def main(args):
p = OptionParser(__doc__)
p.set_beds()
p.set_stripnames()
p.add_option(
"--tandems_only",
dest="tandems_only",
action="store_true",
default=False,
help="only calculate tandems, write .localdup file and exit.",
)
p.add_option("--tandem_Nmax", type="int", default=10, help="merge tandem genes within distance [default: %default]")
p.add_option(
"--cscore",
type="float",
default=0.7,
help="retain hits that have good bitscore. a value of 0.5 means "
"keep all values that are 50% or greater of the best hit. "
"higher is more stringent [default: %default]",
)
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
blastfile, = args
blastfilter_main(blastfile, p, opts)
def rebuild(args):
"""
%prog rebuild blocksfile blastfile
Rebuild anchors file from pre-built blocks file.
"""
p = OptionParser(rebuild.__doc__)
p.add_option("--header", default=False, action="store_true",
help="First line is header [default: %default]")
p.add_option("--write_blast", default=False, action="store_true",
help="Get blast records of rebuilt anchors [default: %default]")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
blocksfile, blastfile = args
bk = BlockFile(blocksfile, header=opts.header)
fw = open("pairs", "w")
for a, b, h in bk.iter_all_pairs():
print >> fw, "\t".join((a, b))
fw.close()
if opts.write_blast:
AnchorFile("pairs").blast(blastfile, "pairs.blast")
fw = open("tracks", "w")
for g, col in bk.iter_gene_col():
print >> fw, "\t".join(str(x) for x in (g, col))
fw.close()
def bed(args):
"""
%prog bed anchorsfile
Convert ANCHORS file to BED format.
"""
from collections import defaultdict
from jcvi.compara.synteny import AnchorFile, check_beds
from jcvi.formats.bed import Bed
from jcvi.formats.base import get_number
p = OptionParser(bed.__doc__)
p.add_option("--switch", default=False, action="store_true",
help="Switch reference and aligned map elements")
p.add_option("--scale", type="float",
help="Scale the aligned map distance by factor")
p.set_beds()
p.set_outfile()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorsfile, = args
switch = opts.switch
scale = opts.scale
ac = AnchorFile(anchorsfile)
pairs = defaultdict(list)
for a, b, block_id in ac.iter_pairs():
pairs[a].append(b)
qbed, sbed, qorder, sorder, is_self = check_beds(anchorsfile, p, opts)
bd = Bed()
for q in qbed:
qseqid, qstart, qend, qaccn = q.seqid, q.start, q.end, q.accn
if qaccn not in pairs:
continue
for s in pairs[qaccn]:
si, s = sorder[s]
sseqid, sstart, send, saccn = s.seqid, s.start, s.end, s.accn
if switch:
qseqid, sseqid = sseqid, qseqid
qstart, sstart = sstart, qstart
qend, send = send, qend
qaccn, saccn = saccn, qaccn
if scale:
sstart /= scale
try:
newsseqid = get_number(sseqid)
except ValueError:
raise ValueError, "`{0}` is on `{1}` with no number to extract".\
format(saccn, sseqid)
bedline = "\t".join(str(x) for x in (qseqid, qstart - 1, qend,
"{0}:{1}".format(newsseqid, sstart)))
bd.add(bedline)
bd.print_to_file(filename=opts.outfile, sorted=True)
def depth(args):
"""
%prog depth anchorfile --qbed qbedfile --sbed sbedfile
Calculate the depths in the two genomes in comparison, given in --qbed and
--sbed. The synteny blocks will be layered on the genomes, and the
multiplicity will be summarized to stderr.
"""
from jcvi.utils.range import range_depth
p = OptionParser(depth.__doc__)
p.add_option("--depthfile",
help="Generate file with gene and depth [default: %default]")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
depthfile = opts.depthfile
ac = AnchorFile(anchorfile)
qranges = []
sranges = []
blocks = ac.blocks
for ib in blocks:
q, s, t = zip(*ib)
q = [qorder[x] for x in q]
s = [sorder[x] for x in s]
qrange = (min(q)[0], max(q)[0])
srange = (min(s)[0], max(s)[0])
qranges.append(qrange)
sranges.append(srange)
if is_self:
qranges.append(srange)
qgenome = op.basename(qbed.filename).split(".")[0]
sgenome = op.basename(sbed.filename).split(".")[0]
print >> sys.stderr, "Genome {0} depths:".format(qgenome)
ds, details = range_depth(qranges, len(qbed))
if depthfile:
fw = open(depthfile, "w")
write_details(fw, details, qbed)
if is_self:
return
print >> sys.stderr, "Genome {0} depths:".format(sgenome)
ds, details = range_depth(sranges, len(sbed))
if depthfile:
write_details(fw, details, sbed)
fw.close()
logging.debug("Depth written to `{0}`.".format(depthfile))
def layout(args):
"""
%prog layout query.subject.simple query.seqids subject.seqids
Compute optimal seqids order in a second genome, based on seqids on one
genome, given the pairwise blocks in .simple format.
"""
from jcvi.algorithms.ec import GA_setup, GA_run
p = OptionParser(layout.__doc__)
p.set_beds()
p.set_cpus(cpus=32)
opts, args = p.parse_args(args)
if len(args) != 3:
sys.exit(not p.print_help())
simplefile, qseqids, sseqids = args
qbed, sbed, qorder, sorder, is_self = check_beds(simplefile, p, opts)
qseqids = qseqids.strip().split(",")
sseqids = sseqids.strip().split(",")
qseqids_ii = dict((s, i) for i, s in enumerate(qseqids))
sseqids_ii = dict((s, i) for i, s in enumerate(sseqids))
blocks = SimpleFile(simplefile).blocks
scores = defaultdict(int)
for a, b, c, d, score, orientation, hl in blocks:
qi, q = qorder[a]
si, s = sorder[c]
qseqid, sseqid = q.seqid, s.seqid
if sseqid not in sseqids:
continue
scores[sseqids_ii[sseqid], qseqid] += score
data = []
for (a, b), score in sorted(scores.items()):
if b not in qseqids_ii:
continue
data.append((qseqids_ii[b], score))
tour = range(len(qseqids))
toolbox = GA_setup(tour)
toolbox.register("evaluate", colinear_evaluate_weights, data=data)
tour, fitness = GA_run(toolbox, ngen=100, npop=100, cpus=opts.cpus)
tour = [qseqids[x] for x in tour]
print ",".join(tour)
def mtdotplots(args):
"""
%prog mtdotplots Mt3.5 Mt4.0 medicago.medicago.lifted.1x1.anchors
Plot Mt3.5 and Mt4.0 side-by-side. This is essentially combined from two
graphics.dotplot() function calls as panel A and B.
"""
from jcvi.graphics.dotplot import check_beds, dotplot
p = OptionParser(mtdotplots.__doc__)
p.set_beds()
opts, args, iopts = p.set_image_options(args, figsize="16x8", dpi=90)
if len(args) != 3:
sys.exit(not p.print_help())
a, b, ac = args
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
r1 = fig.add_axes([0, 0, .5, 1])
r2 = fig.add_axes([.5, 0, .5, 1])
a1 = fig.add_axes([.05, .1, .4, .8])
a2 = fig.add_axes([.55, .1, .4, .8])
anchorfile = op.join(a, ac)
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
dotplot(anchorfile, qbed, sbed, fig, r1, a1, is_self=is_self,
genomenames="Mt3.5_Mt3.5")
opts.qbed = opts.sbed = None
anchorfile = op.join(b, ac)
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
dotplot(anchorfile, qbed, sbed, fig, r2, a2, is_self=is_self,
genomenames="Mt4.0_Mt4.0")
root.text(.03, .95, "A", ha="center", va="center", size=36)
root.text(.53, .95, "B", ha="center", va="center", size=36)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
pf = "mtdotplots"
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def movieframe(args):
"""
%prog movieframe tour test.clm contigs.ref.anchors
Draw heatmap and synteny in the same plot.
