"""
read the blast and convert name into coordinates
"""
fp = open(blast_file)
filtered_blast = []
seen = set()
for row in fp:
b = BlastLine(row)
query, subject = b.query, b.subject
if query == subject:
continue
if ostrip:
query, subject = gene_name(query), gene_name(subject)
if query not in qorder or subject not in sorder:
continue
qi, q = qorder[query]
si, s = sorder[subject]
if is_self and qi > si:
# remove redundant a<->b to one side when doing self-self BLAST
query, subject = subject, query
qi, si = si, qi
q, s = s, q
key = query, subject
if key in seen:
continue
seen.add(key)
b.qseqid, b.sseqid = q.seqid, s.seqid
b.qi, b.si = qi, si
b.query, b.subject = query, subject
filtered_blast.append(b)
logging.debug("A total of {0} BLAST imported from `{1}`.".\
format(len(filtered_blast), blast_file))
return filtered_blast
def some(args):
"""
%prog some bedfile idsfile > newbedfile
Retrieve a subset of bed features given a list of ids.
"""
from jcvi.formats.base import SetFile
from jcvi.utils.cbook import gene_name
p = OptionParser(some.__doc__)
p.add_option("-v",
dest="inverse",
default=False,
action="store_true",
help="Get the inverse, like grep -v [default: %default]")
p.set_outfile()
p.set_stripnames()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
bedfile, idsfile = args
inverse = opts.inverse
ostrip = opts.strip_names
fw = must_open(opts.outfile, "w")
ids = SetFile(idsfile)
if ostrip:
ids = set(gene_name(x) for x in ids)
bed = Bed(bedfile)
ntotal = nkeep = 0
for b in bed:
ntotal += 1
keep = b.accn in ids
if inverse:
keep = not keep
if keep:
nkeep += 1
print >> fw, b
fw.close()
logging.debug("Stats: {0} features kept.".\
format(percentage(nkeep, ntotal)))
def some(args):
"""
%prog some bedfile idsfile > newbedfile
Retrieve a subset of bed features given a list of ids.
"""
from jcvi.formats.base import SetFile
from jcvi.utils.cbook import gene_name
p = OptionParser(some.__doc__)
p.add_option("-v", dest="inverse", default=False, action="store_true",
help="Get the inverse, like grep -v [default: %default]")
p.set_outfile()
p.set_stripnames()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
bedfile, idsfile = args
inverse = opts.inverse
ostrip = opts.strip_names
fw = must_open(opts.outfile, "w")
ids = SetFile(idsfile)
if ostrip:
ids = set(gene_name(x) for x in ids)
bed = Bed(bedfile)
ntotal = nkeep = 0
for b in bed:
ntotal += 1
keep = b.accn in ids
if inverse:
keep = not keep
if keep:
nkeep += 1
print >> fw, b
fw.close()
logging.debug("Stats: {0} features kept.".\
format(percentage(nkeep, ntotal)))
def anchorline(self):
return "\t".join((gene_name(self.gene_a), gene_name(self.gene_b),
"{:.3f}".format(self.ks)))
def benchmark(args):
"""
%prog benchmark at bedfile
Compare SynFind, MCScanx, iADHoRe and OrthoFinder against the truth.
"""
p = OptionParser(benchmark.__doc__)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
pf, bedfile = args
truth = pf + ".truth"
synfind = pf + ".synfind"
mcscanx = pf + ".mcscanx"
iadhore = pf + ".iadhore"
orthofinder = pf + ".orthofinder"
pivots = set([x.accn for x in Bed(bedfile)])
fp = open(truth)
truth = set()
for row in fp:
a, b = row.strip().split("\t")[:2]
pivots.add(a)
truth.add(tuple(sorted((a, b))))
logging.debug("Truth: {0} pairs".format(len(truth)))
fp = open(synfind)
benchmarkfile = pf + ".benchmark"
fw = must_open(benchmarkfile, "w")
synfind = set()
for row in fp:
