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"""functions for explore tool"""
from __future__ import print_function
from collections import defaultdict
import json, itertools
import tempfile, os, contextlib, shutil
import operator
from seqcluster.libs.sam2bed import makeBED
import logging
from seqcluster.libs.do import find_cmd, run
import pysam
import pybedtools
from Bio import pairwise2
from Bio.Seq import Seq
logger = logging.getLogger('read')
@contextlib.contextmanager
def make_temp_directory(remove=True):
temp_dir = tempfile.mkdtemp()
yield temp_dir
shutil.rmtree(temp_dir)
def load_data(in_file):
"""load json file from seqcluster cluster"""
with open(in_file) as in_handle:
return json.load(in_handle)
def write_data(data, out_file):
"""write json file from seqcluster cluster"""
with open(out_file, 'w') as handle_out:
handle_out.write(json.dumps([data], skipkeys=True, indent=2))
def get_sequences_from_cluster(c1, c2, data):
"""get all sequences from on cluster"""
seqs1 = data[c1]['seqs']
seqs2 = data[c2]['seqs']
seqs = list(set(seqs1 + seqs2))
names = []
for s in seqs:
if s in seqs1 and s in seqs2:
names.append("both")
elif s in seqs1:
names.append(c1)
else:
names.append(c2)
return seqs, names
def get_precursors_from_cluster(c1, c2, data):
loci1 = data[c1]['loci']
loci2 = data[c2]['loci']
return {c1:loci1, c2:loci2}
def map_to_precursors(seqs, names, loci, out_file, args):
"""map sequences to precursors with razers3"""
with make_temp_directory() as temp:
pre_fasta = os.path.join(temp, "pre.fa")
seqs_fasta = os.path.join(temp, "seqs.fa")
out_sam = os.path.join(temp, "out.sam")
pre_fasta = get_loci_fasta(loci, pre_fasta, args.ref)
out_precursor_file = out_file.replace("tsv", "fa")
seqs_fasta = get_seqs_fasta(seqs, names, seqs_fasta)
# print(open(pre_fasta).read().split("\n")[1])
if find_cmd("razers3"):
cmd = "razers3 -dr 2 -i 80 -rr 90 -f -o {out_sam} {temp}/pre.fa {seqs_fasta}"
run(cmd.format(**locals()))
out_file = read_alignment(out_sam, loci, seqs, out_file)
shutil.copy(pre_fasta, out_precursor_file)
return out_file
def precursor_sequence(loci, reference):
"""Get sequence from genome"""
region = "%s\t%s\t%s\t.\t.\t%s" % (loci[1], loci[2], loci[3], loci[4])
precursor = pybedtools.BedTool(str(region), from_string=True).sequence(fi=reference, s=True)
return open(precursor.seqfn).read().split("\n")[1]
def map_to_precursors_on_fly(seqs, names, loci, args):
"""map sequences to precursors with franpr algorithm to avoid writting on disk"""
precursor = precursor_sequence(loci, args.ref).upper()
dat = dict()
for s, n in itertools.izip(seqs, names):
res = pyMatch.Match(precursor, str(s), 1, 3)
if res > -1:
dat[n] = [res, res + len(s)]
logger.debug("mapped in %s: %s out of %s" % (loci, len(dat), len(seqs)))
return dat
def _align(x, y, local = False):
"""
https://medium.com/towards-data-science/pairwise-sequence-alignment-using-biopython-d1a9d0ba861f
"""
if local:
aligned_x = pairwise2.align.localxx(x, y)
else:
aligned_x = pairwise2.align.globalms(x, y, 1, -1, -1, -0.5)
if aligned_x:
sorted_alignments = sorted(aligned_x, key=operator.itemgetter(2))
e = enumerate(sorted_alignments[0][0])
nts = [i for i,c in e if c != "-"]
return [min(nts), max(nts)]
def map_to_precursor_biopython(seqs, names, loci, args):
"""map the sequences using biopython package"""
precursor = precursor_sequence(loci, args.ref).upper()
dat = dict()
for s, n in zip(seqs, names):
res = _align(str(s), precursor)
if res:
dat[n] = res
logger.debug("mapped in %s: %s out of %s" % (loci, len(dat), len(seqs)))
return dat
def deprecated_map_to_precursors(seqs, names, loci, out_file, args):
"""map sequences to precursors with bowtie"""
with make_temp_directory() as temp:
pre_fasta = os.path.join(temp, "pre.fa")
seqs_fasta = os.path.join(temp, "seqs.fa")
out_sam = os.path.join(temp, "out.sam")
pre_fasta = get_loci_fasta(loci, pre_fasta, args.ref)
out_precursor_file = out_file.replace("tsv", "fa")
seqs_fasta = get_seqs_fasta(seqs, names, seqs_fasta)
if find_cmd("bowtie2-build"):
cmd = "bowtie2-build -f {pre_fasta} {temp}/pre"
run(cmd.format(**locals()))
cmd = "bowtie2 -a --rdg 7,3 --mp 4 --end-to-end -D 20 -R 3 -N 0 -i S,1,0.8 -L 3 -f -x {temp}/pre -U {seqs_fasta} -S {out_sam}"
run(cmd.format(**locals()))
out_file = read_alignment(out_sam, loci, seqs, out_file)
shutil.copy(pre_fasta, out_precursor_file)
return out_file
def get_seqs_fasta(seqs, names, out_fa):
"""get fasta from sequences"""
with open(out_fa, 'w') as fa_handle:
for s, n in itertools.izip(seqs, names):
print(">cx{1}-{0}\n{0}".format(s, n), file=fa_handle)
return out_fa
def get_fasta(bed_file, ref, out_fa):
"""Run bedtools to get fasta from bed file"""
cmd = "bedtools getfasta -s -fi {ref} -bed {bed_file} -fo {out_fa}"
run(cmd.format(**locals()))
def get_loci_fasta(loci, out_fa, ref):
"""get fasta from precursor"""
if not find_cmd("bedtools"):
raise ValueError("Not bedtools installed")
with make_temp_directory() as temp:
bed_file = os.path.join(temp, "file.bed")
for nc, loci in loci.iteritems():
for l in loci:
with open(bed_file, 'w') as bed_handle:
logger.debug("get_fasta: loci %s" % l)
nc, c, s, e, st = l
print("{0}\t{1}\t{2}\t{3}\t{3}\t{4}".format(c, s, e, nc, st), file=bed_handle)
get_fasta(bed_file, ref, out_fa)
return out_fa
def read_alignment(out_sam, loci, seqs, out_file):
"""read which seqs map to which loci and
return a tab separated file"""
hits = defaultdict(list)
with open(out_file, "w") as out_handle:
samfile = pysam.Samfile(out_sam, "r")
for a in samfile.fetch():
if not a.is_unmapped:
nm = int([t[1] for t in a.tags if t[0] == "NM"][0])
a = makeBED(a)
if not a:
continue
ref, locus = get_loci(samfile.getrname(int(a.chr)), loci)
hits[a.name].append((nm, "%s %s %s %s %s %s" % (a.name, a.name.split("-")[0], locus, ref, a.start, a.end)))
for hit in hits.values():
nm = hit[0][0]
for l in hit:
if nm == l[0]:
print(l[1], file=out_handle)
return out_file
def get_loci(name, loci):
for nc in loci:
for l in loci[nc]:
lname = "{0}:{1}-{2}({3})".format(l[1], l[2], l[3], l[4])
if name == lname:
return nc, l[0]
def plot_positions():
return True
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