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uniref_annotator.py
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#!/usr/bin/env python
from __future__ import print_function
import os
import sys
import argparse
import csv
from utils import say, die, check_path, which, Hit, translate_fasta, try_open
# ---------------------------------------------------------------
# constants
# ---------------------------------------------------------------
c_min_coverage = 0.80
#c_diamond_filters = "--query-cover {COV:d} --subject-cover {COV:d} --max-target-seqs 1"
#c_diamond_filters = c_diamond_filters.format( COV = int( 100 * c_min_coverage ) )
c_diamond_filters = "--evalue 1"
c_output_format = "6 qseqid sseqid pident qlen qstart qend slen sstart send evalue"
# ---------------------------------------------------------------
# cli
# ---------------------------------------------------------------
description = """
A script to annotate a fasta file of coding sequence against
HUMAnN2-formatted UniRef90/UniRef50 databases. Approximates the UniRef
clustering conventions in that query and target must exceed 80% mutual coverage
with the corresponding percent identity (e.g. 90 for UniRef90).
"""
def get_args( ):
parser = argparse.ArgumentParser( description=description )
parser.add_argument( "fasta",
help="Sequences to annotate",
)
parser.add_argument( "--seqtype",
choices=["cds", "nuc", "prot"],
metavar="<cds/nuc/prot>",
default="cds",
help="Sequence type [default: cds]",
)
parser.add_argument( "--diamond",
metavar="<path>",
default="diamond",
help="Path to diamond binary [default: in PATH]",
)
parser.add_argument( "--uniref90db",
metavar="<path>",
required=True,
help="Path to HUMAnN2-formatted UniRef90 database",
)
parser.add_argument( "--uniref50db",
metavar="<path>",
required=True,
help="Path to HUMAnN2-formatted UniRef50 database",
)
parser.add_argument( "--transitive-map",
metavar="<path>",
help="Path to UniRef90->UniRef50 idmapping file (optional)",
)
parser.add_argument( "--temp",
metavar="<path>",
default=".",
help="Path for temp files [default: .]",
)
parser.add_argument( "--out",
metavar="<path>",
default=None,
help="Path for output file [default: <fasta>.annotated]",
)
parser.add_argument( "--force-search",
action="store_true",
help="Rerun searches, even if expected outputs exist",
)
parser.add_argument( "--diamond-options",
metavar="<string>",
help="Additional options to pass to diamond, e.g. --threads",
)
args = parser.parse_args( )
return args
# ---------------------------------------------------------------
# utils
# ---------------------------------------------------------------
def get_mode( path ):
mode = None
for test in "90 50".split( ):
test = "uniref" + test
if test in path.lower( ):
mode = test
if mode is None:
die( "Could not infer mode from path: {}".format( path ) )
return mode
def uniref_search( diamond=None, database=None, query=None, seqtype=None, temp=None, diamond_options=None, force_search=False ):
if which( diamond ) is None:
die( "<diamond> is not executable as: {}".format( diamond ) )
for path in [database, query, temp]:
check_path( path )
binary = {"nuc":"blastx", "prot":"blastp"}[seqtype]
mode = get_mode( database )
results = os.path.split( query )[1]
results = os.path.join( temp, results )
results = ".".join( [results, mode, "hits"] )
command = [
diamond,
binary,
"--db", database,
"--query", query,
"--outfmt", c_output_format,
"--tmpdir", temp,
"--out", results,
"--id", get_mode( results ).replace( "uniref", "" ),
c_diamond_filters,
]
command = " ".join( [str( k ) for k in command] )
command += (" " + diamond_options) if diamond_options is not None else ""
if force_search or not os.path.exists( results ):
