def maf2mvf(args):
"""Main method"""
# ESTABLISH MAF
args.qprint("Starting ConvertMAF2MVF")
maf = MultiAlignFile(args)
args.qprint("MAF Established")
# ESTABLISH MVF
mvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
args.qprint("MVF output initialized")
# PROCESS SAMPLE INFO
contig_translate = {1: 1}
samplelabels = [s.split(':')[0] for s in args.sample_tags.split(',')]
args.qprint("Sample tags processed: {}".format(samplelabels))
if args.ref_tag not in samplelabels:
raise IndexError("--ref-tag not in the tags listed in --sample-tags")
samplelabels.remove(args.ref_tag)
samplelabels.insert(0, args.ref_tag)
mvf.sample_ids = samplelabels[:]
mvf.sample_indices = list(range(len(mvf.sample_ids)))
for i, label in enumerate(samplelabels):
mvf.sample_data[i] = {'id': label, 'index': i}
mvf.reset_max_sample()
mvf.metadata['sourceformat'] = maf.metadata['sourceformat']
mvf.metadata.notes.append(args.command_string)
# WRITE MVF HEADER
mvf.write_data(mvf.get_header())
args.qprint("MAF Headers Written")
mvfentries = []
nentry = 0
total_entries = 0
args.qprint("Begin data conversion")
for pos, length, msa in maf:
for sname in samplelabels:
if sname not in msa:
msa[sname] = '-'*length
msa['contig'] = 1
for i in range(length):
mvf_alleles = encode_mvfstring(
''.join(msa[s][i].strip() for s in samplelabels))
if mvf_alleles:
mvfentries.append(
(contig_translate.get(msa['contig']),
pos+i, (mvf_alleles,)))
nentry += 1
if nentry == args.line_buffer:
total_entries += nentry
mvf.write_entries(mvfentries, encoded=True)
args.qprint("{} entries written".format(total_entries))
mvfentries = []
nentry = 0
if mvfentries:
total_entries += nentry
mvf.write_entries(mvfentries)
args.qprint("{} entries written".format(total_entries))
args.qprint("Complete.")
return ''
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 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 maf2mvf(args):
"""Main method"""
# ESTABLISH MAF
maf = MultiAlignFile(args)
# ESTABLISH MVF
mvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
# PROCESS SAMPLE INFO
contig_translate = {1: 1}
samplelabels = [s.split(':')[0] for s in args.sample_tags]
samplelabels.remove(args.ref_tag)
samplelabels.insert(0, args.ref_tag)
mvf.metadata['labels'] = samplelabels[:]
for i, label in enumerate(samplelabels):
mvf.metadata['samples'][i] = {'label': label}
mvf.metadata['ncol'] = len(mvf.metadata['labels'])
mvf.metadata['sourceformat'] = maf.metadata['sourceformat']
# WRITE MVF HEADER
mvf.write_data(mvf.get_header())
mvfentries = []
nentry = 0
for pos, length, msa in maf:
for sname in samplelabels:
if sname not in msa:
msa[sname] = '-'*length
msa['contig'] = 1
for i in range(length):
mvf_alleles = encode_mvfstring(
''.join(msa[s][i].strip() for s in samplelabels))
if mvf_alleles:
mvfentries.append(
(contig_translate.get(msa['contig']),
pos+i, (mvf_alleles,)))
nentry += 1
if nentry == args.line_buffer:
mvf.write_entries(mvfentries, encoded=True)
mvfentries = []
nentry = 0
if mvfentries:
mvf.write_entries(mvfentries)
return ''
def fasta2mvf(args):
"""Main method"""
sepchars = dict([("PIPE", "\\|"), ("TAB", "\\t"), ("SPACE", "\\s"),
("DBLSPACE", "\\s\\s"), ("COMMA", "\\,"), ("NONE", None),
("AT", "\\@"), ('UNDER', "\\_"), ("DBLUNDER", "\\_\\_")])
if args.field_sep is None:
args.field_sep = ''
else:
args.field_sep = re.compile("[{}]".format(''.join(
[sepchars[x] for x in args.field_sep])))
if args.manual_coord:
assert len(args.manual_coord) == len(args.fasta)
args.manual_coord = [(x.split(':')[0],
int(x.split(":")[1].split('..')[0]),
int(x.split(':')[1].split('..')[1]))
for x in args.manual_coord]
mvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
fasta = {}
current_contig = 0
fsamples = []
fcontigs = []
for ifasta, fastapath in enumerate(args.fasta):
print("Processing {}".format(fastapath))
for header, seq in fasta_iter(fastapath):
if args.field_sep is None:
header = header[:]
if args.field_sep != '' and args.field_sep is not None:
header = [str(x) for x in re.split(args.field_sep, header)]
if args.contig_by_file is True:
contig = os.path.basename(fastapath[:])
if args.sample_field is None:
sample = header[:]
else:
sample = header[args.sample_field]
elif (len(header) < max(
args.contig_field if args.contig_field is not None else 0,
args.sample_field if args.sample_field is not None else 0)