"""
p = OptionParser(movieframe.__doc__)
p.add_option("--label", help="Figure title")
p.set_beds()
p.set_outfile(outfile=None)
opts, args, iopts = p.set_image_options(args, figsize="16x8",
style="white", cmap="coolwarm",
format="png", dpi=120)
if len(args) != 3:
sys.exit(not p.print_help())
tour, clmfile, anchorsfile = args
tour = tour.split(",")
image_name = opts.outfile or ("movieframe." + iopts.format)
label = opts.label or op.basename(image_name).rsplit(".", 1)[0]
clm = CLMFile(clmfile)
totalbins, bins, breaks = make_bins(tour, clm.tig_to_size)
M = read_clm(clm, totalbins, bins)
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1]) # whole canvas
ax1 = fig.add_axes([.05, .1, .4, .8]) # heatmap
ax2 = fig.add_axes([.55, .1, .4, .8]) # dot plot
ax2_root = fig.add_axes([.5, 0, .5, 1]) # dot plot canvas
# Left axis: heatmap
plot_heatmap(ax1, M, breaks, iopts)
# Right axis: synteny
qbed, sbed, qorder, sorder, is_self = check_beds(anchorsfile, p, opts,
sorted=False)
dotplot(anchorsfile, qbed, sbed, fig, ax2_root, ax2, sep=False, title="")
root.text(.5, .98, clm.name, color="g", ha="center", va="center")
root.text(.5, .95, label, color="darkslategray", ha="center", va="center")
normalize_axes(root)
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def offdiag(args):
"""
%prog offdiag diploid.napus.1x1.lifted.anchors
Find gene pairs that are off diagnoal. "Off diagonal" are the pairs that are
not on the orthologous chromosomes. For example, napus chrA01 and brapa A01.
"""
p = OptionParser(offdiag.__doc__)
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorsfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorsfile, p, opts)
fp = open(anchorsfile)
pf = "-".join(anchorsfile.split(".")[:2])
header = "Block-id|Napus|Diploid|Napus-chr|Diploid-chr|RBH?".split("|")
print "\t".join(header)
i = -1
for row in fp:
if row[0] == '#':
i += 1
continue
q, s, score = row.split()
rbh = 'no' if score[-1] == 'L' else 'yes'
qi, qq = qorder[q]
si, ss = sorder[s]
oqseqid = qseqid = qq.seqid
osseqid = sseqid = ss.seqid
sseqid = sseqid.split("_")[0][-3:]
if qseqid[0] == 'A':
qseqid = qseqid[-3:] # A09 => A09
elif qseqid[0] == 'C':
qseqid = 'C0' + qseqid[-1] # C9 => C09
else:
continue
if qseqid == sseqid or sseqid[-2:] == 'nn':
continue
block_id = pf + "-block-{0}".format(i)
print "\t".join((block_id, q, s, oqseqid, osseqid, rbh))
def collinear(args):
"""
%prog collinear a.b.anchors
Reduce synteny blocks to strictly collinear, use dynamic programming in a
procedure similar to DAGchainer.
"""
p = OptionParser(collinear.__doc__)
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
af = AnchorFile(anchorfile)
newanchorfile = anchorfile.rsplit(".", 1)[0] + ".collinear.anchors"
fw = open(newanchorfile, "w")
blocks = af.blocks
for block in blocks:
print >> fw, "#" * 3
iblock = []
for q, s, score in block:
qi, q = qorder[q]
si, s = sorder[s]
score = int(long(score))
iblock.append([qi, si, score])
block = get_collinear(iblock)
for q, s, score in block:
q = qbed[q].accn
s = sbed[s].accn
print >> fw, "\t".join((q, s, str(score)))
fw.close()
def collinear(args):
"""
%prog collinear a.b.anchors
Reduce synteny blocks to strictly collinear, use dynamic programming in a
procedure similar to DAGchainer.
"""
p = OptionParser(collinear.__doc__)
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
af = AnchorFile(anchorfile)
newanchorfile = anchorfile.rsplit(".", 1)[0] + ".collinear.anchors"
fw = open(newanchorfile, "w")
blocks = af.blocks
for block in blocks:
print("#" * 3, file=fw)
iblock = []
for q, s, score in block:
qi, q = qorder[q]
si, s = sorder[s]
score = int(long(score))
iblock.append([qi, si, score])
block = get_collinear(iblock)
for q, s, score in block:
q = qbed[q].accn
s = sbed[s].accn
print("\t".join((q, s, str(score))), file=fw)
fw.close()
def mergechrom(args):
"""
%prog mergechrom a.b.anchors
merge synteny blocks on the same chromosome
"""
p = OptionParser(mergechrom.__doc__)
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
af = AnchorFile(anchorfile)
newanchorfile = anchorfile.rsplit(".", 1)[0] + ".mergechrom.anchors"
fw = open(newanchorfile, "w")
qchrom_dic = dict((b.accn,b.seqid) for b in qbed)
schrom_dic = dict((b.accn,b.seqid) for b in sbed)
block_dic = dict()
blocks = af.blocks
for (i,block) in enumerate(blocks):
q, s, score = block[0]
qchrom, schrom = qchrom_dic[q], schrom_dic[s]
k = "%s_%s" % (qchrom, schrom)
if k not in block_dic: block_dic[k] = []
block_dic[k].append(i)
for (k, idxs) in block_dic.items():
print("#" * 3, file=fw)
for i in idxs:
for q, s, score in blocks[i]:
print("\t".join((q, s, str(score))), file=fw)
fw.close()
print("%d blocks merged to %d" % (len(blocks), len(block_dic.keys())))
def mergechrom(args):
"""
%prog mergechrom a.b.anchors
merge synteny blocks on the same chromosome
"""
p = OptionParser(mergechrom.__doc__)
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
af = AnchorFile(anchorfile)
newanchorfile = anchorfile.rsplit(".", 1)[0] + ".mergechrom.anchors"
fw = open(newanchorfile, "w")
qchrom_dic = dict((b.accn, b.seqid) for b in qbed)
schrom_dic = dict((b.accn, b.seqid) for b in sbed)
block_dic = dict()
blocks = af.blocks
for (i, block) in enumerate(blocks):
q, s, score = block[0]
qchrom, schrom = qchrom_dic[q], schrom_dic[s]
k = "%s_%s" % (qchrom, schrom)
if k not in block_dic: block_dic[k] = []
block_dic[k].append(i)
for (k, idxs) in block_dic.items():
print("#" * 3, file=fw)
for i in idxs:
for q, s, score in blocks[i]:
print("\t".join((q, s, str(score))), file=fw)
fw.close()
print("%d blocks merged to %d" % (len(blocks), len(block_dic.keys())))
def main(args):
p = OptionParser(__doc__)
p.set_beds()
p.set_stripnames()
p.add_option("--tandems_only", dest="tandems_only",
action="store_true", default=False,
help="only calculate tandems, write .localdup file and exit.")
p.add_option("--tandem_Nmax", type="int", default=10,
help="merge tandem genes within distance [default: %default]")
p.add_option("--cscore", type="float", default=.7,
help="retain hits that have good bitscore. a value of 0.5 means "
"keep all values that are 50% or greater of the best hit. "
"higher is more stringent [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
blastfile, = args
blastfilter_main(blastfile, p, opts)
def rebuild(args):
"""
%prog rebuild blocksfile blastfile
Rebuild anchors file from pre-built blocks file.
"""
p = OptionParser(rebuild.__doc__)
p.add_option("--header",
default=False,
action="store_true",
help="First line is header [default: %default]")
p.add_option(
"--write_blast",
default=False,
action="store_true",
help="Get blast records of rebuilt anchors [default: %default]")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
blocksfile, blastfile = args
bk = BlockFile(blocksfile, header=opts.header)
fw = open("pairs", "w")
for a, b, h in bk.iter_all_pairs():
print >> fw, "\t".join((a, b))
fw.close()
if opts.write_blast:
AnchorFile("pairs").blast(blastfile, "pairs.blast")
fw = open("tracks", "w")
for g, col in bk.iter_gene_col():
print >> fw, "\t".join(str(x) for x in (g, col))
fw.close()
def cluster(args):
"""
%prog cluster blastfile anchorfile --qbed qbedfile --sbed sbedfile
Cluster the segments and form PAD. This is the method described in Tang et
al. (2010) PNAS paper. The anchorfile defines a list of synteny blocks,
based on which the genome on one or both axis can be chopped up into pieces
and clustered.
