def legacy_annotate_mvf(args):
"""Main method"""
args.qprint("Running LegacyAnnotateMVF")
mvf = MultiVariantFile(args.mvf, 'read')
args.qprint("Input MVF header processed.")
args.qprint("MVF flavor: {}".format(mvf.flavor))
gff, geneids = parse_gff_legacy_annotate(
args.gff, mvf.contig_data, gene_pattern=args.gene_pattern)
args.qprint("GFF processed.")
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite,
flavor=mvf.flavor)
outmvf.copy_headers_from(mvf)
if args.nongenic_mode is False:
outmvf.contig_data = geneids.copy()
outmvf.contig_indices = list(range(len(geneids)))
outmvf.contig_ids = [geneids[x]['id'] for x in
outmvf.contig_indices]
outmvf.contig_labels = [geneids[x]['label'] for x in
outmvf.contig_indices]
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 = None
if contigid in gff:
for (xgeneid, xstart, xstop) in gff[contigid]:
if xstart < pos < xstop:
annotated_pos = xgeneid + 0
break
if args.nongenic_mode is True and args.unmargin > 0:
for xpos in range(pos - args.unmargin,
pos + args.unmargin + 1):
if xstart < xpos < xstop:
annotated_pos = xgeneid + 0
break
if annotated_pos is not None and not args.nongenic_mode:
entrybuffer.append((annotated_pos, pos, allelesets))
elif args.nongenic_mode and annotated_pos is None:
entrybuffer.append((contigid, pos, allelesets))
if args.nongenic_mode or annotated_pos is not None:
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 filter_mvf(args):
"""Main method"""
args.qprint("Running FilterMVF")
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']
args.qprint("Input MVF read with {} columns.".format(ncol))
# Create Actionset
if args.labels:
for i in range(len(args.actions)):
action = args.actions[i]
arr = action.split(':')
if arr[0] in ('collapsepriority', 'collapsemerge'):
arr[1] = ','.join([
str(mvf.sample_id_to_index[x])
for x in arr[1].split(',')])
if arr[0] in ('columns', 'allelegroup',
'notmultigroup', 'reqsample'):
for j in range(1, len(arr)):
arr[j] = ','.join([
str(mvf.sample_id_to_index[x])
for x in arr[j].split(',')])
args.actions[i] = ':'.join(arr)
removed_columns = set([])
for i in range(len(args.actions)):
action = args.actions[i]
arr = action.split(':')
if arr[0] in ('collapsepriority', 'collapsemerge'):
tmp_arr = arr[1][:]
arr[1] = ','.join([
str(int(x) - len([y for y in removed_columns if y < int(x)]))
for x in arr[1].split(',')])
removed_columns.update([int(x) for x in tmp_arr.split(',')[1:]])
print(arr)
print(removed_columns)
if arr[0] in ('columns', 'allelegroup',
'notmultigroup', 'reqsample'):
for j in range(1, len(arr)):
arr[j] = ','.join([
str(int(x) - len([y for y in removed_columns if y < int(x)]))
for x in arr[j].split(',')])
args.actions[i] = ':'.join(arr)
actionset = build_actionset(args.actions, ncol)
args.qprint("Actions established.")
args.qprint(actionset)
# 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
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
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
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.copy_headers_from(mvf)
removed_indices = set([])
# reprocess header if actions are used that filter columns
if any(x == y[0] for x in ('columns', 'collapsepriority', 'collapsemerge')
for y in actionset):
for actionname, actiontype, actionfunc, actionarg in actionset:
if actionname == 'columns':
if args.labels:
oldindices = [outmvf.sample_id_to_index[int(x)]
for x in actionarg[0]]
else:
oldindices = [int(x) for x in actionarg[0]]
elif actionname in ('collapsepriority', 'collapsemerge'):
actionarg[0] = [x - len([y for y in removed_indices if y < x])
for x in actionarg[0]]
oldindices = [x for x in outmvf.sample_indices
if x not in actionarg[0][1:]]
outmvf.sample_ids = outmvf.get_sample_ids(oldindices)
outmvf.sample_data = dict(
(i, outmvf.sample_data[oldindices[i]])
for i, _ in enumerate(oldindices))
if actionname in ('collapsepriority', 'collapsemerge'):
if len(actionarg) == 2:
outmvf.sample_data[actionarg[0][0]]['id'] = actionarg[1][0]
outmvf.sample_ids[actionarg[0][0]] = actionarg[1][0]
outmvf.sample_indices = list(range(len(oldindices)))
outmvf.metadata['ncol'] = len(outmvf.sample_indices)
outmvf.notes.append(args.command_string)
outmvf.write_data(outmvf.get_header())
args.qprint("Output MVF established.")