atoms = row.strip().split("\t")
query, hit, tag = atoms[:3]
if tag != "S":
continue
synfind.add(tuple(sorted((query, hit))))
calc_sensitivity_specificity(synfind, truth, "SynFind", fw)
fp = open(mcscanx)
mcscanx = set()
for row in fp:
if row[0] == '#':
continue
atoms = row.strip().split(":")[1].split()
query, hit = atoms[:2]
mcscanx.add(tuple(sorted((query, hit))))
calc_sensitivity_specificity(mcscanx, truth, "MCScanX", fw)
fp = open(iadhore)
iadhore = set()
next(fp)
for row in fp:
atoms = row.strip().split("\t")
query, hit = atoms[3:5]
iadhore.add(tuple(sorted((query, hit))))
calc_sensitivity_specificity(iadhore, truth, "iADHoRe", fw)
fp = open(orthofinder)
orthofinder = set()
next(fp)
for row in fp:
row = row.replace('"', "")
atoms = row.replace(",", " ").split()
genes = [x.strip() for x in atoms if not x.startswith("OG")]
genes = [gene_name(x) for x in genes]
pps = [x for x in genes if x in pivots]
for p in pps:
for g in genes:
if p == g:
continue
orthofinder.add(tuple(sorted((p, g))))
#write_pairs(orthofinder, "orthofinder.pairs")
calc_sensitivity_specificity(orthofinder, truth, "OrthoFinder", fw)
fw.close()
def tandem_main(blast_file, cds_file, bed_file, N=3, P=50, is_self=True, \
evalue=.01, strip_name=".", ofile=sys.stderr, genefam=False):
if genefam:
N = 1e5
# get the sizes for the CDS first
f = Fasta(cds_file)
sizes = dict(f.itersizes())
# retrieve the locations
bed = Bed(bed_file)
order = bed.order
if is_self:
# filter the blast file
g = Grouper()
fp = open(blast_file)
for row in fp:
b = BlastLine(row)
query_len = sizes[b.query]
subject_len = sizes[b.subject]
if b.hitlen < min(query_len, subject_len)*P/100.:
continue
query = gene_name(b.query, strip_name)
subject = gene_name(b.subject, strip_name)
qi, q = order[query]
si, s = order[subject]
if abs(qi - si) <= N and b.evalue <= evalue:
if genefam:
g.join(query, subject)
elif q.seqid == s.seqid:
g.join(query, subject)
else:
homologs = Grouper()
fp = open(blast_file)
for row in fp:
b = BlastLine(row)
query_len = sizes[b.query]
subject_len = sizes[b.subject]
if b.hitlen < min(query_len, subject_len)*P/100.:
continue
if b.evalue > evalue:
continue
query = gene_name(b.query, strip_name)
subject = gene_name(b.subject, strip_name)
homologs.join(query, subject)
if genefam:
g = homologs
else:
g = Grouper()
for i, atom in enumerate(bed):
for x in range(1, N+1):
if all([i-x >= 0, bed[i-x].seqid == atom.seqid, \
homologs.joined(bed[i-x].accn, atom.accn)]):
leni = sizes[bed[i].accn]
lenx = sizes[bed[i-x].accn]
if abs(leni - lenx) > max(leni, lenx)*(1-P/100.):
continue
g.join(bed[i-x].accn, atom.accn)
# dump the grouper
fw = must_open(ofile, "w")
ngenes, nfamilies = 0, 0
families = []
for group in sorted(g):
if len(group) >= 2:
print >>fw, ",".join(sorted(group))
ngenes += len(group)
nfamilies += 1
families.append(sorted(group))
longest_family = max(families, key=lambda x: len(x))
# generate reports
print >>sys.stderr, "Proximal paralogues (dist=%d):" % N
print >>sys.stderr, "Total %d genes in %d families" % (ngenes, nfamilies)
print >>sys.stderr, "Longest families (%d): %s" % (len(longest_family),
",".join(longest_family))
return families
def test_gene_name(input, output):
from jcvi.utils.cbook import gene_name
assert gene_name(input) == output
def loss(args):
"""
%prog loss a.b.i1.blocks [a.b-genomic.blast]
Extract likely gene loss candidates between genome a and b.