"""
from jcvi.utils.range import Range
p = OptionParser(cluster.__doc__)
p.set_beds()
p.add_option("--minsize", default=10, type="int",
help="Only segment using blocks >= size [default: %default]")
p.add_option("--path", default="~/scratch/bin",
help="Path to the CLUSTER 3.0 binary [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
blastfile, anchorfile = args
qbed, sbed, qorder, sorder, is_self = check_beds(blastfile, p, opts)
minsize = opts.minsize
ac = AnchorFile(anchorfile)
qranges, sranges = [], []
qextra = [x[1:] for x in qbed.get_breaks()]
sextra = [x[1:] for x in sbed.get_breaks()]
id = 0
for block in ac.iter_blocks(minsize=minsize):
q, s = zip(*block)[:2]
q = [qorder[x][0] for x in q]
s = [sorder[x][0] for x in s]
minq, maxq = min(q), max(q)
mins, maxs = min(s), max(s)
id += 1
qr = Range("0", minq, maxq, maxq - minq, id)
sr = Range("0", mins, maxs, maxs - mins, id)
qranges.append(qr)
sranges.append(sr)
qpads = list(get_segments(qranges, qextra))
spads = list(get_segments(sranges, sextra))
suffix = ".pad.bed"
qpf = opts.qbed.split(".")[0]
spf = opts.sbed.split(".")[0]
qpadfile = qpf + suffix
spadfile = spf + suffix
qnpads, qpadnames = write_PAD_bed(qpadfile, qpf, qpads, qbed)
snpads, spadnames = write_PAD_bed(spadfile, spf, spads, sbed)
qpadbed, spadbed = Bed(qpadfile), Bed(spadfile)
logmp = make_arrays(blastfile, qpadbed, spadbed, qpadnames, spadnames)
m, n = logmp.shape
matrixfile = ".".join((qpf, spf, "logmp.txt"))
fw = open(matrixfile, "w")
header = ["o"] + spadnames
print("\t".join(header), file=fw)
for i in xrange(m):
row = [qpadnames[i]] + ["{0:.1f}".format(x) for x in logmp[i, :]]
print("\t".join(row), file=fw)
fw.close()
# Run CLUSTER 3.0 (Pearson correlation, average linkage)
cmd = op.join(opts.path, "cluster")
cmd += " -g 2 -e 2 -m a -f {0}".format(matrixfile)
pf = matrixfile.rsplit(".", 1)[0]
cdtfile = pf + ".cdt"
if need_update(matrixfile, cdtfile):
sh(cmd)
def pad(args):
"""
%prog pad blastfile cdtfile --qbed q.pad.bed --sbed s.pad.bed
Test and reconstruct candidate PADs.
"""
from jcvi.formats.cdt import CDT
p = OptionParser(pad.__doc__)
p.set_beds()
p.add_option("--cutoff", default=.3, type="float",
help="The clustering cutoff to call similar [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
cutoff = opts.cutoff
blastfile, cdtfile = args
qbed, sbed, qorder, sorder, is_self = check_beds(blastfile, p, opts)
cdt = CDT(cdtfile)
qparts = list(cdt.iter_partitions(cutoff=cutoff))
sparts = list(cdt.iter_partitions(cutoff=cutoff, gtr=False))
qid, sid = {}, {}
for i, part in enumerate(qparts):
qid.update(dict((x, i) for x in part))
for i, part in enumerate(sparts):
sid.update(dict((x, i) for x in part))
# Without writing files, conversion from PAD to merged PAD is done in memory
for q in qbed:
q.seqid = qid[q.seqid]
for s in sbed:
s.seqid = sid[s.seqid]
qnames = range(len(qparts))
snames = range(len(sparts))
logmp = make_arrays(blastfile, qbed, sbed, qnames, snames)
m, n = logmp.shape
pvalue_cutoff = 1e-30
cutoff = - log(pvalue_cutoff)
significant = []
for i in xrange(m):
for j in xrange(n):
score = logmp[i, j]
if score < cutoff:
continue
significant.append((qparts[i], sparts[j], score))
for a, b, score in significant:
print("|".join(a), "|".join(b), score)
logging.debug("Collected {0} PAR comparisons significant at (P < {1}).".\
format(len(significant), pvalue_cutoff))
return significant
def movie(args):
"""
%prog movie test.tour test.clm ref.contigs.last
Plot optimization history.
"""
p = OptionParser(movie.__doc__)
p.add_option("--frames",
default=500,
type="int",
help="Only plot every N frames")
p.add_option("--engine",
default="ffmpeg",
choices=("ffmpeg", "gifsicle"),
help="Movie engine, output MP4 or GIF")
p.set_beds()
opts, args, iopts = p.set_image_options(args,
figsize="16x8",
style="white",
cmap="coolwarm",
format="png",
dpi=300)
if len(args) != 3:
sys.exit(not p.print_help())
tourfile, clmfile, lastfile = args
tourfile = op.abspath(tourfile)
clmfile = op.abspath(clmfile)
lastfile = op.abspath(lastfile)
cwd = os.getcwd()
odir = op.basename(tourfile).rsplit(".", 1)[0] + "-movie"
anchorsfile, qbedfile, contig_to_beds = \
prepare_synteny(tourfile, lastfile, odir, p, opts)
args = []
for i, label, tour, tour_o in iter_tours(tourfile, frames=opts.frames):
padi = "{:06d}".format(i)
# Make sure the anchorsfile and bedfile has the serial number in,
# otherwise parallelization may fail
a, b = op.basename(anchorsfile).split(".", 1)
ianchorsfile = a + "_" + padi + "." + b
symlink(anchorsfile, ianchorsfile)
# Make BED file with new order
qb = Bed()
for contig, o in zip(tour, tour_o):
if contig not in contig_to_beds:
continue
bedlines = contig_to_beds[contig][:]
if o == '-':
bedlines.reverse()
for x in bedlines:
qb.append(x)
a, b = op.basename(qbedfile).split(".", 1)
ibedfile = a + "_" + padi + "." + b
qb.print_to_file(ibedfile)
# Plot dot plot, but do not sort contigs by name (otherwise losing
# order)
image_name = padi + "." + iopts.format
tour = ",".join(tour)
args.append([[
tour, clmfile, ianchorsfile, "--outfile", image_name, "--label",
label
]])
Jobs(movieframe, args).run()
os.chdir(cwd)
make_movie(odir, odir, engine=opts.engine, format=iopts.format)
def simple(args):
"""
%prog simple anchorfile --qbed=qbedfile --sbed=sbedfile [options]
Write the block ends for each block in the anchorfile.
GeneA1 GeneA2 GeneB1 GeneB2 +/- score
Optional additional columns:
orderA1 orderA2 orderB1 orderB2 sizeA sizeB size block_id
With base coordinates (--coords):
block_id seqidA startA endA bpSpanA GeneA1 GeneA2 geneSpanA
block_id seqidB startB endB bpSpanB GeneB1 GeneB2 geneSpanB
"""
p = OptionParser(simple.__doc__)
p.add_option("--rich", default=False, action="store_true", \
help="Output additional columns [default: %default]")
p.add_option(
"--coords",
default=False,
action="store_true",
help="Output columns with base coordinates [default: %default]")
p.add_option("--bed",
default=False,
action="store_true",
help="Generate BED file for the blocks")
p.add_option("--noheader",
default=False,
action="store_true",
help="Don't output header [default: %default]")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
additional = opts.rich
coords = opts.coords
header = not opts.noheader
bed = opts.bed
if bed:
coords = True
bbed = Bed()
ac = AnchorFile(anchorfile)
simplefile = anchorfile.rsplit(".", 1)[0] + ".simple"
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
pf = "-".join(anchorfile.split(".", 2)[:2])
blocks = ac.blocks
if coords:
h = "Block|Chr|Start|End|Span|StartGene|EndGene|GeneSpan|Orientation"
else:
h = "StartGeneA|EndGeneA|StartGeneB|EndGeneB|Orientation|Score"
if additional:
h += "|StartOrderA|EndOrderA|StartOrderB|EndOrderB|"\
"SizeA|SizeB|Size|Block"
fws = open(simplefile, "w")
if header:
print >> fws, "\t".join(h.split("|"))
atotalbase = btotalbase = 0
for i, block in enumerate(blocks):
a, b, scores = zip(*block)
a = [qorder[x] for x in a]
b = [sorder[x] for x in b]
ia, oa = zip(*a)
ib, ob = zip(*b)
astarti, aendi = min(ia), max(ia)
bstarti, bendi = min(ib), max(ib)
astart, aend = min(a)[1].accn, max(a)[1].accn
bstart, bend = min(b)[1].accn, max(b)[1].accn
sizeA = len(set(ia))
sizeB = len(set(ib))
size = len(block)
slope, intercept = np.polyfit(ia, ib, 1)
orientation = "+" if slope >= 0 else '-'
aspan = aendi - astarti + 1
bspan = bendi - bstarti + 1
score = int((aspan * bspan)**.5)
score = str(score)
block_id = pf + "-block-{0}".format(i)
if coords:
aseqid, astartbase, aendbase = \
get_boundary_bases(astart, aend, qorder)
bseqid, bstartbase, bendbase = \
get_boundary_bases(bstart, bend, sorder)
abase = aendbase - astartbase + 1
bbase = bendbase - bstartbase + 1
atotalbase += abase
btotalbase += bbase
# Write dual lines
aargs = [
block_id, aseqid, astartbase, aendbase, abase, astart, aend,
aspan, "+"
]
bargs = [
block_id, bseqid, bstartbase, bendbase, bbase, bstart, bend,
bspan, orientation
]
if bed:
bbed.append(BedLine("\t".join(str(x) for x in \
(bseqid, bstartbase - 1, bendbase,
"{}:{}-{}".format(aseqid, astartbase, aendbase),
size, orientation))))
for args in (aargs, bargs):
print >> fws, "\t".join(str(x) for x in args)
continue
args = [astart, aend, bstart, bend, score, orientation]
if additional:
args += [
astarti, aendi, bstarti, bendi, sizeA, sizeB, size, block_id
]
print >> fws, "\t".join(str(x) for x in args)
fws.close()
logging.debug("A total of {0} blocks written to `{1}`.".format(
i + 1, simplefile))
if coords:
print >> sys.stderr, "Total block span in {0}: {1}".format(qbed.filename, \
human_size(atotalbase, precision=2))
print >> sys.stderr, "Total block span in {0}: {1}".format(sbed.filename, \
human_size(btotalbase, precision=2))
print >> sys.stderr, "Ratio: {0:.1f}x".format(\
max(atotalbase, btotalbase) * 1. / min(atotalbase, btotalbase))
if bed:
bedfile = simplefile + ".bed"
bbed.print_to_file(filename=bedfile, sorted=True)
logging.debug("Bed file written to `{}`".format(bedfile))
def pad(args):
"""
%prog pad blastfile cdtfile --qbed q.pad.bed --sbed s.pad.bed
Test and reconstruct candidate PADs.
