def annotate_mvf(args):
"""Main method"""
args.qprint("Running AnnotateMVF")
mvf = MultiVariantFile(args.mvf, 'read')
args.qprint("Input MVF header processed.")
args.qprint("MVF flavor: {}".format(mvf.metadata['flavor']))
gff, geneids = parse_gff_annotate(args.gff, mvf.metadata['contigs'],
gene_prefix=args.gene_prefix)
args.qprint("GFF processed.")
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite,
flavor=mvf.metadata['flavor'])
outmvf.metadata = deepcopy(mvf.metadata)
if args.nongenic_mode is False:
outmvf.metadata['contigs'] = geneids
outmvf.write_data(outmvf.get_header())
args.qprint("Output MVF established.")
entrybuffer = []
nentry = 0
args.qprint("Processing MVF entries.")
for contigid, pos, allelesets in mvf.iterentries(decode=False):
annotated_pos = False
if contigid in gff:
if pos in gff[contigid]:
annotated_pos = True
elif args.nongenic_mode is True and args.unmargin > 0:
for xpos in range(pos - args.unmargin,
pos + args.unmargin + 1):
if xpos in gff[contigid]:
annotated_pos = True
break
if annotated_pos and not args.nongenic_mode:
entrybuffer.append((gff[contigid][pos], pos, allelesets))
elif args.nongenic_mode and not annotated_pos:
entrybuffer.append((contigid, pos, allelesets))
if args.nongenic_mode or annotated_pos:
nentry += 1
if nentry == args.line_buffer:
args.qprint("Writing block of entries.")
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
if entrybuffer:
outmvf.write_entries(entrybuffer)
args.qprint("Writing final block of entries.")
entrybuffer = []
nentry = 0
return ''
def annotate_mvf(args):
"""Main method"""
mvf = MultiVariantFile(args.mvf, 'read')
gff, geneids = parse_gff_annotate(args.gff, mvf.metadata['contigs'])
if args.quiet is False:
print("gff_processed")
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
outmvf.metadata = deepcopy(mvf.metadata)
if args.nongenic_mode is False:
outmvf.metadata['contigs'] = geneids
outmvf.write_data(outmvf.get_header())
entrybuffer = []
nentry = 0
for contigid, pos, allelesets in mvf.iterentries(decode=False):
annotated_pos = False
if contigid in gff:
if pos in gff[contigid]:
annotated_pos = True
elif args.nongenic_mode is True and args.unmargin > 0:
for xpos in range(pos - args.unmargin,
pos + args.unmargin + 1):
if xpos in gff[contigid]:
annotated_pos = True
break
if args.nongenic_mode is False and annotated_pos is True:
entrybuffer.append((gff[contigid][pos], pos, allelesets))
nentry += 1
if nentry == args.line_buffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
elif args.nongenic_mode is True and annotated_pos is False:
entrybuffer.append((contigid, pos, allelesets))
nentry += 1
if nentry == args.line_buffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
if entrybuffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
return ''
def filter_mvf(args):
"""Main method"""
if args.more_help is True:
modulehelp()
sys.exit()
if args.mvf is None and args.test is None:
raise RuntimeError("No input file specified with --mvf")
if args.out is None and args.test is None:
raise RuntimeError("No output file specified with --out")
# Establish Input MVF
if args.test is not None:
ncol = args.test_nchar or len(args.test.split()[1])
else:
mvf = MultiVariantFile(args.mvf, 'read')
ncol = mvf.metadata['ncol']
# Create Actionset
if args.labels:
labels = mvf.get_sample_labels()[:]
for i in range(len(args.actions)):
action = args.actions[i]
arr = action.split(':')
if arr[0] in ('columns', 'collapsepriority', 'collapsemerge',
'allelegroup', 'notmultigroup'):
for j in range(1, len(arr)):
arr[j] = ','.join(