"""
p = OptionParser(loss.__doc__)
p.add_option("--bed", default=False, action="store_true",
help="Genomic BLAST is in bed format [default: %default]")
p.add_option("--gdist", default=20, type="int",
help="Gene distance [default: %default]")
p.add_option("--bdist", default=20000, type="int",
help="Base pair distance [default: %default]")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) not in (1, 2):
sys.exit(not p.print_help())
blocksfile = args[0]
emptyblast = (len(args) == 1)
if emptyblast:
genomicblast = "empty.blast"
sh("touch {0}".format(genomicblast))
else:
genomicblast = args[1]
gdist, bdist = opts.gdist, opts.bdist
qbed, sbed, qorder, sorder, is_self = check_beds(blocksfile, p, opts)
blocks = []
fp = open(blocksfile)
genetrack = {}
proxytrack = {}
for row in fp:
a, b = row.split()
genetrack[a] = b
blocks.append((a, b))
data = []
for key, rows in groupby(blocks, key=lambda x: x[-1]):
rows = list(rows)
data.append((key, rows))
imax = len(data) - 1
for i, (key, rows) in enumerate(data):
if i == 0 or i == imax:
continue
if key != '.':
continue
before, br = data[i - 1]
after, ar = data[i + 1]
bi, bx = sorder[before]
ai, ax = sorder[after]
dist = abs(bi - ai)
if bx.seqid != ax.seqid or dist > gdist:
continue
start, end = range_minmax(((bx.start, bx.end), (ax.start, ax.end)))
start, end = max(start - bdist, 1), end + bdist
proxy = (bx.seqid, start, end)
for a, b in rows:
proxytrack[a] = proxy
tags = {}
if opts.bed:
bed = Bed(genomicblast, sorted=False)
key = lambda x: gene_name(x.accn.rsplit(".", 1)[0])
for query, bb in groupby(bed, key=key):
bb = list(bb)
if query not in proxytrack:
continue
proxy = proxytrack[query]
tag = "NS"
best_b = bb[0]
for b in bb:
hsp = (b.seqid, b.start, b.end)
if range_overlap(proxy, hsp):
tag = "S"
best_b = b
break
hsp = (best_b.seqid, best_b.start, best_b.end)
proxytrack[query] = hsp
tags[query] = tag
else:
blast = Blast(genomicblast)
for query, bb in blast.iter_hits():
bb = list(bb)
query = gene_name(query)
if query not in proxytrack:
continue
proxy = proxytrack[query]
tag = "NS"
best_b = bb[0]
for b in bb:
hsp = (b.subject, b.sstart, b.sstop)
if range_overlap(proxy, hsp):
tag = "S"
best_b = b
break
hsp = (best_b.subject, best_b.sstart, best_b.sstop)
proxytrack[query] = hsp
tags[query] = tag
for b in qbed:
accn = b.accn
target_region = genetrack[accn]
if accn in proxytrack:
target_region = region_str(proxytrack[accn])
if accn in tags:
ptag = "[{0}]".format(tags[accn])
else:
ptag = "[NF]"
target_region = ptag + target_region
print "\t".join((b.seqid, accn, target_region))
if emptyblast:
sh("rm -f {0}".format(genomicblast))
def pastegenes(args):
"""
%prog pastegenes coverage.list old.genes.bed new.genes.bed old.assembly
Paste in zero or low coverage genes. For a set of neighboring genes
missing, add the whole cassette as unplaced scaffolds. For singletons the
program will try to make a patch.
"""
from jcvi.formats.base import DictFile
from jcvi.utils.cbook import gene_name
p = OptionParser(pastegenes.__doc__)
p.add_option(
"--cutoff",
default=90,
type="int",
help="Coverage cutoff to call gene missing",
)
p.add_option(
"--flank",
default=2000,
type="int",
help="Get the seq of size on two ends",
)
p.add_option(
"--maxsize",
default=50000,
type="int",
help="Maximum size of patchers to be replaced",
)
opts, args = p.parse_args(args)
if len(args) != 4:
sys.exit(not p.print_help())
coveragefile, oldbed, newbed, oldassembly = args
cutoff = opts.cutoff
flank = opts.flank
maxsize = opts.maxsize
coverage = DictFile(coveragefile, valuepos=2, cast=float)
obed = Bed(oldbed)
order = obed.order
bed = [x for x in obed if x.accn in coverage]
key = lambda x: coverage[x.accn] >= cutoff
extrabed = "extra.bed"
extendbed = "extend.bed"
pastebed = "paste.bed"
fw = open(extrabed, "w")
fwe = open(extendbed, "w")
fwp = open(pastebed, "w")
fw_ids = open(extendbed + ".ids", "w")
singletons, large, large_genes = 0, 0, 0
for chr, chrbed in groupby(bed, key=lambda x: x.seqid):
chrbed = list(chrbed)
for good, beds in groupby(chrbed, key=key):
if good:
continue
beds = list(beds)
blocksize = len(set([gene_name(x.accn) for x in beds]))
if blocksize == 1:
singletons += 1
accn = beds[0].accn
gi, gb = order[accn]
leftb = obed[gi - 1]
rightb = obed[gi + 1]
leftr = leftb.range
rightr = rightb.range
cur = gb.range
distance_to_left, oo = range_distance(leftr, cur)
distance_to_right, oo = range_distance(cur, rightr)
span, oo = range_distance(leftr, rightr)
if distance_to_left <= distance_to_right and distance_to_left > 0:
label = "LEFT"
else:
label = "RIGHT"
if 0 < span <= maxsize:
print(
"\t".join(
str(x) for x in (chr, leftb.start, rightb.end, gb.accn)
),
file=fwp,
)
print(leftb, file=fwe)
print(gb, file=fwe)
print(rightb, file=fwe)
print(
"L:{0} R:{1} [{2}]".format(
distance_to_left, distance_to_right, label
),
file=fwe,
)
print(gb.accn, file=fw_ids)
continue
large += 1
large_genes += blocksize
ranges = [(x.start, x.end) for x in beds]
rmin, rmax = range_minmax(ranges)
rmin -= flank
rmax += flank
name = "-".join((beds[0].accn, beds[-1].accn))
print("\t".join(str(x) for x in (chr, rmin - 1, rmax, name)), file=fw)
fw.close()
fwe.close()
extrabed = mergeBed(extrabed, d=flank, nms=True)
fastaFromBed(extrabed, oldassembly, name=True)
summary([extrabed])
logging.debug("Singleton blocks : {0}".format(singletons))
logging.debug("Large blocks : {0} ({1} genes)".format(large, large_genes))
def pastegenes(args):
"""
%prog pastegenes coverage.list old.genes.bed new.genes.bed old.assembly
Paste in zero or low coverage genes. For a set of neighboring genes
missing, add the whole cassette as unplaced scaffolds. For singletons the
program will try to make a patch.