"""
from jcvi.formats.cdt import CDT
p = OptionParser(pad.__doc__)
p.set_beds()
p.add_option(
"--cutoff",
default=0.3,
type="float",
help="The clustering cutoff to call similar",
)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
cutoff = opts.cutoff
blastfile, cdtfile = args
qbed, sbed, qorder, sorder, is_self = check_beds(blastfile, p, opts)
cdt = CDT(cdtfile)
qparts = list(cdt.iter_partitions(cutoff=cutoff))
sparts = list(cdt.iter_partitions(cutoff=cutoff, gtr=False))
qid, sid = {}, {}
for i, part in enumerate(qparts):
qid.update(dict((x, i) for x in part))
for i, part in enumerate(sparts):
sid.update(dict((x, i) for x in part))
# Without writing files, conversion from PAD to merged PAD is done in memory
for q in qbed:
q.seqid = qid[q.seqid]
for s in sbed:
s.seqid = sid[s.seqid]
qnames = range(len(qparts))
snames = range(len(sparts))
logmp = make_arrays(blastfile, qbed, sbed, qnames, snames)
m, n = logmp.shape
pvalue_cutoff = 1e-30
cutoff = -log(pvalue_cutoff)
significant = []
for i in range(m):
for j in range(n):
score = logmp[i, j]
if score < cutoff:
continue
significant.append((qparts[i], sparts[j], score))
for a, b, score in significant:
print("|".join(a), "|".join(b), score)
logging.debug(
"Collected {0} PAR comparisons significant at (P < {1}).".format(
len(significant), pvalue_cutoff
)
)
return significant
logging.debug("Self comparisons, mirror ignored")
else:
batch_query(qbed, sbed, all_data, opts, fw=fw, c=c, transpose=True)
if sqlite:
c.execute("create index q on synteny (query)")
conn.commit()
c.close()
else:
fw.close()
if __name__ == '__main__':
p = OptionParser(__doc__)
p.set_beds()
p.set_stripnames()
p.set_outfile()
coge_group = OptionGroup(p, "CoGe-specific options")
coge_group.add_option("--sqlite", help="Write sqlite database")
coge_group.add_option("--qnote",
default="null",
help="Query dataset group id")
coge_group.add_option("--snote",
default="null",
help="Subject dataset group id")
params_group = OptionGroup(p, "Synteny parameters")
params_group.add_option("--window",
type="int",
def omgprepare(args):
"""
%prog omgprepare ploidy anchorsfile blastfile
Prepare to run Sankoff's OMG algorithm to get orthologs.
"""
from jcvi.formats.blast import cscore
from jcvi.formats.base import DictFile
p = OptionParser(omgprepare.__doc__)
p.add_option("--norbh", action="store_true",
help="Disable RBH hits [default: %default]")
p.add_option("--pctid", default=0, type="int",
help="Percent id cutoff for RBH hits [default: %default]")
p.add_option("--cscore", default=90, type="int",
help="C-score cutoff for RBH hits [default: %default]")
p.set_stripnames()
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 3:
sys.exit(not p.print_help())
ploidy, anchorfile, blastfile = args
norbh = opts.norbh
pctid = opts.pctid
cs = opts.cscore
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
fp = open(ploidy)
genomeidx = dict((x.split()[0], i) for i, x in enumerate(fp))
fp.close()
ploidy = DictFile(ploidy)
geneinfo(qbed, qorder, genomeidx, ploidy)
geneinfo(sbed, sorder, genomeidx, ploidy)
pf = blastfile.rsplit(".", 1)[0]
cscorefile = pf + ".cscore"
cscore([blastfile, "-o", cscorefile, "--cutoff=0", "--pct"])
ac = AnchorFile(anchorfile)
pairs = set((a, b) for a, b, i in ac.iter_pairs())
logging.debug("Imported {0} pairs from `{1}`.".format(len(pairs), anchorfile))
weightsfile = pf + ".weights"
fp = open(cscorefile)
fw = open(weightsfile, "w")
npairs = 0
for row in fp:
a, b, c, pct = row.split()
c, pct = float(c), float(pct)
c = int(c * 100)
if (a, b) not in pairs:
if norbh:
continue
if c < cs:
continue
if pct < pctid:
continue
c /= 10 # This severely penalizes RBH against synteny
print >> fw, "\t".join((a, b, str(c)))
npairs += 1
fw.close()
logging.debug("Write {0} pairs to `{1}`.".format(npairs, weightsfile))
def main(args):
p = OptionParser(__doc__)
p.set_beds()
p.add_option(
"--quota",
default="1:1",
help="`quota mapping` procedure -- screen blocks to constrain mapping"
" (useful for orthology), "
"put in the format like (#subgenomes expected for genome X):"
"(#subgenomes expected for genome Y) "
"[default: %default]")
p.add_option("--Nm",
dest="Nmax",
type="int",
default=10,
help="distance cutoff to tolerate two blocks that are "
"slightly overlapping (cutoff for `quota mapping`) "
"[default: %default units (gene or bp dist)]")
supported_solvers = ("SCIP", "GLPK")
p.add_option(
"--self",
dest="self_match",
action="store_true",
default=False,
help="you might turn this on when screening paralogous blocks, "
"esp. if you have reduced mirrored blocks into non-redundant set")
p.add_option("--solver",
default="SCIP",
choices=supported_solvers,
help="use MIP solver [default: %default]")
p.set_verbose(help="Show verbose solver output")
p.add_option("--screen",
default=False,
action="store_true",
help="generate new anchors file [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
qa_file, = args
qbed, sbed, qorder, sorder, is_self = check_beds(qa_file, p, opts)
# sanity check for the quota
if opts.quota:
try:
qa, qb = opts.quota.split(":")
qa, qb = int(qa), int(qb)
except:
print("quota string should be the form x:x (2:4, 1:3, etc.)",
file=sys.stderr)
sys.exit(1)
if opts.self_match and qa != qb:
raise Exception("when comparing genome to itself, "
"quota must be the same number "
"(like 1:1, 2:2) you have %s" % opts.quota)
quota = (qa, qb)
self_match = opts.self_match
clusters = read_clusters(qa_file, qorder, sorder)
for cluster in clusters:
assert len(cluster) > 0
# below runs `quota mapping`
work_dir = op.join(op.dirname(op.abspath(qa_file)), "work")
selected_ids = solve_lp(clusters,
quota,
work_dir=work_dir,
Nmax=opts.Nmax,
self_match=self_match,
solver=opts.solver,
verbose=opts.verbose)
logging.debug("Selected {0} blocks.".format(len(selected_ids)))
prefix = qa_file.rsplit(".", 1)[0]
suffix = "{0}x{1}".format(qa, qb)
outfile = ".".join((prefix, suffix))
fw = must_open(outfile, "w")
print(",".join(str(x) for x in selected_ids), file=fw)
fw.close()
logging.debug("Screened blocks ids written to `{0}`.".format(outfile))
if opts.screen:
from jcvi.compara.synteny import screen
new_qa_file = ".".join((prefix, suffix, "anchors"))
largs = [qa_file, new_qa_file, "--ids", outfile]
if opts.qbed and opts.sbed:
largs += ["--qbed={0}".format(opts.qbed)]
largs += ["--sbed={0}".format(opts.sbed)]
screen(largs)
def movie(args):
"""
%prog movie test.tour test.clm ref.contigs.last
Plot optimization history.