# End header editing
linebuffer = []
nbuffer = 0
args.qprint("Processing Entries.")
write_total = 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, _ in actionset:
if actiontype == 'filter':
linefail = not actionfunc(alleles, linetype)
elif actiontype == 'transform':
transformed = True
alleles = actionfunc(alleles, linetype)
linetype = get_linetype(alleles)
linefail = linetype == 'empty'
elif actiontype == 'location':
linefail = not actionfunc([chrom, pos])
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:
write_total += args.line_buffer
args.qprint("{} entries written. Total written: {}.".format(
args.line_buffer, write_total))
outmvf.write_entries(linebuffer)
linebuffer = []
nbuffer = 0
elif args.verbose:
sys.stdout.write("FAIL\n")
if linebuffer:
outmvf.write_entries(linebuffer)
write_total += len(linebuffer)
args.qprint("{} entries written. Total written: {}.".format(
args.line_buffer, write_total))
linebuffer = []
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()
args.qprint("GFF processing start.")
gff_genes, gene_order = parse_gff_exome(args)
args.qprint("GFF processed.")
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
outmvf.copy_headers_from(mvf)
outmvf.contig_data = dict(
(
i, dict((y, z)
for (y, z) in gff_genes[x].items()
if y not in ('cds', )))
for (i, x) in enumerate(gene_order))
outmvf.contig_indices = list(range(len(gene_order)))
outmvf.contig_ids = [gff_genes[x]['id']
for x in gene_order]
outmvf.contig_labels = [gff_genes[x]['label']
for x in gene_order]
outmvf.flavor = args.output_data
outmvf.metadata.notes.append(args.command_string)
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, outmvf):
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:
running_gene_index = -1
for igene, gene in enumerate(gene_order):
xcontiglabel = gff_genes[gene]['contig']
xcontig = mvf.get_contig_indices(
labels=gff_genes[gene]['contig'])
if xcontig is None:
print("Warning: contig {} not found".format(
gff_genes[gene]['contig']))
xcontigid = mvf.get_contig_ids(indices=xcontig)[0]
min_gene_coord = gff_genes[gene]['cds'][0][0]
max_gene_coord = gff_genes[gene]['cds'][-1][1]
mvf_entries = {}
if not igene % 100:
args.qprint("Processing gene {} on {}".format(
gene, xcontiglabel))
for contigid, pos, allelesets in mvf.itercontigentries(
xcontig, decode=False):
if pos < min_gene_coord:
continue
if pos > max_gene_coord:
break
mvf_entries[pos] = allelesets[0]
reverse_strand = gff_genes[gene]['strand'] == '-'
coords = []
running_gene_index += 1
for elem in gff_genes[gene]['cds']:
coords.extend(list(range(elem[0], elem[1] + 1)))
if reverse_strand:
coords = coords[::-1]
for codoncoord in range(0, len(coords), 3):
alleles = tuple(mvf_entries.get(x, '-')
for x in coords[codoncoord:codoncoord + 3])
if len(alleles) < 3:
alleles = tuple(list(alleles) + ['-'] * (3 - len(alleles)))
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 is True:
decoded_alleles = tuple(tuple(MLIB.complement_bases[y]
for y in mvf.decode(x))
for x in alleles)
alleles = tuple(outmvf.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))
amino_acids = outmvf.encode(''.join(amino_acids))
if args.output_data == 'protein':
entrybuffer.append((
(
xcontigid
if args.retain_contigs
else running_gene_index
),
(
coords[codoncoord]
if args.retain_coords
else codoncoord
),
(
amino_acids,
)
))
elif args.output_data == 'codon':
entrybuffer.append((
(
xcontigid
if args.retain_contigs
else running_gene_index
),
(
coords[codoncoord]
if args.retain_coords
else codoncoord
),
(
amino_acids,
alleles[0],
alleles[1],
alleles[2]
)
))
elif args.output_data == 'dna':
for j, elem in enumerate(
range(codoncoord,
min(codoncoord + 3, len(coords)))):
entrybuffer.append((
(
xcontigid
if args.retain_contigs
else running_gene_index
),
(
coords[elem]
if args.retain_coords
else elem + 1
),
(
alleles[j],
)
))
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 ''
def legacy_translate_mvf(args):
"""Main method"""
args.qprint("Running LegacyTranslateMVF")
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()
args.qprint("GFF processing start.")
gff = parse_gff_legacy_translate(
args.gff, args,
parent_gene_pattern=args.parent_gene_pattern)
args.qprint("GFF processed.")
outmvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
outmvf.copy_headers_from(mvf)
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, outmvf):
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 xcontig in outmvf.get_contig_indices():
mvf_entries = {}
xcontiglabel = outmvf.get_contig_labels(indices=xcontig)[0]
xcontigid = outmvf.get_contig_ids(indices=xcontig)[0]
if xcontiglabel not in gff:
if args.verbose:
print(
("No entries in GFF, "
"skipping contig: index:{} id:{} label:{}").format(
xcontig, xcontigid, xcontiglabel))
continue
if not xcontig % 100:
args.qprint("Processing contig: {} {}".format(
xcontigid, xcontiglabel))
for contigid, pos, allelesets in mvf.itercontigentries(
xcontig, decode=False):
mvf_entries[pos] = allelesets[0]
for coords in sorted(gff[xcontiglabel]):
reverse_strand = coords[3] == '-'
alleles = (tuple(mvf_entries.get(x, '-')
for x in coords[2::-1])
if reverse_strand is True
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 is True:
decoded_alleles = tuple(tuple(MLIB.complement_bases[y]
for y in mvf.decode(x))
for x in alleles)
alleles = tuple(outmvf.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 = outmvf.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((xcontig, 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 ''