say( "Executing:\n ", command )
os.system( command )
else:
say( "Using existing results file:\n ", results )
return results
def parse_results( results ):
say( "Parsing results file:\n ", results )
check_path( results )
mapping = {}
mode = get_mode( results )
min_pident = float( mode.replace( "uniref", "" ) )
with try_open( results ) as fh:
for row in csv.reader( fh, csv.excel_tab ):
h = Hit( row, config=c_output_format )
if h.qseqid not in mapping:
if h.pident >= min_pident and h.mcov >= c_min_coverage:
uniref = h.sseqid.split( "|" )[0]
mapping[h.qseqid] = uniref
return mapping
def trans_mapping( uniref90map, p_trans_map ):
say( "Loading transitive mapping file:\n ", p_trans_map )
check_path( p_trans_map )
overrides = {}
uniref90map_r = {}
for header, uniref90 in uniref90map.items( ):
uniref90map_r.setdefault( uniref90, set( ) ).add( header )
with try_open( p_trans_map ) as fh:
for row in csv.reader( fh, csv.excel_tab ):
uniref90, uniref50 = row
headers = uniref90map_r.get( uniref90, set( ) )
for h in headers:
overrides[h] = uniref50
return overrides
def reannotate( query=None, out=None, uniref90map=None, uniref50map=None, overrides=None ):
say( "Writing new output file:\n ", out )
oh = try_open( out, "w" )
ntot, nmap90, ninf50, nmap50 = [0 for i in range( 4 )]
with try_open( query ) as fh:
for line in fh:
line = line.strip( )
if line == "":
continue
elif line[0] != ">":
print( line, file=oh )
else:
# diamond breaks the header on whitespace
header = line[1:].split( )[0]
ntot += 1
uniref90code = "UniRef90_unknown"
if header in uniref90map:
uniref90code = uniref90map[header]
nmap90 += 1
uniref50code = "UniRef50_unknown"
if header in overrides:
uniref50code = overrides[header]
ninf50 += 1
elif header in uniref50map:
uniref50code = uniref50map[header]
nmap50 += 1
print( "|".join( [line, uniref90code, uniref50code] ), file=oh )
oh.close( )
# report
say( "Summary of annotations:" )
say( " Genes in input FASTA: {:,}".format( ntot ) )
say( " UniRef90 codes assigned: {:,} ({:.1f}%)".format(
nmap90, 100 * nmap90 / float( ntot ) ) )
say( " UniRef50 codes assigned: {:,} ({:.1f}%)".format(
nmap50 + ninf50, 100 * (nmap50 + ninf50) / float( ntot ) ) )
say( " UniRef50 codes inferred from UniRef90 codes: {:,} ({:.1f}%)".format(
ninf50, 100 * ninf50 / float( ntot ) ) )
# done
return None
# ---------------------------------------------------------------
# main
# ---------------------------------------------------------------
def main( ):
args = get_args( )
# set defaults
if args.out is None:
args.out = args.fasta + ".annotated"
# translate fasta?
query = args.fasta
if args.seqtype == "cds":
query = os.path.split( query )[1]
query = os.path.join( args.temp, query )
query = query + ".translated"
say( "Translating input fasta to:\n ", query )
translate_fasta( args.fasta, query )
args.seqtype = "prot"
# perform uniref90 search
uniref90hits = uniref_search(
diamond=args.diamond,
database=args.uniref90db,
query=query,
seqtype=args.seqtype,
temp=args.temp,
diamond_options=args.diamond_options,
force_search=args.force_search,
)
uniref90map = parse_results( uniref90hits )
# perform uniref50 search
uniref50hits = uniref_search(
diamond=args.diamond,
database=args.uniref50db,
query=query,
seqtype=args.seqtype,
temp=args.temp,
diamond_options=args.diamond_options,
force_search=args.force_search,
)
uniref50map = parse_results( uniref50hits )
# override mappings?
overrides = {}
if args.transitive_map is not None:
overrides = trans_mapping( uniref90map, args.transitive_map )
# reannoate the fasta
reannotate(
query=args.fasta,
out=args.out,
uniref90map=uniref90map,
uniref50map=uniref50map,
overrides=overrides, )
# done
say( "Finished successfully." )
if __name__ == "__main__":
main( )