[str(labels.index(x)) for x in arr[j].split(',')])
args.actions[i] = ':'.join(arr)
actionset = build_actionset(args.actions, ncol)
# TESTING MODE
if args.test:
loc, alleles = args.test.split()
linefail = False
transformed = False
# invar = invariant (single character)
# refvar (all different than reference, two chars)
# onecov (single coverage, + is second character)
# onevar (one variable base, + is third character)
# full = full alleles (all chars)
if args.verbose:
print(alleles)
linetype = get_linetype(alleles)
sys.stdout.write("MVF Encoding type '{}' detected\n".format(linetype))
for actionname, actiontype, actionfunc, actionarg in actionset:
sys.stdout.write("Applying action {} ({}): ".format(
actionname, actiontype))
if actiontype == 'filter':
if not actionfunc(alleles, linetype):
linefail = True
sys.stdout.write("Filter Fail\n")
break
else:
sys.stdout.write("Filter Pass\n")
elif actiontype == 'transform':
transformed = True
alleles = actionfunc(alleles, linetype)
linetype = get_linetype(alleles)
if linetype == 'empty':
linefail = True
sys.stdout.write("Transform removed all alleles\n")
break
else:
sys.stdout.write("Transform result {}\n".format(alleles))
elif actiontype == 'location':
loc = loc.split(':')
loc[1] = int(loc[1])
if actionfunc(loc) is False:
linefail = True
sys.stdout.write("Location Fail\n")
break
else:
sys.stdout.write("Location Pass\n")
if linefail is False:
if transformed:
if linetype == 'full':
alleles = encode_mvfstring(alleles)
if alleles:
test_output = "{}\t{}\n".format(loc, alleles)
sys.stdout.write("Final output = {}\n".format(test_output))
else:
sys.stdout.write("Transform removed all alleles\n")
else:
sys.stdout.write("No changes applied\n")
sys.stdout.write("Final output = {}\n".format(args.test))
sys.exit()
# MAIN MODE
# Set up file handler
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
outmvf.metadata = deepcopy(mvf.metadata)
# reprocess header if actions are used that filter columns
if any(x == y[0] for x in ('columns', 'collapsepriority', 'collapsemerge')
for y in actionset):
if args.labels:
labels = outmvf.metadata['labels'][:]
else:
labels = [x for x in outmvf.metadata['samples']]
for actionname, actiontype, actionfunc, actionarg in actionset:
if actionname == 'columns':
labels = [labels[x] for x in actionarg[0]]
elif actionname in ('collapsepriority', 'collapsemerge'):
labels = [
labels[x] for x in range(len(labels))
if x not in actionarg[0][1:]
]
if args.labels:
oldindices = mvf.get_sample_indices(labels)
else:
oldindices = labels[:]
newsamples = {}
for i, _ in enumerate(labels):
newsamples[i] = mvf.metadata['samples'][oldindices[i]]
outmvf.metadata['samples'] = newsamples.copy()
outmvf.metadata['labels'] = labels[:]
outmvf.write_data(outmvf.get_header())
# End header editing
linebuffer = []
nbuffer = 0
for chrom, pos, allelesets in mvf.iterentries(decode=False):
linefail = False
transformed = False
# invar = invariant (single character)
# refvar (all different than reference, two chars)
# onecov (single coverage, + is second character)
# onevar (one variable base, + is third character)
# full = full alleles (all chars)
alleles = allelesets[0]
linetype = get_linetype(alleles)
if linetype == 'empty':
continue
if args.verbose is True:
sys.stdout.write(" {} {}".format(alleles, linetype))
for actionname, actiontype, actionfunc, actionargs in actionset:
if actiontype == 'filter':
if not actionfunc(alleles, linetype):
linefail = True
elif actiontype == 'transform':
transformed = True
alleles = actionfunc(alleles, linetype)
linetype = get_linetype(alleles)