"""
from jcvi.formats.base import DictFile
from jcvi.utils.cbook import gene_name
p = OptionParser(pastegenes.__doc__)
p.add_option("--cutoff", default=90, type="int",
help="Coverage cutoff to call gene missing [default: %default]")
p.add_option("--flank", default=2000, type="int",
help="Get the seq of size on two ends [default: %default]")
p.add_option("--maxsize", default=50000, type="int",
help="Maximum size of patchers to be replaced [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 4:
sys.exit(not p.print_help())
coveragefile, oldbed, newbed, oldassembly = args
cutoff = opts.cutoff
flank = opts.flank
maxsize = opts.maxsize
coverage = DictFile(coveragefile, valuepos=2, cast=float)
obed = Bed(oldbed)
order = obed.order
bed = [x for x in obed if x.accn in coverage]
key = lambda x: coverage[x.accn] >= cutoff
extrabed = "extra.bed"
extendbed = "extend.bed"
pastebed = "paste.bed"
fw = open(extrabed, "w")
fwe = open(extendbed, "w")
fwp = open(pastebed, "w")
fw_ids = open(extendbed + ".ids", "w")
singletons, large, large_genes = 0, 0, 0
for chr, chrbed in groupby(bed, key=lambda x: x.seqid):
chrbed = list(chrbed)
for good, beds in groupby(chrbed, key=key):
if good:
continue
beds = list(beds)
blocksize = len(set([gene_name(x.accn) for x in beds]))
if blocksize == 1:
singletons += 1
accn = beds[0].accn
gi, gb = order[accn]
leftb = obed[gi - 1]
rightb = obed[gi + 1]
leftr = leftb.range
rightr = rightb.range
cur = gb.range
distance_to_left, oo = range_distance(leftr, cur)
distance_to_right, oo = range_distance(cur, rightr)
span, oo = range_distance(leftr, rightr)
if distance_to_left <= distance_to_right and \
distance_to_left > 0:
label = "LEFT"
else:
label = "RIGHT"
if 0 < span <= maxsize:
print >> fwp, "\t".join(str(x) for x in \
(chr, leftb.start, rightb.end, gb.accn))
print >> fwe, leftb
print >> fwe, gb
print >> fwe, rightb
print >> fwe, "L:{0} R:{1} [{2}]".format(distance_to_left, \
distance_to_right, label)
print >> fw_ids, gb.accn
continue
large += 1
large_genes += blocksize
ranges = [(x.start, x.end) for x in beds]
rmin, rmax = range_minmax(ranges)
rmin -= flank
rmax += flank
name = "-".join((beds[0].accn, beds[-1].accn))
print >> fw, "\t".join(str(x) for x in (chr, rmin - 1, rmax, name))
fw.close()
fwe.close()
extrabed = mergeBed(extrabed, d=flank, nms=True)
fastaFromBed(extrabed, oldassembly, name=True)
summary([extrabed])
logging.debug("Singleton blocks : {0}".format(singletons))
logging.debug("Large blocks : {0} ({1} genes)".format(large, large_genes))
def blastfilter_main(blast_file, p, opts):
qbed, sbed, qorder, sorder, is_self = check_beds(blast_file, p, opts)
tandem_Nmax = opts.tandem_Nmax
cscore = opts.cscore
fp = open(blast_file)
total_lines = sum(1 for line in fp if line[0] != '#')
logging.debug("Load BLAST file `%s` (total %d lines)" % \
(blast_file, total_lines))
bl = Blast(blast_file)
blasts = sorted(list(bl), key=lambda b: b.score, reverse=True)
filtered_blasts = []
seen = set()
ostrip = opts.strip_names
nwarnings = 0
for b in blasts:
query, subject = b.query, b.subject
if query == subject:
continue
if ostrip:
query, subject = gene_name(query), gene_name(subject)
if query not in qorder:
if nwarnings < 100:
logging.warning("{0} not in {1}".format(query,
qbed.filename))
elif nwarnings == 100:
logging.warning("too many warnings.. suppressed")
nwarnings += 1
continue
if subject not in sorder:
if nwarnings < 100:
logging.warning("{0} not in {1}".format(subject,
sbed.filename))
elif nwarnings == 100:
logging.warning("too many warnings.. suppressed")
nwarnings += 1
continue
qi, q = qorder[query]
si, s = sorder[subject]
if is_self and qi > si:
# move all hits to same side when doing self-self BLAST
query, subject = subject, query
qi, si = si, qi
q, s = s, q
key = query, subject
if key in seen:
continue
seen.add(key)
b.query, b.subject = key
b.qi, b.si = qi, si
b.qseqid, b.sseqid = q.seqid, s.seqid