"""
p = OptionParser(movie.__doc__)
p.add_option("--frames", default=500, type="int",
help="Only plot every N frames")
p.add_option("--engine", default="ffmpeg", choices=("ffmpeg", "gifsicle"),
help="Movie engine, output MP4 or GIF")
p.set_beds()
opts, args, iopts = p.set_image_options(args, figsize="16x8",
style="white", cmap="coolwarm",
format="png", dpi=300)
if len(args) != 3:
sys.exit(not p.print_help())
tourfile, clmfile, lastfile = args
tourfile = op.abspath(tourfile)
clmfile = op.abspath(clmfile)
lastfile = op.abspath(lastfile)
cwd = os.getcwd()
odir = op.basename(tourfile).rsplit(".", 1)[0] + "-movie"
anchorsfile, qbedfile, contig_to_beds = \
prepare_synteny(tourfile, lastfile, odir, p, opts)
args = []
for i, label, tour, tour_o in iter_tours(tourfile, frames=opts.frames):
padi = "{:06d}".format(i)
# Make sure the anchorsfile and bedfile has the serial number in,
# otherwise parallelization may fail
a, b = op.basename(anchorsfile).split(".", 1)
ianchorsfile = a + "_" + padi + "." + b
symlink(anchorsfile, ianchorsfile)
# Make BED file with new order
qb = Bed()
for contig, o in zip(tour, tour_o):
if contig not in contig_to_beds:
continue
bedlines = contig_to_beds[contig][:]
if o == '-':
bedlines.reverse()
for x in bedlines:
qb.append(x)
a, b = op.basename(qbedfile).split(".", 1)
ibedfile = a + "_" + padi + "." + b
qb.print_to_file(ibedfile)
# Plot dot plot, but do not sort contigs by name (otherwise losing
# order)
image_name = padi + "." + iopts.format
tour = ",".join(tour)
args.append([[tour, clmfile, ianchorsfile,
"--outfile", image_name, "--label", label]])
Jobs(movieframe, args).run()
os.chdir(cwd)
make_movie(odir, odir, engine=opts.engine, format=iopts.format)
def main(args):
p = OptionParser(__doc__)
p.set_beds()
p.add_option("--quota", default="1:1",
help="`quota mapping` procedure -- screen blocks to constrain mapping"\
" (useful for orthology), "\
"put in the format like (#subgenomes expected for genome X):"\
"(#subgenomes expected for genome Y) "\
"[default: %default]")
p.add_option("--Nm", dest="Nmax", type="int", default=10,
help="distance cutoff to tolerate two blocks that are "\
"slightly overlapping (cutoff for `quota mapping`) "\
"[default: %default units (gene or bp dist)]")
supported_solvers = ("SCIP", "GLPK")
p.add_option("--self", dest="self_match",
action="store_true", default=False,
help="you might turn this on when screening paralogous blocks, "\
"esp. if you have reduced mirrored blocks into non-redundant set")
p.add_option("--solver", default="SCIP", choices=supported_solvers,
help="use MIP solver [default: %default]")
p.add_option("--verbose", action="store_true",
default=False, help="show verbose solver output")
p.add_option("--screen", default=False, action="store_true",
help="generate new anchors file [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
qa_file, = args
qbed, sbed, qorder, sorder, is_self = check_beds(qa_file, p, opts)
# sanity check for the quota
if opts.quota:
try:
qa, qb = opts.quota.split(":")
qa, qb = int(qa), int(qb)
except:
print >> sys.stderr, "quota string should be the form x:x (2:4, 1:3, etc.)"
sys.exit(1)
if opts.self_match and qa != qb:
raise Exception, "when comparing genome to itself, " \
"quota must be the same number " \
"(like 1:1, 2:2) you have %s" % opts.quota
quota = (qa, qb)
self_match = opts.self_match
clusters = read_clusters(qa_file, qorder, sorder)
for cluster in clusters:
assert len(cluster) > 0
# below runs `quota mapping`
work_dir = op.join(op.dirname(op.abspath(qa_file)), "work")
selected_ids = solve_lp(clusters, quota, work_dir=work_dir, \
Nmax=opts.Nmax, self_match=self_match, \
solver=opts.solver, verbose=opts.verbose)
logging.debug("Selected {0} blocks.".format(len(selected_ids)))
prefix = qa_file.rsplit(".", 1)[0]
suffix = "{0}x{1}".format(qa, qb)
outfile = ".".join((prefix, suffix))
fw = must_open(outfile, "w")
print >> fw, ",".join(str(x) for x in selected_ids)
fw.close()
logging.debug("Screened blocks ids written to `{0}`.".format(outfile))
if opts.screen:
from jcvi.compara.synteny import screen
new_qa_file = ".".join((prefix, suffix, "anchors"))
largs = [qa_file, new_qa_file, "--ids", outfile]
if opts.qbed and opts.sbed:
largs += ["--qbed={0}".format(opts.qbed)]
largs += ["--sbed={0}".format(opts.sbed)]
screen(largs)
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 ancestral(args):
"""
%prog ancestral vplanifoliaA.vplanifoliaA.anchors > vplanifoliaA_blocks.bed
Paint 14 chromosomes following alpha WGD.
"""
p = OptionParser(ancestral.__doc__)
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
(anchorsfile, ) = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorsfile, p, opts)
# We focus on the following chromosome pairs
target_pairs = {
(1, 1),
(1, 6),
(1, 8),
(1, 13),
(2, 4),
(3, 12),
(3, 14),
(5, 6),
(5, 8),
(7, 9),
(7, 11),
(9, 10),
(10, 11),
}
def get_target(achr, bchr):
if "chr" not in achr and "chr" not in bchr:
return None
achr, bchr = get_number(achr), get_number(bchr)
if achr > bchr:
achr, bchr = bchr, achr
if (achr, bchr) in target_pairs:
return achr, bchr
return None
def build_bedline(astart, aend, target_pair):
# target_name = "{:02d}-{:02d}".format(*target_pair)
target_name = [
str(x) for x in target_pair if x in (1, 2, 3, 5, 7, 10)
][0]
return "\t".join(
str(x)
for x in (astart.seqid, astart.start, aend.end, target_name))
# Iterate through the blocks, store any regions that has hits to one of the
# target_pairs
ac = AnchorFile(anchorsfile)
blocks = ac.blocks
outbed = Bed()
for i, block in enumerate(blocks):
a, b, scores = zip(*block)
a = [qorder[x] for x in a]
b = [sorder[x] for x in b]
astart, aend = min(a)[1], max(a)[1]
bstart, bend = min(b)[1], max(b)[1]
# Now convert to BED lines with new accn
achr, bchr = astart.seqid, bstart.seqid
target = get_target(achr, bchr)
if target is None:
continue
outbed.add(build_bedline(astart, aend, target))
outbed.add(build_bedline(bstart, bend, target))
outbed.print_to_file(sorted=True)
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 dotplot_main(args):
p = OptionParser(__doc__)
p.set_beds()
p.add_option("--synteny", default=False, action="store_true",
help="Run a fast synteny scan and display blocks [default: %default]")
p.add_option("--cmaptext", help="Draw colormap box on the bottom-left corner")
p.add_option("--vmin", dest="vmin", type="float", default=0,
help="Minimum value in the colormap [default: %default]")
p.add_option("--vmax", dest="vmax", type="float", default=2,
help="Maximum value in the colormap [default: %default]")
p.add_option("--genomenames", type="string", default=None,
help="genome names for labeling axes in the form of qname_sname, " \
"eg. \"Vitis vinifera_Oryza sativa\"")
p.add_option("--nmax", dest="sample_number", type="int", default=10000,
help="Maximum number of data points to plot [default: %default]")
p.add_option("--minfont", type="int", default=4,
help="Do not render labels with size smaller than")
p.add_option("--colormap",
help="Two column file, block id to color mapping [default: %default]")
p.add_option("--nosort", default=False, action="store_true",
help="Do not sort the seqids along the axes")
p.add_option("--nosep", default=False, action="store_true",
help="Do not add contig lines")
p.add_option("--nostdpf", default=False, action="store_true",
help="Do not standardize contig names")
p.add_option("--skipempty", default=False, action="store_true",
help="Skip seqids that do not have matches")
p.add_option("--title", help="Title of the dot plot")
p.set_outfile(outfile=None)
opts, args, iopts = p.set_image_options(args, figsize="8x8",
style="dark", dpi=90, cmap="copper")
if len(args) != 1:
sys.exit(not p.print_help())
palette = opts.colormap
if palette:
palette = Palette(palette)
anchorfile, = args
cmaptext = opts.cmaptext
if anchorfile.endswith(".ks"):
from jcvi.apps.ks import KsFile
logging.debug("Anchors contain Ks values")
cmaptext = cmaptext or "*Ks* values"
anchorksfile = anchorfile + ".anchors"
if need_update(anchorfile, anchorksfile):
ksfile = KsFile(anchorfile)
ksfile.print_to_anchors(anchorksfile)
anchorfile = anchorksfile
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts,
sorted=(not opts.nosort))
if opts.skipempty:
ac = AnchorFile(anchorfile)
if is_self:
qseqids = sseqids = set()
else:
qseqids, sseqids = set(), set()
for pair in ac.iter_pairs():
q, s = pair[:2]
qi, q = qorder[q]
si, s = sorder[s]
qseqids.add(q.seqid)
sseqids.add(s.seqid)
if is_self:
qbed = sbed = subset_bed(qbed, qseqids)
else:
qbed = subset_bed(qbed, qseqids)
sbed = subset_bed(sbed, sseqids)
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1]) # the whole canvas
ax = fig.add_axes([.1, .1, .8, .8]) # the dot plot
dotplot(anchorfile, qbed, sbed, fig, root, ax,
vmin=opts.vmin, vmax=opts.vmax, is_self=is_self,
synteny=opts.synteny, cmap_text=opts.cmaptext, cmap=iopts.cmap,
genomenames=opts.genomenames, sample_number=opts.sample_number,
minfont=opts.minfont, palette=palette, sep=(not opts.nosep),
title=opts.title, stdpf=(not opts.nostdpf))
image_name = opts.outfile or \
(op.splitext(anchorfile)[0] + "." + opts.format)
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
fig.clear()
def depth(args):
"""
%prog depth anchorfile --qbed qbedfile --sbed sbedfile
Calculate the depths in the two genomes in comparison, given in --qbed and
--sbed. The synteny blocks will be layered on the genomes, and the
multiplicity will be summarized to stderr.
