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#!/usr/bin/env python
"""BLAST Reciprocal Best Hit (RBH) from two FASTA input files.
Run " -h" to see the help text, or read the associated
blast_rbh.xml and README.rst files which are available on GitHub at:
This requires Python and the NCBI BLAST+ tools to be installed
and on the $PATH.
You can also run this tool via Galaxy using the "blast_rbh.xml"
definition file. This is available as a package on the Galaxy
Tool Shed:
# TODO - Output more columns, e.g. pident, qcovs, descriptions?
# TODO - Use new -qcov_hsp_perc option in BLAST+ 2.2.30 to filter
# results, rather than doing minimum HSP coverage in Python.
# [Not doing this right now as would break on older BLAST+]
from __future__ import print_function
import os
import shutil
import sys
import tempfile
from optparse import OptionParser
def run(cmd):
"""Run the given command line string."""
return_code = os.system(cmd)
if return_code:
sys.exit("Error %i from: %s" % (return_code, cmd))
if "--version" in sys.argv[1:]:
# TODO - Capture version of BLAST+ binaries too?
print("BLAST RBH v0.1.11")
threads = int(os.environ.get("GALAXY_SLOTS", "1"))
except ValueError:
threads = 1
assert 1 <= threads, threads
# Parse Command Line
usage = """Use as follows:
$ python [options] A.fasta B.fasta
Many of the options are required. Example with proteins and blastp:
$ python -a prot -t blasp -o output.tsv protA.fasta protB.fasta
There is additional guidance in the help text in the blast_rbh.xml file,
which is shown to the user via the Galaxy interface to this tool.
parser = OptionParser(usage=usage)
parser.add_option("-a", "--alphabet", dest="dbtype",
help="Alphabet type (nucl or prot; required)")
parser.add_option("-t", "--task", dest="task",
help="BLAST task (e.g. blastp, blastn, megablast; required)")
parser.add_option("-i", "--identity", dest="min_identity",
help="Minimum percentage identity (optional, default 70)")
parser.add_option("-c", "--coverage", dest="min_coverage",
help="Minimum HSP coverage (optional, default 50)")
parser.add_option("--nr", dest="nr", default=False, action="store_true",
help="Preprocess FASTA files to collapse identitical "
"entries (make sequences non-redundant)")
parser.add_option("-o", "--output", dest="output",
default=None, metavar="FILE",
help="Output filename (required)")
parser.add_option("--threads", dest="threads",
help="Number of threads when running BLAST. Defaults to the "
"$GALAXY_SLOTS environment variable if set, or 1.")
options, args = parser.parse_args()
if len(args) != 2:
sys.exit("Expects two input FASTA filenames")
fasta_a, fasta_b = args
if not os.path.isfile(fasta_a):
sys.exit("Missing input file for species A: %r" % fasta_a)
if not os.path.isfile(fasta_b):
sys.exit("Missing input file for species B: %r" % fasta_b)
if os.path.abspath(fasta_a) == os.path.abspath(fasta_b):
self_comparison = True
print("Doing self comparison; ignoring self matches.")