filtered_blasts.append(b)
if cscore:
before_filter = len(filtered_blasts)
logging.debug("running the cscore filter (cscore>=%.2f) .." % cscore)
filtered_blasts = list(filter_cscore(filtered_blasts, cscore=cscore))
logging.debug("after filter (%d->%d) .." % (before_filter,
len(filtered_blasts)))
if tandem_Nmax:
logging.debug("running the local dups filter (tandem_Nmax=%d) .." % \
tandem_Nmax)
qtandems = tandem_grouper(qbed, filtered_blasts,
flip=True, tandem_Nmax=tandem_Nmax)
standems = tandem_grouper(sbed, filtered_blasts,
flip=False, tandem_Nmax=tandem_Nmax)
qdups_fh = open(op.splitext(opts.qbed)[0] + ".localdups", "w") \
if opts.tandems_only else None
if is_self:
for s in standems:
qtandems.join(*s)
qdups_to_mother = write_localdups(qtandems, qbed, qdups_fh)
sdups_to_mother = qdups_to_mother
else:
qdups_to_mother = write_localdups(qtandems, qbed, qdups_fh)
sdups_fh = open(op.splitext(opts.sbed)[0] + ".localdups", "w") \
if opts.tandems_only else None
sdups_to_mother = write_localdups(standems, sbed, sdups_fh)
if opts.tandems_only:
# write out new .bed after tandem removal
write_new_bed(qbed, qdups_to_mother)
if not is_self:
write_new_bed(sbed, sdups_to_mother)
# just want to use this script as a tandem finder.
#sys.exit()
before_filter = len(filtered_blasts)
filtered_blasts = list(filter_tandem(filtered_blasts, \
qdups_to_mother, sdups_to_mother))
logging.debug("after filter (%d->%d) .." % \
(before_filter, len(filtered_blasts)))
blastfilteredfile = blast_file + ".filtered"
fw = open(blastfilteredfile, "w")
write_new_blast(filtered_blasts, fh=fw)
fw.close()
def benchmark(args):
"""
%prog benchmark at bedfile
Compare SynFind, MCScanx, iADHoRe and OrthoFinder against the truth.
"""
p = OptionParser(benchmark.__doc__)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
pf, bedfile = args
truth = pf + ".truth"
synfind = pf + ".synfind"
mcscanx = pf + ".mcscanx"
iadhore = pf + ".iadhore"
orthofinder = pf + ".orthofinder"
pivots = set([x.accn for x in Bed(bedfile)])
fp = open(truth)
truth = set()
for row in fp:
a, b = row.strip().split("\t")[:2]
pivots.add(a)
truth.add(tuple(sorted((a, b))))
logging.debug("Truth: {0} pairs".format(len(truth)))
fp = open(synfind)
benchmarkfile = pf + ".benchmark"
fw = must_open(benchmarkfile, "w")
synfind = set()
for row in fp:
atoms = row.strip().split("\t")
query, hit, tag = atoms[:3]
if tag != "S":
continue
synfind.add(tuple(sorted((query, hit))))
calc_sensitivity_specificity(synfind, truth, "SynFind", fw)
fp = open(mcscanx)
mcscanx = set()
for row in fp:
if row[0] == '#':
continue
atoms = row.strip().split(":")[1].split()
query, hit = atoms[:2]
mcscanx.add(tuple(sorted((query, hit))))
calc_sensitivity_specificity(mcscanx, truth, "MCScanX", fw)
fp = open(iadhore)
iadhore = set()
fp.next()
for row in fp:
atoms = row.strip().split("\t")
query, hit = atoms[3:5]
iadhore.add(tuple(sorted((query, hit))))
calc_sensitivity_specificity(iadhore, truth, "iADHoRe", fw)
fp = open(orthofinder)
orthofinder = set()
fp.next()
for row in fp:
row = row.replace('"', "")
atoms = row.replace(",", " ").split()
genes = [x.strip() for x in atoms if not x.startswith("OG")]
genes = [gene_name(x) for x in genes]
pps = [x for x in genes if x in pivots]
for p in pps:
for g in genes:
if p == g:
continue
orthofinder.add(tuple(sorted((p, g))))
#write_pairs(orthofinder, "orthofinder.pairs")
calc_sensitivity_specificity(orthofinder, truth, "OrthoFinder", fw)
fw.close()
def tandem_main(blast_file, cds_file, bed_file, N=3, P=50, is_self=True, \
evalue=.01, strip_name=".", ofile=sys.stderr, genefam=False):
if genefam:
N = 1e5
# get the sizes for the CDS first
f = Fasta(cds_file)
sizes = dict(f.itersizes())
# retrieve the locations
bed = Bed(bed_file)
order = bed.order
if is_self:
# filter the blast file
g = Grouper()
fp = open(blast_file)
for row in fp:
b = BlastLine(row)
query_len = sizes[b.query]
subject_len = sizes[b.subject]