"""
from jcvi.utils.range import range_depth
p = OptionParser(depth.__doc__)
p.add_option("--depthfile",
help="Generate file with gene and depth [default: %default]")
p.add_option("--histogram", default=False, action="store_true",
help="Plot histograms in PDF")
p.add_option("--xmax", type="int", help="x-axis maximum to display in plot")
p.add_option("--title", default=None, help="Title to display in plot")
p.add_option("--quota", help="Force to use this quota, e.g. 1:1, 1:2 ...")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
depthfile = opts.depthfile
ac = AnchorFile(anchorfile)
qranges = []
sranges = []
blocks = ac.blocks
for ib in blocks:
q, s, t = zip(*ib)
q = [qorder[x] for x in q]
s = [sorder[x] for x in s]
qrange = (min(q)[0], max(q)[0])
srange = (min(s)[0], max(s)[0])
qranges.append(qrange)
sranges.append(srange)
if is_self:
qranges.append(srange)
qgenome = op.basename(qbed.filename).split(".")[0]
sgenome = op.basename(sbed.filename).split(".")[0]
qtag = "Genome {0} depths".format(qgenome)
print >> sys.stderr, "{}:".format(qtag)
dsq, details = range_depth(qranges, len(qbed))
if depthfile:
fw = open(depthfile, "w")
write_details(fw, details, qbed)
if is_self:
return
stag = "Genome {0} depths".format(sgenome)
print >> sys.stderr, "{}:".format(stag)
dss, details = range_depth(sranges, len(sbed))
if depthfile:
write_details(fw, details, sbed)
fw.close()
logging.debug("Depth written to `{0}`.".format(depthfile))
if not opts.histogram:
return
from jcvi.graphics.base import plt, quickplot_ax, savefig, normalize_axes
# Plot two histograms one for query genome, one for subject genome
plt.figure(1, (6, 3))
f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
xmax = opts.xmax or max(4, max(dsq.keys() + dss.keys()))
if opts.quota:
speak, qpeak = opts.quota.split(":")
qpeak, speak = int(qpeak), int(speak)
else:
qpeak = find_peak(dsq)
speak = find_peak(dss)
qtag = "# of {} blocks per {} gene".format(sgenome, qgenome)
stag = "# of {} blocks per {} gene".format(qgenome, sgenome)
quickplot_ax(ax1, dss, 0, xmax, stag, ylabel="Percentage of genome",
highlight=range(1, speak + 1))
quickplot_ax(ax2, dsq, 0, xmax, qtag, ylabel=None,
highlight=range(1, qpeak + 1))
title = opts.title or "{} vs {} syntenic depths\n{}:{} pattern"\
.format(qgenome, sgenome, speak, qpeak)
root = f.add_axes([0, 0, 1, 1])
vs, pattern = title.split('\n')
root.text(.5, .97, vs, ha="center", va="center", color="darkslategray")
root.text(.5, .925, pattern, ha="center", va="center",
color="tomato", size=16)
print >> sys.stderr, title
normalize_axes(root)
pf = anchorfile.rsplit(".", 1)[0] + ".depth"
image_name = pf + ".pdf"
savefig(image_name)
logging.debug("Self comparisons, mirror ignored")
else:
batch_query(qbed, sbed, all_data, opts, fw=fw, c=c, transpose=True)
if sqlite:
c.execute("create index q on synteny (query)")
conn.commit()
c.close()
else:
fw.close()
if __name__ == '__main__':
p = OptionParser(__doc__)
p.set_beds()
p.set_stripnames()
p.set_outfile()
coge_group = OptionGroup(p, "CoGe-specific options")
coge_group.add_option("--sqlite", help="Write sqlite database")
coge_group.add_option("--qnote", default="null",
help="Query dataset group id")
coge_group.add_option("--snote", default="null",
help="Subject dataset group id")
params_group = OptionGroup(p, "Synteny parameters")
params_group.add_option("--window", type="int", default=40,
help="Synteny window size")
params_group.add_option("--cutoff", type="float", default=.1,
help="Minimum number of anchors to call synteny")
def simple(args):
"""
%prog simple anchorfile --qbed=qbedfile --sbed=sbedfile [options]
Write the block ends for each block in the anchorfile.
GeneA1 GeneA2 GeneB1 GeneB2 +/- score
Optional additional columns:
orderA1 orderA2 orderB1 orderB2 sizeA sizeB size block_id
With base coordinates (--coords):
block_id seqidA startA endA bpSpanA GeneA1 GeneA2 geneSpanA
block_id seqidB startB endB bpSpanB GeneB1 GeneB2 geneSpanB
"""
p = OptionParser(simple.__doc__)
p.add_option("--rich", default=False, action="store_true", \
help="Output additional columns [default: %default]")
p.add_option("--coords", default=False, action="store_true",
help="Output columns with base coordinates [default: %default]")
p.add_option("--bed", default=False, action="store_true",
help="Generate BED file for the blocks")
p.add_option("--noheader", default=False, action="store_true",
help="Don't output header [default: %default]")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
additional = opts.rich
coords = opts.coords
header = not opts.noheader
bed = opts.bed
if bed:
coords = True
bbed = Bed()
ac = AnchorFile(anchorfile)
simplefile = anchorfile.rsplit(".", 1)[0] + ".simple"
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
pf = "-".join(anchorfile.split(".", 2)[:2])
blocks = ac.blocks
if coords:
h = "Block|Chr|Start|End|Span|StartGene|EndGene|GeneSpan|Orientation"
else:
h = "StartGeneA|EndGeneA|StartGeneB|EndGeneB|Orientation|Score"
if additional:
h += "|StartOrderA|EndOrderA|StartOrderB|EndOrderB|"\
"SizeA|SizeB|Size|Block"
fws = open(simplefile, "w")
if header:
print >> fws, "\t".join(h.split("|"))
atotalbase = btotalbase = 0
for i, block in enumerate(blocks):
a, b, scores = zip(*block)
a = [qorder[x] for x in a]
b = [sorder[x] for x in b]
ia, oa = zip(*a)
ib, ob = zip(*b)
astarti, aendi = min(ia), max(ia)
bstarti, bendi = min(ib), max(ib)
astart, aend = min(a)[1].accn, max(a)[1].accn
bstart, bend = min(b)[1].accn, max(b)[1].accn
sizeA = len(set(ia))
sizeB = len(set(ib))
size = len(block)
slope, intercept = np.polyfit(ia, ib, 1)
orientation = "+" if slope >= 0 else '-'
aspan = aendi - astarti + 1
bspan = bendi - bstarti + 1
score = int((aspan * bspan) ** .5)
score = str(score)
block_id = pf + "-block-{0}".format(i)
if coords:
aseqid, astartbase, aendbase = \
get_boundary_bases(astart, aend, qorder)
bseqid, bstartbase, bendbase = \
get_boundary_bases(bstart, bend, sorder)
abase = aendbase - astartbase + 1
bbase = bendbase - bstartbase + 1
atotalbase += abase
btotalbase += bbase
# Write dual lines
aargs = [block_id, aseqid, astartbase, aendbase,
abase, astart, aend, aspan, "+"]
bargs = [block_id, bseqid, bstartbase, bendbase,
bbase, bstart, bend, bspan, orientation]
if bed:
bbed.append(BedLine("\t".join(str(x) for x in \
(bseqid, bstartbase - 1, bendbase,
"{}:{}-{}".format(aseqid, astartbase, aendbase),
size, orientation))))
for args in (aargs, bargs):
print >> fws, "\t".join(str(x) for x in args)
continue
args = [astart, aend, bstart, bend, score, orientation]
if additional:
args += [astarti, aendi, bstarti, bendi,
sizeA, sizeB, size, block_id]
print >> fws, "\t".join(str(x) for x in args)
fws.close()
logging.debug("A total of {0} blocks written to `{1}`.".format(i + 1, simplefile))
if coords:
print >> sys.stderr, "Total block span in {0}: {1}".format(qbed.filename, \
human_size(atotalbase, precision=2))
print >> sys.stderr, "Total block span in {0}: {1}".format(sbed.filename, \
human_size(btotalbase, precision=2))
print >> sys.stderr, "Ratio: {0:.1f}x".format(\
max(atotalbase, btotalbase) * 1. / min(atotalbase, btotalbase))
if bed:
bedfile = simplefile + ".bed"
bbed.print_to_file(filename=bedfile, sorted=True)
logging.debug("Bed file written to `{}`".format(bedfile))
def cluster(args):
"""
%prog cluster blastfile anchorfile --qbed qbedfile --sbed sbedfile
Cluster the segments and form PAD. This is the method described in Tang et
al. (2010) PNAS paper. The anchorfile defines a list of synteny blocks,
based on which the genome on one or both axis can be chopped up into pieces
and clustered.