if linetype == 'empty':
linefail = True
elif actiontype == 'location':
if actionfunc([chrom, pos]) is False:
linefail = True
if linefail:
break
if linefail is False:
if transformed:
if linetype == 'full':
alleles = mvf.encode(alleles)
if not alleles:
linefail = True
nbuffer += 1
linebuffer.append((chrom, pos, (alleles, )))
if args.verbose:
sys.stdout.write("{}\n".format(alleles))
if nbuffer == args.line_buffer:
outmvf.write_entries(linebuffer)
linebuffer = []
nbuffer = 0
elif args.verbose:
sys.stdout.write("FAIL\n")
if linebuffer:
outmvf.write_entries(linebuffer)
linebuffer = []
return ''
def mvf_join(args):
"""Main method"""
concatmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
# Copy the first file's metadata
if args.main_header_file:
if args.main_header_file not in args.mvf:
raise RuntimeError("{} not found in files".format(
args.main_header_file))
else:
args.main_header_file = args.mvf.index(args.main_header_file)
else:
args.main_header_file = 0
first_mvf = MultiVariantFile(args.mvf[args.main_header_file], 'read')
concatmvf.metadata = first_mvf.metadata.copy()
# Open each MVF file, read headers to make unified header
transformers = []
for mvfname in args.mvf:
# This will create a dictionary of samples{old:new}, contigs{old:new}
transformer = MvfTransformer()
mvf = MultiVariantFile(mvfname, 'read')
for i, label in enumerate(mvf.get_sample_labels()):
if label not in concatmvf.get_sample_labels():
concatmvf.metadata['labels'].append(label)
concatmvf.metadata['samples'][
concatmvf.metadata['labels'].index(label)] = {
'label': label
}
if concatmvf.metadata['labels'].index(label) != i:
transformer.set_label(
i, concatmvf.metadata['labels'].index(label))
for contigid, contigdata in iter(mvf.metadata['contigs'].items()):
if contigdata['label'] not in [
concatmvf.metadata['contigs'][x]['label']
for x in concatmvf.metadata['contigs']
]:
newid = (contigid not in concatmvf.metadata['contigs']
and contigid or concatmvf.get_next_contig_id())
concatmvf.metadata['contigs'][newid] = contigdata
else:
for concatid, concatdata in (
concatmvf.metadata['contigs'].items()):
if contigdata['label'] == concatdata['label']:
newid = concatid
break
if newid != contigid:
transformer.set_contig(contigid, newid)
transformers.append(transformer)
# Write output header
concatmvf.write_data(concatmvf.get_header())
# Now loop through each file
entries = []
nentries = 0
for ifile, mvfname in enumerate(args.mvf):
if not args.quiet:
sys.stderr.write("Processing {} ...\n".format(mvfname))
transformer = transformers[ifile]
mvf = MultiVariantFile(mvfname, 'read')
for contigid, pos, allelesets in mvf.iterentries(decode=False,
quiet=args.quiet):
if transformer.labels:
allelesets = [mvf.decode(x) for x in allelesets]
for j, alleles in enumerate(allelesets):
allelesets[j] = concatmvf.encode(''.join([
x in transformer.labels
and alleles[transformer.labels[x]] or alleles[x]
for x in range(len(alleles))
]))
if transformer.contigs:
contigid = (contigid in transformer['contigs']
and transformer['contigs'][contigid] or contigid)
entries.append((contigid, pos, allelesets))
nentries += 1
if nentries == args.line_buffer:
concatmvf.write_entries(entries)
entries = []
nentries = 0
if entries:
concatmvf.write_entries(entries)
entries = []
nentries = 0
if not args.quiet:
sys.stderr.write("done\n")
return ''
def merge_mvf(args):
"""Main method"""
args.qprint("Running MergeMVF")
if any(fpath.endswith('.gz') for fpath in args.mvf):
print("WARNING! Running MergeMVF with gzipped input files is "
"extremely slow and strongly discouraged.")
concatmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
# Copy the first file's metadata
args.qprint("Reading First File and Establishing Output")
if args.main_header_file:
if args.main_header_file not in args.mvf:
raise RuntimeError("{} not found in files".format(
args.main_header_file))
else:
args.main_header_file = args.mvf.index(args.main_header_file)
else:
args.main_header_file = 0
first_mvf = MultiVariantFile(args.mvf[args.main_header_file], 'read')
concatmvf.metadata = first_mvf.metadata.copy()
# Open each MVF file, read headers to make unified header
transformers = []
mvfmetadata = []
concatmvf_reverse_contig = dict(
(x['label'], k) for (k, x) in concatmvf.metadata['contigs'].items())
inputfiles = []
for mvfname in args.mvf:
args.qprint("Reading headers from {}".format(mvfname))
# This will create a dictionary of samples{old:new}, contigs{old:new}
args.qprint("Processing Headers and Indexing: {}".format(mvfname))
transformer = MvfTransformer()
mvf = MultiVariantFile(mvfname,
'read',
contigindex=(not args.skip_index))
if args.skip_index:
mvf.read_index_file()
mvf.reset_max_contig_id()
mvfmetadata.append(mvf.metadata)
for i, label in enumerate(mvf.get_sample_labels()):
if label not in concatmvf.get_sample_labels():
concatmvf.metadata['labels'].append(label)
concatmvf.metadata['samples'][
concatmvf.metadata['labels'].index(label)] = {
'label': label
}
# if concatmvf.metadata['labels'].index(label) != i:
transformer.set_label(i, concatmvf.metadata['labels'].index(label))
for contigid, contigdata in iter(mvf.metadata['contigs'].items()):
if contigdata['label'] not in concatmvf_reverse_contig:
newid = (contigid
if contigid not in concatmvf.metadata['contigs'] else
concatmvf.get_next_contig_id())
concatmvf.metadata['contigs'][newid] = contigdata
concatmvf_reverse_contig[contigdata['label']] = newid
else:
newid = concatmvf_reverse_contig[contigdata['label']]
transformer.set_contig(contigid, newid)
transformers.append(transformer)
inputfiles.append(mvf)
# Write output header
args.qprint("Writing headers to merge output")
concatmvf.reset_ncol()
concatmvf.write_data(concatmvf.get_header())
contigs = concatmvf.metadata['contigs']
# Now loop through each file
blank_entry = '-' * len(concatmvf.metadata['samples'])
for current_contig in contigs:
contig_merged_entries = {}
args.qprint("Merging Contig: {}".format(current_contig))
for ifile, mvffile in enumerate(inputfiles):
if current_contig not in transformers[ifile].contigs:
continue
localcontig = transformers[ifile].contigs[current_contig]
for chrom, pos, allelesets in mvffile.itercontigentries(
localcontig, decode=True):
if pos not in contig_merged_entries:
contig_merged_entries[pos] = blank_entry[:]
for j, base in enumerate(allelesets[0]):
xcoord = transformers[ifile].labels_rev[j]
if contig_merged_entries[pos][xcoord] != '-':
if contig_merged_entries[pos][xcoord] == base:
continue
if base == '-' or base == 'X':
continue
raise RuntimeError(
"Merging columns have two different bases: {} {} {}"
.format(pos, contig_merged_entries[pos][xcoord],
base))
contig_merged_entries[pos] = (
contig_merged_entries[pos][:xcoord] + base +
contig_merged_entries[pos][xcoord + 1:])
concatmvf.write_entries(
((current_contig, coord, (entry, ))
for coord, entry in sorted(contig_merged_entries.items())),
encoded=False)
args.qprint("Entries written for contig {}: {}".format(
current_contig, len(contig_merged_entries)))
return ''
def translate_mvf(args):
"""Main method"""
mvf = MultiVariantFile(args.mvf, 'read')