if b.hitlen < min(query_len, subject_len) * P / 100.:
continue
query = gene_name(b.query, strip_name)
subject = gene_name(b.subject, strip_name)
qi, q = order[query]
si, s = order[subject]
if abs(qi - si) <= N and b.evalue <= evalue:
if genefam:
g.join(query, subject)
elif q.seqid == s.seqid:
g.join(query, subject)
else:
homologs = Grouper()
fp = open(blast_file)
for row in fp:
b = BlastLine(row)
query_len = sizes[b.query]
subject_len = sizes[b.subject]
if b.hitlen < min(query_len, subject_len) * P / 100.:
continue
if b.evalue > evalue:
continue
query = gene_name(b.query, strip_name)
subject = gene_name(b.subject, strip_name)
homologs.join(query, subject)
if genefam:
g = homologs
else:
g = Grouper()
for i, atom in enumerate(bed):
for x in range(1, N + 1):
if all([i-x >= 0, bed[i-x].seqid == atom.seqid, \
homologs.joined(bed[i-x].accn, atom.accn)]):
leni = sizes[bed[i].accn]
lenx = sizes[bed[i - x].accn]
if abs(leni - lenx) > max(leni, lenx) * (1 - P / 100.):
continue
g.join(bed[i - x].accn, atom.accn)
# dump the grouper
fw = must_open(ofile, "w")
ngenes, nfamilies = 0, 0
families = []
for group in sorted(g):
if len(group) >= 2:
print >> fw, ",".join(sorted(group))
ngenes += len(group)
nfamilies += 1
families.append(sorted(group))
longest_family = max(families, key=lambda x: len(x))
# generate reports
print >> sys.stderr, "Proximal paralogues (dist=%d):" % N
print >> sys.stderr, "Total %d genes in %d families" % (ngenes, nfamilies)
print >> sys.stderr, "Longest families (%d): %s" % (
len(longest_family), ",".join(longest_family))
return families
def cscore(args):
"""
%prog cscore blastfile > cscoreOut
See supplementary info for sea anemone genome paper, C-score formula:
cscore(A,B) = score(A,B) /
max(best score for A, best score for B)
A C-score of one is the same as reciprocal best hit (RBH).
Output file will be 3-column (query, subject, cscore). Use --cutoff to
select a different cutoff.
"""
from jcvi.utils.cbook import gene_name
p = OptionParser(cscore.__doc__)
p.add_option("--cutoff",
default=.9999,
type="float",
help="Minimum C-score to report [default: %default]")
p.add_option("--pct",
default=False,
action="store_true",
help="Also include pct as last column [default: %default]")
p.add_option("--writeblast",
default=False,
action="store_true",
help="Also write filtered blast file [default: %default]")
p.set_stripnames()
p.set_outfile()
opts, args = p.parse_args(args)
ostrip = opts.strip_names
writeblast = opts.writeblast
outfile = opts.outfile
if len(args) != 1:
sys.exit(not p.print_help())
blastfile, = args
blast = Blast(blastfile)
logging.debug("Register best scores ..")
best_score = defaultdict(float)
for b in blast:
query, subject = b.query, b.subject
if ostrip:
query, subject = gene_name(query), gene_name(subject)
score = b.score
if score > best_score[query]:
best_score[query] = score
if score > best_score[subject]:
best_score[subject] = score
blast = Blast(blastfile)
pairs = {}
cutoff = opts.cutoff
for b in blast:
query, subject = b.query, b.subject
if ostrip:
query, subject = gene_name(query), gene_name(subject)
score = b.score
pctid = b.pctid
s = score / max(best_score[query], best_score[subject])
if s > cutoff:
pair = (query, subject)
if pair not in pairs or s > pairs[pair][0]:
pairs[pair] = (s, pctid, b)
fw = must_open(outfile, "w")
if writeblast:
fwb = must_open(outfile + ".filtered.blast", "w")
pct = opts.pct
for (query, subject), (s, pctid, b) in sorted(pairs.items()):
args = [query, subject, "{0:.2f}".format(s)]
if pct:
args.append("{0:.1f}".format(pctid))
print >> fw, "\t".join(args)
if writeblast:
print >> fwb, b
fw.close()
if writeblast:
fwb.close()
def cscore(args):
"""
%prog cscore blastfile > cscoreOut
See supplementary info for sea anemone genome paper, C-score formula:
cscore(A,B) = score(A,B) /
max(best score for A, best score for B)
A C-score of one is the same as reciprocal best hit (RBH).