"""
from jcvi.utils.range import Range
p = OptionParser(cluster.__doc__)
p.set_beds()
p.add_option(
"--minsize", default=10, type="int", help="Only segment using blocks >= size"
)
p.add_option(
"--path", default="~/scratch/bin", help="Path to the CLUSTER 3.0 binary"
)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
blastfile, anchorfile = args
qbed, sbed, qorder, sorder, is_self = check_beds(blastfile, p, opts)
minsize = opts.minsize
ac = AnchorFile(anchorfile)
qranges, sranges = [], []
qextra = [x[1:] for x in qbed.get_breaks()]
sextra = [x[1:] for x in sbed.get_breaks()]
id = 0
for block in ac.iter_blocks(minsize=minsize):
q, s = list(zip(*block))[:2]
q = [qorder[x][0] for x in q]
s = [sorder[x][0] for x in s]
minq, maxq = min(q), max(q)
mins, maxs = min(s), max(s)
id += 1
qr = Range("0", minq, maxq, maxq - minq, id)
sr = Range("0", mins, maxs, maxs - mins, id)
qranges.append(qr)
sranges.append(sr)
qpads = list(get_segments(qranges, qextra))
spads = list(get_segments(sranges, sextra))
suffix = ".pad.bed"
qpf = opts.qbed.split(".")[0]
spf = opts.sbed.split(".")[0]
qpadfile = qpf + suffix
spadfile = spf + suffix
qnpads, qpadnames = write_PAD_bed(qpadfile, qpf, qpads, qbed)
snpads, spadnames = write_PAD_bed(spadfile, spf, spads, sbed)
qpadbed, spadbed = Bed(qpadfile), Bed(spadfile)
logmp = make_arrays(blastfile, qpadbed, spadbed, qpadnames, spadnames)
m, n = logmp.shape
matrixfile = ".".join((qpf, spf, "logmp.txt"))
fw = open(matrixfile, "w")
header = ["o"] + spadnames
print("\t".join(header), file=fw)
for i in range(m):
row = [qpadnames[i]] + ["{0:.1f}".format(x) for x in logmp[i, :]]
print("\t".join(row), file=fw)
fw.close()
# Run CLUSTER 3.0 (Pearson correlation, average linkage)
cmd = op.join(opts.path, "cluster")
cmd += " -g 2 -e 2 -m a -f {0}".format(matrixfile)
pf = matrixfile.rsplit(".", 1)[0]
cdtfile = pf + ".cdt"
if need_update(matrixfile, cdtfile):
sh(cmd)
def screen(args):
"""
%prog screen anchorfile newanchorfile --qbed=qbedfile --sbed=sbedfile [options]
Extract subset of blocks from anchorfile. Provide several options:
1. Option --ids: a file with IDs, 0-based, comma separated, all in one line.
2. Option --seqids: only allow seqids in this file.
3. Option --seqpairs: only allow seqpairs in this file, one per line, e.g. "Chr01,Chr05".
4. Option --minspan: remove blocks with less span than this.
5. Option --minsize: remove blocks with less number of anchors than this.
"""
p = OptionParser(screen.__doc__)
p.set_beds()
p.add_option("--ids", help="File with block IDs (0-based) [default: %default]")
p.add_option("--seqids", help="File with seqids [default: %default]")
p.add_option("--seqpairs", help="File with seqpairs [default: %default]")
p.add_option("--nointra", action="store_true",
help="Remove intra-chromosomal blocks [default: %default]")
p.add_option("--minspan", default=0, type="int",
help="Only blocks with span >= [default: %default]")
p.add_option("--minsize", default=0, type="int",
help="Only blocks with anchors >= [default: %default]")
p.add_option("--simple", action="store_true",
help="Write simple anchorfile with block ends [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
anchorfile, newanchorfile = args
ac = AnchorFile(anchorfile)
idsfile = opts.ids
seqidsfile = opts.seqids
seqpairsfile = opts.seqpairs
minspan = opts.minspan
minsize = opts.minsize
osimple = opts.simple
nointra = opts.nointra
ids, seqids, seqpairs = None, None, None
if idsfile:
ids = SetFile(idsfile, delimiter=',')
ids = set(int(x) for x in ids)
if seqidsfile:
seqids = SetFile(seqidsfile, delimiter=',')
if seqpairsfile:
fp = open(seqpairsfile)
seqpairs = set()
for row in fp:
a, b = row.strip().split(",")
seqpairs.add((a, b))
seqpairs.add((b, a))
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
blocks = ac.blocks
selected = 0
fw = open(newanchorfile, "w")
for i, block in enumerate(blocks):
if ids and i not in ids:
continue
a, b, scores = zip(*block)
a = [qorder[x] for x in a]
b = [sorder[x] for x in b]
ia, oa = zip(*a)
ib, ob = zip(*b)
aspan = max(ia) - min(ia) + 1
bspan = max(ib) - min(ib) + 1
aseqid = oa[0].seqid
bseqid = ob[0].seqid
if seqids:
if (aseqid not in seqids) or (bseqid not in seqids):
continue
if seqpairs:
if (aseqid, bseqid) not in seqpairs:
continue
if nointra and aseqid == bseqid:
continue
if minsize:
if len(block) < minsize:
continue
if minspan:
if aspan < minspan or bspan < minspan:
continue
selected += 1
print >> fw, "###"
for line in block:
print >> fw, "\t".join(line)
fw.close()
if osimple:
simple([newanchorfile, "--noheader", \
"--qbed=" + qbed.filename, "--sbed=" + sbed.filename])
logging.debug("Before: {0} blocks, After: {1} blocks".\
format(len(blocks), selected))
def omgprepare(args):
"""
%prog omgprepare ploidy anchorsfile blastfile
Prepare to run Sankoff's OMG algorithm to get orthologs.
"""
from jcvi.formats.blast import cscore
from jcvi.formats.base import DictFile
p = OptionParser(omgprepare.__doc__)
p.add_option("--norbh",
action="store_true",
help="Disable RBH hits [default: %default]")
p.add_option("--pctid",
default=0,
type="int",
help="Percent id cutoff for RBH hits [default: %default]")
p.add_option("--cscore",
default=90,
type="int",
help="C-score cutoff for RBH hits [default: %default]")
p.set_stripnames()
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 3:
sys.exit(not p.print_help())
ploidy, anchorfile, blastfile = args
norbh = opts.norbh
pctid = opts.pctid
cs = opts.cscore
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
fp = open(ploidy)
genomeidx = dict((x.split()[0], i) for i, x in enumerate(fp))
fp.close()
ploidy = DictFile(ploidy)
geneinfo(qbed, qorder, genomeidx, ploidy)
geneinfo(sbed, sorder, genomeidx, ploidy)
pf = blastfile.rsplit(".", 1)[0]
cscorefile = pf + ".cscore"
cscore([blastfile, "-o", cscorefile, "--cutoff=0", "--pct"])
ac = AnchorFile(anchorfile)
pairs = set((a, b) for a, b, i in ac.iter_pairs())
logging.debug("Imported {0} pairs from `{1}`.".format(
len(pairs), anchorfile))
weightsfile = pf + ".weights"
fp = open(cscorefile)
fw = open(weightsfile, "w")
npairs = 0
for row in fp:
a, b, c, pct = row.split()
c, pct = float(c), float(pct)
c = int(c * 100)
if (a, b) not in pairs:
if norbh:
continue
if c < cs:
continue
if pct < pctid:
continue
c /= 10 # This severely penalizes RBH against synteny
print >> fw, "\t".join((a, b, str(c)))
npairs += 1
fw.close()
logging.debug("Write {0} pairs to `{1}`.".format(npairs, weightsfile))
def bed(args):
"""
%prog bed anchorsfile
Convert ANCHORS file to BED format.