if mvf.flavor != 'dna':
raise RuntimeError("MVF must be flavor=dna to translate")
if args.gff:
gff = parse_gff_translate(args.gff, args)
if not args.quiet:
print("gff_processed")
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
outmvf.metadata = deepcopy(mvf.metadata)
outmvf.flavor = args.output_data
outmvf.write_data(outmvf.get_header())
entrybuffer = []
nentry = 0
if not args.gff:
inputbuffer = []
current_contig = ''
for contigid, pos, allelesets in mvf.iterentries(decode=False):
if current_contig == '':
current_contig = contigid[:]
if contigid == current_contig:
inputbuffer.append((pos, allelesets))
else:
for _, amino_acids, alleles in iter_codons(inputbuffer, mvf):
if all([x in '-X' for x in amino_acids]):
continue
if args.output_data == 'protein':
entrybuffer.append(
(current_contig, pos, (amino_acids, )))
else:
entrybuffer.append(
(current_contig, pos, (amino_acids, alleles[0],
alleles[1], alleles[2])))
nentry += 1
if nentry == args.line_buffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
inputbuffer = [(pos, allelesets)]
current_contig = contigid[:]
if inputbuffer:
for _, amino_acids, alleles in iter_codons(inputbuffer, mvf):
if all([x in '-X' for x in amino_acids]):
continue
if args.output_data == 'protein':
entrybuffer.append((current_contig, pos, (amino_acids, )))
else:
entrybuffer.append(
(current_contig, pos, (amino_acids, alleles[0],
alleles[1], alleles[2])))
nentry += 1
if nentry == args.line_buffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
else:
mvf_entries = {}
for contigid, pos, allelesets in mvf.iterentries(decode=False):
if contigid not in mvf_entries:
mvf_entries[contigid] = {}
mvf_entries[contigid][pos] = allelesets[0]
for contigname in sorted(gff):
contigid = mvf.get_contig_ids(labels=contigname)[0]
for coords in sorted(gff[contigname]):
reverse_strand = False
if coords[3] == '-':
reverse_strand = True
alleles = [
mvf_entries[contigid].get(x, '-')
for x in coords[2::-1]
]
else:
alleles = [
mvf_entries[contigid].get(x, '-') for x in coords[0:3]
]
if all(len(x) == 1 for x in alleles):
if reverse_strand:
alleles = [MLIB.complement_bases[x] for x in alleles]
decoded_alleles = alleles
amino_acids = translate(''.join(alleles))[0]
else:
if reverse_strand:
decoded_alleles = [[
MLIB.complement_bases[y] for y in mvf.decode(x)
] for x in alleles]
alleles = [
mvf.encode(''.join(x)) for x in decoded_alleles
]
else:
decoded_alleles = [mvf.decode(x) for x in alleles]
amino_acids = [
translate(''.join(x)) for x in zip(*decoded_alleles)
]
amino_acids = mvf.encode(''.join(
[x[0] for x in amino_acids]))
if all([x in '-X' for x in amino_acids]):
continue
if args.output_data == 'protein':
entrybuffer.append((contigid, coords[0], (amino_acids, )))
else:
entrybuffer.append(
(contigid, coords[0], (amino_acids, alleles[0],
alleles[1], alleles[2])))
nentry += 1
if nentry == args.line_buffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
if entrybuffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
return ''
def translate_mvf(args):
"""Main method"""
args.qprint("Running TranslateMVF")
if args.gff:
args.qprint("Reading and Indexing MVF.")
else:
args.qprint("Reading MVF.")
mvf = MultiVariantFile(args.mvf, 'read', contigindex=bool(args.gff))
if mvf.flavor != 'dna':
raise RuntimeError("MVF must be flavor=dna to translate")
if args.gff:
args.qprint("Processing MVF Index File.")
mvf.read_index_file()
gff = parse_gff_translate(args.gff, args,
parent_gene_prefix=args.parent_gene_prefix)
args.qprint("GFF processed.")
