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"""prepare data for CoRaL"""
from __future__ import print_function
import os.path as op
from collections import Counter
import pybedtools
from seqcluster.libs import utils
from seqcluster.libs.do import run, find_cmd
from seqcluster.function.rnafold import calculate_structure
min_trimmed_read_len = 14
max_trimmed_read_len = 50
seg_threshold = 2
seg_maxgap = 44
seg_minrun = min_trimmed_read_len
antisense_min_reads = 0
def prepare_bam(bam_in, precursors):
"""
Clean BAM file to keep only position inside the bigger cluster
"""
# use pybedtools to keep valid positions
# intersect option with -b bigger_cluster_loci
a = pybedtools.BedTool(bam_in)
b = pybedtools.BedTool(precursors)
c = a.intersect(b, u=True)
out_file = utils.splitext_plus(op.basename(bam_in))[0] + "_clean.bam"
c.saveas(out_file)
return op.abspath(out_file)
def _select_anno(annotation):
"""
Select annotation from multiple elements
"""
options = annotation.split(",")
return options[0]
def _reorder_columns(bed_file):
"""
Reorder columns to be compatible with CoRaL
"""
new_bed = utils.splitext_plus(bed_file)[0] + '_order.bed'
with open(bed_file) as in_handle:
with open(new_bed, 'w') as out_handle:
for line in in_handle:
cols = line.strip().split("\t")
cols[3] = _select_anno(cols[3]) + "_" + cols[4]
cols[4] = "0"
print("\t".join(cols), file=out_handle, end="")
return new_bed
def _fix_score_column(cov_file):
"""
Move counts to score columns in bed file
"""
new_cov = utils.splitext_plus(cov_file)[0] + '_fix.cov'
with open(cov_file) as in_handle:
with open(new_cov, 'w') as out_handle:
for line in in_handle:
cols = line.strip().split("\t")
cols[4] = cols[6]
print("\t".join(cols[0:6]), file=out_handle, end="")
return new_cov
def detect_regions(bam_in, bed_file, out_dir, prefix):
"""
Detect regions using first CoRaL module
"""
bed_file = _reorder_columns(bed_file)
counts_reads_cmd = ("coverageBed -s -counts -b {bam_in} "
"-a {bed_file} | sort -k4,4 "
"> {out_dir}/loci.cov")
# with tx_tmpdir() as temp_dir:
with utils.chdir(out_dir):
run(counts_reads_cmd.format(min_trimmed_read_len=min_trimmed_read_len, max_trimmed_read_len=max_trimmed_read_len, **locals()), "Run counts_reads")
loci_file = _fix_score_column(op.join(out_dir, "loci.cov"))
return loci_file
def _order_antisense_column(cov_file, min_reads):
"""
Move counts to score columns in bed file
"""
new_cov = op.join(op.dirname(cov_file), 'feat_antisense.txt')
with open(cov_file) as in_handle:
with open(new_cov, 'w') as out_handle:
print("name\tantisense", file=out_handle, end="")
for line in in_handle:
cols = line.strip().split("\t")
cols[6] = 0 if cols[6] < min_reads else cols[6]
print("%s\t%s" % (cols[3], cols[6]), file=out_handle, end="")
return new_cov
def _reads_per_position(bam_in, loci_file, out_dir):
"""
Create input for compute entropy
"""
data = Counter()
a = pybedtools.BedTool(bam_in)
b = pybedtools.BedTool(loci_file)
c = a.intersect(b, s=True, bed=True, wo=True)
for line in c:
end = int(line[1]) + 1 + int(line[2]) if line[5] == "+" else int(line[1]) + 1
start = int(line[1]) + 1 if line[5] == "+" else int(line[1]) + 1 + int(line[2])
side5 = "%s\t5p\t%s" % (line[15], start)
side3 = "%s\t3p\t%s" % (line[15], end)
data[side5] += 1
data[side3] += 1
counts_reads = op.join(out_dir, 'locus_readpos.counts')
with open(counts_reads, 'w') as out_handle:
for k in data:
print(k, file=out_handle, end="")
return counts_reads
def create_features(bam_in, loci_file, reference, out_dir):
"""
Use feature extraction module from CoRaL
"""
lenvec_plus = op.join(out_dir, 'genomic_lenvec.plus')
lenvec_minus = op.join(out_dir, 'genomic_lenvec.minus')
compute_genomic_cmd = ("compute_genomic_lenvectors "
"{bam_in} {lenvec_plus} "
"{lenvec_minus} "
"{min_len} "
"{max_len} ")
index_genomic_cmd = ("index_genomic_lenvectors "
"{lenvec} ")
genomic_lenvec = op.join(out_dir, 'genomic_lenvec')
feat_len_file = op.join(out_dir, 'feat_lengths.txt')
compute_locus_cmd = ("compute_locus_lenvectors "
"{loci_file} "
"{genomic_lenvec} "
"{min_len} "
"{max_len} "
"> {feat_len_file}")
cov_S_file = op.join(out_dir, 'loci.cov_anti')
coverage_anti_cmd = ("coverageBed -S -counts -b "
"{bam_in} -a {loci_file} "
"> {cov_S_file}")
feat_posentropy = op.join(out_dir, 'feat_posentropy.txt')
entropy_cmd = ("compute_locus_entropy.rb "
"{counts_reads} "
"> {feat_posentropy}")
with utils.chdir(out_dir):
run(compute_genomic_cmd.format(min_len=min_trimmed_read_len, max_len=max_trimmed_read_len, **locals()), "Run compute_genomic")
run(index_genomic_cmd.format(lenvec=lenvec_plus), "Run index in plus")
run(index_genomic_cmd.format(lenvec=lenvec_minus), "Run index in minus")
run(compute_locus_cmd.format(min_len=min_trimmed_read_len, max_len=max_trimmed_read_len, **locals()), "Run compute locus")
run(coverage_anti_cmd.format(**locals()), "Run coverage antisense")
feat_antisense = _order_antisense_column(cov_S_file, min_trimmed_read_len)
counts_reads = _reads_per_position(bam_in, loci_file, out_dir)
run(entropy_cmd.format(**locals()), "Run entropy")
rnafold = calculate_structure(loci_file, reference)
def prepare_ann_file(args):
"""
Create custom ann_file for Coral
"""
def download_hsa_file(args):
"""
In case of human, download from server
"""
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