"""
from collections import defaultdict
from jcvi.compara.synteny import AnchorFile, check_beds
from jcvi.formats.bed import Bed
from jcvi.formats.base import get_number
p = OptionParser(bed.__doc__)
p.add_option(
"--switch",
default=False,
action="store_true",
help="Switch reference and aligned map elements",
)
p.add_option(
"--scale", type="float", help="Scale the aligned map distance by factor"
)
p.set_beds()
p.set_outfile()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
(anchorsfile,) = args
switch = opts.switch
scale = opts.scale
ac = AnchorFile(anchorsfile)
pairs = defaultdict(list)
for a, b, block_id in ac.iter_pairs():
pairs[a].append(b)
qbed, sbed, qorder, sorder, is_self = check_beds(anchorsfile, p, opts)
bd = Bed()
for q in qbed:
qseqid, qstart, qend, qaccn = q.seqid, q.start, q.end, q.accn
if qaccn not in pairs:
continue
for s in pairs[qaccn]:
si, s = sorder[s]
sseqid, sstart, send, saccn = s.seqid, s.start, s.end, s.accn
if switch:
qseqid, sseqid = sseqid, qseqid
qstart, sstart = sstart, qstart
qend, send = send, qend
qaccn, saccn = saccn, qaccn
if scale:
sstart /= scale
try:
newsseqid = get_number(sseqid)
except ValueError:
raise ValueError(
"`{0}` is on `{1}` with no number to extract".format(saccn, sseqid)
)
bedline = "\t".join(
str(x)
for x in (qseqid, qstart - 1, qend, "{0}:{1}".format(newsseqid, sstart))
)
bd.add(bedline)
bd.print_to_file(filename=opts.outfile, sorted=True)
def screen(args):
"""
%prog screen anchorfile newanchorfile --qbed=qbedfile --sbed=sbedfile [options]
Extract subset of blocks from anchorfile. Provide several options:
1. Option --ids: a file with IDs, 0-based, comma separated, all in one line.
2. Option --seqids: only allow seqids in this file.
3. Option --seqpairs: only allow seqpairs in this file, one per line, e.g. "Chr01,Chr05".
4. Option --minspan: remove blocks with less span than this.
5. Option --minsize: remove blocks with less number of anchors than this.
"""
p = OptionParser(screen.__doc__)
p.set_beds()
p.add_option("--ids",
help="File with block IDs (0-based) [default: %default]")
p.add_option("--seqids", help="File with seqids [default: %default]")
p.add_option("--seqpairs", help="File with seqpairs [default: %default]")
p.add_option("--nointra",
action="store_true",
help="Remove intra-chromosomal blocks [default: %default]")
p.add_option("--minspan",
default=0,
type="int",
help="Only blocks with span >= [default: %default]")
p.add_option("--minsize",
default=0,
type="int",
help="Only blocks with anchors >= [default: %default]")
p.add_option(
"--simple",
action="store_true",
help="Write simple anchorfile with block ends [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
anchorfile, newanchorfile = args
ac = AnchorFile(anchorfile)
idsfile = opts.ids
seqidsfile = opts.seqids
seqpairsfile = opts.seqpairs
minspan = opts.minspan
minsize = opts.minsize
osimple = opts.simple
nointra = opts.nointra
ids, seqids, seqpairs = None, None, None
if idsfile:
ids = SetFile(idsfile, delimiter=',')
ids = set(int(x) for x in ids)
if seqidsfile:
seqids = SetFile(seqidsfile, delimiter=',')
if seqpairsfile:
fp = open(seqpairsfile)
seqpairs = set()
for row in fp:
a, b = row.strip().split(",")
seqpairs.add((a, b))
seqpairs.add((b, a))
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
blocks = ac.blocks
selected = 0
fw = open(newanchorfile, "w")
for i, block in enumerate(blocks):
if ids and i not in ids:
continue
a, b, scores = zip(*block)
a = [qorder[x] for x in a]
b = [sorder[x] for x in b]
ia, oa = zip(*a)
ib, ob = zip(*b)
aspan = max(ia) - min(ia) + 1
bspan = max(ib) - min(ib) + 1
aseqid = oa[0].seqid
bseqid = ob[0].seqid
if seqids:
if (aseqid not in seqids) or (bseqid not in seqids):
continue
if seqpairs:
if (aseqid, bseqid) not in seqpairs:
continue
if nointra and aseqid == bseqid:
continue
if minsize:
if len(block) < minsize:
continue
if minspan:
if aspan < minspan or bspan < minspan:
continue
selected += 1
print >> fw, "###"
for line in block:
print >> fw, "\t".join(line)
fw.close()
if osimple:
simple([newanchorfile, "--noheader", \
"--qbed=" + qbed.filename, "--sbed=" + sbed.filename])
logging.debug("Before: {0} blocks, After: {1} blocks".\
format(len(blocks), selected))
def depth(args):
"""
%prog depth anchorfile --qbed qbedfile --sbed sbedfile
Calculate the depths in the two genomes in comparison, given in --qbed and
--sbed. The synteny blocks will be layered on the genomes, and the
multiplicity will be summarized to stderr.
"""
from jcvi.utils.range import range_depth
p = OptionParser(depth.__doc__)
p.add_option("--depthfile",
help="Generate file with gene and depth [default: %default]")
p.add_option("--histogram", default=False, action="store_true",
help="Plot histograms in PDF")
p.add_option("--xmax", type="int", help="x-axis maximum to display in plot")
p.add_option("--title", default=None, help="Title to display in plot")
p.add_option("--quota", help="Force to use this quota, e.g. 1:1, 1:2 ...")
p.set_beds()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
anchorfile, = args
qbed, sbed, qorder, sorder, is_self = check_beds(anchorfile, p, opts)
depthfile = opts.depthfile
ac = AnchorFile(anchorfile)
qranges = []
sranges = []
blocks = ac.blocks
for ib in blocks:
q, s, t = zip(*ib)
q = [qorder[x] for x in q]
s = [sorder[x] for x in s]
qrange = (min(q)[0], max(q)[0])
srange = (min(s)[0], max(s)[0])
qranges.append(qrange)
sranges.append(srange)
if is_self:
qranges.append(srange)
qgenome = op.basename(qbed.filename).split(".")[0]
sgenome = op.basename(sbed.filename).split(".")[0]
qtag = "Genome {0} depths".format(qgenome)
print("{}:".format(qtag), file=sys.stderr)
dsq, details = range_depth(qranges, len(qbed))
if depthfile:
fw = open(depthfile, "w")
write_details(fw, details, qbed)
if is_self:
return
stag = "Genome {0} depths".format(sgenome)
print("{}:".format(stag), file=sys.stderr)
dss, details = range_depth(sranges, len(sbed))
if depthfile:
write_details(fw, details, sbed)
fw.close()
logging.debug("Depth written to `{0}`.".format(depthfile))
if not opts.histogram:
return
from jcvi.graphics.base import plt, quickplot_ax, savefig, normalize_axes
# Plot two histograms one for query genome, one for subject genome
plt.figure(1, (6, 3))
f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
xmax = opts.xmax or max(4, max(dsq.keys() + dss.keys()))
if opts.quota:
speak, qpeak = opts.quota.split(":")
qpeak, speak = int(qpeak), int(speak)
else:
qpeak = find_peak(dsq)
speak = find_peak(dss)
qtag = "# of {} blocks per {} gene".format(sgenome, qgenome)
stag = "# of {} blocks per {} gene".format(qgenome, sgenome)
quickplot_ax(ax1, dss, 0, xmax, stag, ylabel="Percentage of genome",
highlight=range(1, speak + 1))
quickplot_ax(ax2, dsq, 0, xmax, qtag, ylabel=None,
highlight=range(1, qpeak + 1))
title = opts.title or "{} vs {} syntenic depths\n{}:{} pattern"\
.format(qgenome, sgenome, speak, qpeak)
root = f.add_axes([0, 0, 1, 1])
vs, pattern = title.split('\n')
root.text(.5, .97, vs, ha="center", va="center", color="darkslategray")
root.text(.5, .925, pattern, ha="center", va="center",
color="tomato", size=16)
print(title, file=sys.stderr)
normalize_axes(root)
pf = anchorfile.rsplit(".", 1)[0] + ".depth"
image_name = pf + ".pdf"
savefig(image_name)