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
outmvf.metadata = deepcopy(mvf.metadata)
outmvf.flavor = args.output_data
outmvf.write_data(outmvf.get_header())
args.qprint("Output MVF Established.")
entrybuffer = []
nentry = 0
pos = None
if not args.gff:
args.qprint("No GFF used, translating sequences as pre-aligned in "
"coding frame.")
inputbuffer = []
current_contig = ''
for contigid, pos, allelesets in mvf.iterentries(decode=False):
if current_contig == '':
current_contig = contigid[:]
if contigid == current_contig:
inputbuffer.append((pos, allelesets))
else:
for _, amino_acids, alleles in iter_codons(
inputbuffer, mvf):
if all([x in '-X' for x in amino_acids]):
continue
if args.output_data == 'protein':
entrybuffer.append(
(current_contig, pos, (amino_acids,)))
else:
entrybuffer.append((
current_contig, pos, (
amino_acids, alleles[0],
alleles[1], alleles[2])))
nentry += 1
if nentry == args.line_buffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
inputbuffer = [(pos, allelesets)]
current_contig = contigid[:]
if inputbuffer:
for _, amino_acids, alleles in iter_codons(
inputbuffer, mvf):
if all([x in '-X' for x in amino_acids]):
continue
if args.output_data == 'protein':
entrybuffer.append(
(current_contig, pos, (amino_acids,)))
else:
entrybuffer.append((
current_contig, pos, (
amino_acids, alleles[0],
alleles[1], alleles[2])))
nentry += 1
if nentry == args.line_buffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
else:
args.qprint("Indexing GFF gene names.")
#mvfid_to_gffname = outmvf.get_contig_reverse_dict()
for xcontigid in outmvf.get_contig_ids():
mvf_entries = {}
contigname = outmvf.metadata['contigs'][xcontigid]['label']
if contigname not in gff:
if args.verbose:
print("No entries in GFF, skipping contig: {} {}".format(
xcontigid, contigname))
continue
if not int(xcontigid) % 100:
args.qprint("Processing contig: {} {}".format(
xcontigid, contigname))
#contig_cds_bases = chain(x[:3] for x in gff[contigname])
for contigid, pos, allelesets in mvf.itercontigentries(
xcontigid, decode=False):
# if pos in contig_cds_bases:
mvf_entries[pos] = allelesets[0]
for coords in sorted(gff[contigname]):
reverse_strand = coords[3] == '-'
alleles = (tuple(mvf_entries.get(x, '-')
for x in coords[2::-1]) if
reverse_strand else tuple(mvf_entries.get(x, '-')
for x in coords[0:3]))
if all(len(x) == 1 for x in alleles):
if reverse_strand:
alleles = tuple(
MLIB.complement_bases[x] for x in alleles)
decoded_alleles = alleles
amino_acids = translate_single_codon(''.join(alleles))
else:
if reverse_strand:
decoded_alleles = tuple(tuple(MLIB.complement_bases[y]
for y in mvf.decode(x))
for x in alleles)
alleles = tuple(mvf.encode(''.join(x))
for x in decoded_alleles)
else:
decoded_alleles = tuple(mvf.decode(x) for x in alleles)
amino_acids = tuple(translate_single_codon(''.join(x))
for x in zip(*decoded_alleles))
#print("aminx", amino_acids)
amino_acids = mvf.encode(''.join(amino_acids))
# if all(x in '-X' for x in amino_acids):
# continue
# print("amino", amino_acids)
# print("translated", amino_acids, alleles)
if args.output_data == 'protein':
entrybuffer.append((xcontigid, coords[0], (amino_acids,)))
else:
entrybuffer.append((
xcontigid, coords[0], (
amino_acids, alleles[0], alleles[1], alleles[2])))
nentry += 1
if nentry >= args.line_buffer:
args.qprint("Writing a block of {} entries.".format(
args.line_buffer))
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
if entrybuffer:
outmvf.write_entries(entrybuffer)
entrybuffer = []
nentry = 0
return ''