Output file will be 3-column (query, subject, cscore). Use --cutoff to
select a different cutoff.
"""
from jcvi.utils.cbook import gene_name
p = OptionParser(cscore.__doc__)
p.add_option("--cutoff", default=.9999, type="float",
help="Minimum C-score to report [default: %default]")
p.add_option("--pct", default=False, action="store_true",
help="Also include pct as last column [default: %default]")
p.add_option("--writeblast", default=False, action="store_true",
help="Also write filtered blast file [default: %default]")
p.set_stripnames()
p.set_outfile()
opts, args = p.parse_args(args)
ostrip = opts.strip_names
writeblast = opts.writeblast
outfile = opts.outfile
if len(args) != 1:
sys.exit(not p.print_help())
blastfile, = args
blast = Blast(blastfile)
logging.debug("Register best scores ..")
best_score = defaultdict(float)
for b in blast:
query, subject = b.query, b.subject
if ostrip:
query, subject = gene_name(query), gene_name(subject)
score = b.score
if score > best_score[query]:
best_score[query] = score
if score > best_score[subject]:
best_score[subject] = score
blast = Blast(blastfile)
pairs = {}
cutoff = opts.cutoff
for b in blast:
query, subject = b.query, b.subject
if ostrip:
query, subject = gene_name(query), gene_name(subject)
score = b.score
pctid = b.pctid
s = score / max(best_score[query], best_score[subject])
if s > cutoff:
pair = (query, subject)
if pair not in pairs or s > pairs[pair][0]:
pairs[pair] = (s, pctid, b)
fw = must_open(outfile, "w")
if writeblast:
fwb = must_open(outfile + ".filtered.blast", "w")
pct = opts.pct
for (query, subject), (s, pctid, b) in sorted(pairs.items()):
args = [query, subject, "{0:.2f}".format(s)]
if pct:
args.append("{0:.1f}".format(pctid))
print >> fw, "\t".join(args)
if writeblast:
print >> fwb, b
fw.close()
if writeblast:
fwb.close()
def blastfilter_main(blast_file, p, opts):
qbed, sbed, qorder, sorder, is_self = check_beds(blast_file, p, opts)
tandem_Nmax = opts.tandem_Nmax
cscore = opts.cscore
fp = open(blast_file)
total_lines = sum(1 for line in fp if line[0] != '#')
logging.debug("Load BLAST file `%s` (total %d lines)" % \
(blast_file, total_lines))
bl = Blast(blast_file)
blasts = sorted(list(bl), key=lambda b: b.score, reverse=True)
filtered_blasts = []
seen = set()
ostrip = opts.strip_names
nwarnings = 0
for b in blasts:
query, subject = b.query, b.subject
if query == subject:
continue
if ostrip:
query, subject = gene_name(query), gene_name(subject)
if query not in qorder:
if nwarnings < 100:
logging.warning("{0} not in {1}".format(query, qbed.filename))
elif nwarnings == 100:
logging.warning("too many warnings.. suppressed")
nwarnings += 1
continue
if subject not in sorder:
if nwarnings < 100:
logging.warning("{0} not in {1}".format(
subject, sbed.filename))
elif nwarnings == 100:
logging.warning("too many warnings.. suppressed")
nwarnings += 1
continue
qi, q = qorder[query]
si, s = sorder[subject]
if is_self and qi > si:
# move all hits to same side when doing self-self BLAST
query, subject = subject, query
qi, si = si, qi
q, s = s, q
key = query, subject
if key in seen:
continue
seen.add(key)
b.query, b.subject = key
b.qi, b.si = qi, si
b.qseqid, b.sseqid = q.seqid, s.seqid
filtered_blasts.append(b)
if cscore:
before_filter = len(filtered_blasts)
logging.debug("running the cscore filter (cscore>=%.2f) .." % cscore)
filtered_blasts = list(filter_cscore(filtered_blasts, cscore=cscore))
logging.debug("after filter (%d->%d) .." %
(before_filter, len(filtered_blasts)))
if tandem_Nmax:
logging.debug("running the local dups filter (tandem_Nmax=%d) .." % \
tandem_Nmax)
qtandems = tandem_grouper(qbed,
filtered_blasts,
flip=True,
tandem_Nmax=tandem_Nmax)
standems = tandem_grouper(sbed,
filtered_blasts,
flip=False,
tandem_Nmax=tandem_Nmax)
qdups_fh = open(op.splitext(opts.qbed)[0] + ".localdups", "w") \
if opts.tandems_only else None
if is_self:
for s in standems:
qtandems.join(*s)
qdups_to_mother = write_localdups(qtandems, qbed, qdups_fh)
sdups_to_mother = qdups_to_mother
else:
qdups_to_mother = write_localdups(qtandems, qbed, qdups_fh)
sdups_fh = open(op.splitext(opts.sbed)[0] + ".localdups", "w") \
if opts.tandems_only else None
sdups_to_mother = write_localdups(standems, sbed, sdups_fh)
if opts.tandems_only:
# write out new .bed after tandem removal
write_new_bed(qbed, qdups_to_mother)
if not is_self:
write_new_bed(sbed, sdups_to_mother)