self_comparison = False
if not options.output:
sys.exit("Output filename required, e.g. -o")
out_file = options.output
min_identity = float(options.min_identity)
except ValueError:
sys.exit("Expected number between 0 and 100 for minimum identity, not %r" % min_identity)
if not (0 <= min_identity <= 100):
sys.exit("Expected minimum identity between 0 and 100, not %0.2f" % min_identity)
min_coverage = float(options.min_coverage)
except ValueError:
sys.exit("Expected number between 0 and 100 for minimum coverage, not %r" % min_coverage)
if not (0 <= min_coverage <= 100):
sys.exit("Expected minimum coverage between 0 and 100, not %0.2f" % min_coverage)
if not options.task:
sys.exit("Missing BLAST task, e.g. -t blastp")
blast_type = options.task
if not options.dbtype:
sys.exit("Missing database type, -a nucl, or -a prot")
dbtype = options.dbtype
if dbtype == "nucl":
if blast_type in ["megablast", "blastn", "blastn-short", "dc-megablast"]:
blast_cmd = "blastn -task %s" % blast_type
elif blast_type == "tblastx":
blast_cmd = "tblastx"
sys.exit("Invalid BLAST type for BLASTN: %r" % blast_type)
elif dbtype == "prot":
if blast_type not in ["blastp", "blastp-fast", "blastp-short"]:
sys.exit("Invalid BLAST type for BLASTP: %r" % blast_type)
blast_cmd = "blastp -task %s" % blast_type
sys.exit("Expected 'nucl' or 'prot' for BLAST database type, not %r" % blast_type)
threads = int(options.threads)
except ValueError:
sys.exit("Expected positive integer for number of threads, not %r" % options.threads)
if threads < 1:
sys.exit("Expected positive integer for number of threads, not %r" % threads)
makeblastdb_exe = "makeblastdb"
base_path = tempfile.mkdtemp()
tmp_a = os.path.join(base_path, "SpeciesA.fasta")
db_a = os.path.join(base_path, "SpeciesA")
a_vs_b = os.path.join(base_path, "A_vs_B.tabular")
if self_comparison:
tmp_b = tmp_a
db_b = db_a
b_vs_a = a_vs_b
tmp_b = os.path.join(base_path, "SpeciesB.fasta")
db_b = os.path.join(base_path, "SpeciesB")
b_vs_a = os.path.join(base_path, "B_vs_A.tabular")
log = os.path.join(base_path, "blast.log")
cols = "qseqid sseqid bitscore pident qcovhsp qlen length" # Or qcovs?
c_query = 0
c_match = 1
c_score = 2
c_identity = 3
c_coverage = 4
c_qlen = 5
c_length = 6
tie_warning = 0
def best_hits(blast_tabular, ignore_self=False):
"""Iterate over BLAST tabular output, returns best hits as 2-tuples.
Each return value is (query name, tuple of value for the best hit).
Tied best hits to different sequences are NOT returned.
One hit is returned for tied best hits to the same sequence
(e.g. repeated domains).
global tie_warning
current = None
best_score = None
best = None
col_count = len(cols.split())
with open(blast_tabular) as h:
for line in h:
if line.startswith("#"):
parts = line.rstrip("\n").split("\t")
if len(parts) != col_count:
# Using NCBI BLAST+ 2.2.27 the undefined field is ignored
# Even NCBI BLAST+ 2.5.0 silently ignores unknown fields :(
sys.exit("Old version of NCBI BLAST? Expected %i columns, got %i:\n%s\n"
"Note the qcovhsp field was only added in version 2.2.28\n"
% (col_count, len(parts), line))
if float(parts[c_identity]) < min_identity or float(parts[c_coverage]) < min_coverage:
a = parts[c_query]
b = parts[c_match]
if ignore_self and a == b:
score = float(parts[c_score])
qlen = int(parts[c_qlen])
length = int(parts[c_length])
# print("Considering hit for %s to %s with score %s..." % (a, b, score))
if current is None:
# First hit
assert best is None
assert best_score is None
best = dict()
# Now append this hit...
elif a != current:
# New hit
if len(best) == 1:
# Unambiguous (no tied matches)
yield current, list(best.values())[0]
# print("%s has %i equally good hits: %s" % (a, len(best), ", ".join(best)))
tie_warning += 1
best = dict()
# Now append this hit...
elif score < best_score:
# print("No improvement for %s, %s < %s" % (a, score, best_score))
elif score > best_score:
# This is better, discard old best
best = dict()
# Now append this hit...
# print("Tied best hits for %s" % a)
assert best_score == score
# Now append this hit...
current = a
best_score = score
# This will collapse two equally good hits to the same target (e.g. duplicated domain)
best[b] = (b, score, parts[c_score], parts[c_identity], parts[c_coverage], qlen, length)
# Best hit for final query, if unambiguous:
if current is not None:
if len(best) == 1:
yield current, list(best.values())[0]
# print("%s has %i equally good hits: %s" % (a, len(best), ", ".join(best)))
tie_warning += 1
def check_duplicate_ids(filename):
"""Check for duplicate identifiers in a FASTA file."""