# just want to use this script as a tandem finder.
#sys.exit()
before_filter = len(filtered_blasts)
filtered_blasts = list(filter_tandem(filtered_blasts, \
qdups_to_mother, sdups_to_mother))
logging.debug("after filter (%d->%d) .." % \
(before_filter, len(filtered_blasts)))
blastfilteredfile = blast_file + ".filtered"
fw = open(blastfilteredfile, "w")
write_new_blast(filtered_blasts, fh=fw)
fw.close()
def loss(args):
"""
%prog loss a.b.i1.blocks [a.b-genomic.blast]
Extract likely gene loss candidates between genome a and b.
"""
p = OptionParser(loss.__doc__)
p.add_option("--bed",
default=False,
action="store_true",
help="Genomic BLAST is in bed format [default: %default]")
p.add_option("--gdist",
default=20,
type="int",
help="Gene distance [default: %default]")
p.add_option("--bdist",
default=20000,
type="int",
help="Base pair distance [default: %default]")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) not in (1, 2):
sys.exit(not p.print_help())
blocksfile = args[0]
emptyblast = (len(args) == 1)
if emptyblast:
genomicblast = "empty.blast"
sh("touch {0}".format(genomicblast))
else:
genomicblast = args[1]
gdist, bdist = opts.gdist, opts.bdist
qbed, sbed, qorder, sorder, is_self = check_beds(blocksfile, p, opts)
blocks = []
fp = open(blocksfile)
genetrack = {}
proxytrack = {}
for row in fp:
a, b = row.split()
genetrack[a] = b
blocks.append((a, b))
data = []
for key, rows in groupby(blocks, key=lambda x: x[-1]):
rows = list(rows)
data.append((key, rows))
imax = len(data) - 1
for i, (key, rows) in enumerate(data):
if i == 0 or i == imax:
continue
if key != '.':
continue
before, br = data[i - 1]
after, ar = data[i + 1]
bi, bx = sorder[before]
ai, ax = sorder[after]
dist = abs(bi - ai)
if bx.seqid != ax.seqid or dist > gdist:
continue
start, end = range_minmax(((bx.start, bx.end), (ax.start, ax.end)))
start, end = max(start - bdist, 1), end + bdist
proxy = (bx.seqid, start, end)
for a, b in rows:
proxytrack[a] = proxy
tags = {}
if opts.bed:
bed = Bed(genomicblast, sorted=False)
key = lambda x: gene_name(x.accn.rsplit(".", 1)[0])
for query, bb in groupby(bed, key=key):
bb = list(bb)
if query not in proxytrack:
continue
proxy = proxytrack[query]
tag = "NS"
best_b = bb[0]
for b in bb:
hsp = (b.seqid, b.start, b.end)
if range_overlap(proxy, hsp):
tag = "S"
best_b = b
break
hsp = (best_b.seqid, best_b.start, best_b.end)
proxytrack[query] = hsp
tags[query] = tag
else:
blast = Blast(genomicblast)
for query, bb in blast.iter_hits():
bb = list(bb)
query = gene_name(query)
if query not in proxytrack:
continue
proxy = proxytrack[query]
tag = "NS"
best_b = bb[0]
for b in bb:
hsp = (b.subject, b.sstart, b.sstop)
if range_overlap(proxy, hsp):
tag = "S"
best_b = b
break
hsp = (best_b.subject, best_b.sstart, best_b.sstop)
proxytrack[query] = hsp
tags[query] = tag
for b in qbed:
accn = b.accn
target_region = genetrack[accn]
if accn in proxytrack:
target_region = region_str(proxytrack[accn])
if accn in tags:
ptag = "[{0}]".format(tags[accn])
else:
ptag = "[NF]"
target_region = ptag + target_region
print "\t".join((b.seqid, accn, target_region))
if emptyblast:
sh("rm -f {0}".format(genomicblast))
def anchorline(self):
return "\t".join((gene_name(self.gene_a), gene_name(self.gene_b),
"{:.3f}".format(self.ks)))