# Copied from tools/ncbi_blast_plus/
# TODO - just use Biopython's FASTA parser?
if not os.path.isfile(filename):
sys.stderr.write("Missing FASTA file %r\n" % filename)
identifiers = set()
handle = open(filename)
for line in handle:
if line.startswith(">"):
# The split will also take care of the new line character,
# e.g. ">test\n" and ">test description here\n" both give "test"
seq_id = line[1:].split(None, 1)[0]
if seq_id in identifiers:
sys.stderr.write("Repeated identifiers, e.g. %r\n" % seq_id)
def make_nr(input_fasta, output_fasta, sep=";"):
"""Make the sequences in a FASTA file non-redundant."""
# TODO - seq-hash based to avoid loading everything into RAM?
by_seq = dict()
from Bio import SeqIO
except ImportError:
sys.exit("Missing Biopython")
for record in SeqIO.parse(input_fasta, "fasta"):
s = str(record.seq).upper()
except KeyError:
by_seq[s] = []
unique = 0
representatives = dict()
duplicates = set()
for cluster in by_seq.values():
if len(cluster) > 1:
representatives[cluster[0]] = cluster
unique += 1
del by_seq
if duplicates:
# TODO - refactor as a generator with single SeqIO.write(...) call
with open(output_fasta, "w") as handle:
for record in SeqIO.parse(input_fasta, "fasta"):
if in representatives:
cluster = representatives[] = sep.join(cluster)
record.description = "representing %i records" % len(cluster)
elif in duplicates:
SeqIO.write(record, handle, "fasta")
print("%i unique entries; removed %i duplicates leaving %i representative records"
% (unique, len(duplicates), len(representatives)))
os.symlink(os.path.abspath(input_fasta), output_fasta)
print("No perfect duplicates in file, %i unique entries" % unique)
# print("Starting...")
if not self_comparison:
make_nr(fasta_a, tmp_a)
if not self_comparison:
make_nr(fasta_b, tmp_b)
fasta_a = tmp_a
fasta_b = tmp_b
# TODO - Report log in case of error?
run('%s -dbtype %s -in "%s" -out "%s" -logfile "%s"' % (makeblastdb_exe, dbtype, fasta_a, db_a, log))
if not self_comparison:
run('%s -dbtype %s -in "%s" -out "%s" -logfile "%s"' % (makeblastdb_exe, dbtype, fasta_b, db_b, log))
# print("BLAST databases prepared.")
run('%s -query "%s" -db "%s" -out "%s" -outfmt "6 %s" -num_threads %i'
% (blast_cmd, fasta_a, db_b, a_vs_b, cols, threads))
# print("BLAST species A vs species B done.")
if not self_comparison:
run('%s -query "%s" -db "%s" -out "%s" -outfmt "6 %s" -num_threads %i'
% (blast_cmd, fasta_b, db_a, b_vs_a, cols, threads))
# print("BLAST species B vs species A done.")
best_b_vs_a = dict(best_hits(b_vs_a, self_comparison))
count = 0
outfile = open(out_file, 'w')
for a, (b, a_score_float, a_score_str,
a_identity_str, a_coverage_str, a_qlen, a_length) in best_hits(a_vs_b, self_comparison):
if b not in best_b_vs_a:
# Match b has no best hit
a2, b_score_float, b_score_str, b_identity_str, b_coverage_str, b_qlen, b_length = best_b_vs_a[b]
if a != a2:
# Not an RBH
# Start with IDs, lengths, coverage
values = [a, b, a_qlen, b_qlen, a_coverage_str, b_coverage_str]
# Alignment length was an integer so don't care about original string
values.append(min(a_length, b_length))
# Output the original string versions of the scores
if float(a_identity_str) < float(b_identity_str):
if a_score_float < b_score_float:
outfile.write("%s\t%s\t%i\t%i\t%s\t%s\t%i\t%s\t%s\n" % tuple(values))
count += 1
print("Done, %i RBH found" % count)
if tie_warning:
sys.stderr.write("Warning: Sequences with tied best hits found, you may have duplicates/clusters\n")
# Remove temp files...