or args.contig_field is None or args.sample_field is None):
contig = "UNK{}".format(current_contig)
sample = header[:]
elif args.manual_coord:
contig = args.manual_coord[ifasta][0]
else:
contig = header[args.contig_field]
sample = header[args.sample_field]
if contig not in fcontigs:
fcontigs.append(contig)
fasta[contig] = {}
if sample not in fsamples:
fsamples.append(sample)
fasta[contig][sample] = (len(seq), seq)
reflabel = None
if args.ref_label:
for i, samplename in enumerate(fsamples):
if args.ref_label in samplename:
reflabel = i
break
if reflabel:
newref = fsamples.pop(i)
fsamples = [newref] + fsamples
for i, contig in enumerate(fcontigs):
new_index = mvf.get_next_contig_index()
mvf.contig_indices.append(new_index)
mvf.contig_ids.append(str(new_index))
mvf.contig_labels.append(contig)
mvf.contig_label_to_index[contig] = new_index
mvf.contig_id_to_index[str(new_index)] = new_index
mvf.contig_data[new_index] = {
'label': contig,
'id': str(new_index),
'length': max([fasta[contig][x][0] for x in fasta[contig]])
}
mvf.metadata['labels'] = fsamples[:]
for i, label in enumerate(fsamples[:]):
mvf.sample_indices.append(i)
mvf.sample_id_to_index[label] = i
mvf.sample_ids.append(label)
mvf.sample_data[i] = {'id': label}
mvf.metadata['ncol'] = len(mvf.metadata['labels'])
mvf.metadata['sourceformat'] = 'fasta'
mvf.metadata.append(args.command_string)
mvf.flavor = args.flavor
# WRITE MVF HEADER
mvf.write_data(mvf.get_header())
mvfentries = []
nentry = 0
mvf_alleles = {}
for cind, contig in enumerate(fcontigs):
for pos in range(mvf.contig_data[cind + 1]['length']):
mvf_alleles = encode_mvfstring(
''.join(samp not in fasta[contig] and '-'
or pos >= fasta[contig][samp][0] and '-'
or fasta[contig][samp][1][pos] for samp in fsamples))
if mvf_alleles:
if args.flavor == 'dna':
mvf_alleles = ''.join(
["X" if x in 'NX' else x for x in mvf_alleles])
mvfentries.append((cind, pos + 1, (mvf_alleles, )))
nentry += 1
if nentry == args.write_buffer:
mvf.write_entries(mvfentries, encoded=True)
mvfentries = []
nentry = 0
if mvfentries:
mvf.write_entries(mvfentries)
mvfentries = []
return ''
def vcf2mvf(args=None):
"""Main method for vcf2mvf"""
sepchars = dict([("TAB", "\t"), ("SPACE", " "), ("DBLSPACE", " "),
("COMMA", ","), ("MIXED", None)])
args.fieldsep = sepchars[args.field_sep]
# ESTABLISH VCF
args.qprint("Opening input VCF: {}".format(args.vcf))
vcf = VariantCallFile(args.vcf, indexcontigs=(not args.no_autoindex))
# ESTABLISH MVF
args.qprint("Establishing output MVF: {}".format(args.out))
mvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
mvf.notes.append(args.command_string)
mvf.metadata['mvfversion'] = args.versionx
# PROCESS CONTIG INFO
args.qprint("Processing VCF headers.")
vcfcontigs = vcf.metadata['contigs'].copy()
args.qprint("{} contigs found.".format(len(vcfcontigs)))
contig_translate = {}
if args.contig_ids:
for cid, cvcf, cmvf in (x.split(';') for x in args.contig_ids):
try:
cid = int(cid)
except ValueError:
pass
assert cvcf in [vcfcontigs[x]['label'] for x in vcfcontigs]
for vid in vcfcontigs:
if vcfcontigs[vid]['label'] == cvcf:
contig_translate[cvcf] = [cid, cmvf]
if cid in mvf.metadata['contigs']:
raise RuntimeError(
'Contig id {} is not unique'.format(cid))
mvf.metadata['contigs'][cid] = vcfcontigs[vid].copy()
if cmvf in mvf.get_contig_labels():
raise RuntimeError(
'Contig label {} is not unique'.format(cmvf))
mvf.metadata['contigs'][cid]['label'] = cmvf[:]
mvf.reset_max_contig()
mvf.max_contig_index -= 1
args.qprint("Processing contigs.")
static_contig_ids = list(mvf.get_contig_ids())
for vcid in vcfcontigs:
vlabel = vcfcontigs[vcid]['label']
if vlabel not in static_contig_ids:
newindex = mvf.get_next_contig_index()
if ((is_int(vlabel) or len(vlabel) < 3)
and vlabel not in static_contig_ids):
newid = vlabel[:]
else:
newid = str(newindex)
mvf.contig_indices.append(newindex)
mvf.contig_ids.append(newid)
mvf.contig_data[newindex] = vcfcontigs[vcid].copy()
static_contig_ids.append(newid)
contig_translate[vlabel] = [newindex, vlabel]
mvf.reset_max_contig()
new_contigs = [(x, mvf.contig_data[x]['label'])
for x in mvf.contig_indices]
if args.skip_contig_label_check is False:
args.qprint("Checking contigs for label/id overlap errors.")
xids = [x[0] for x in new_contigs]
xlabels = [x[1] for x in new_contigs]
xintersect = set(xids).intersection(xlabels)
if xintersect:
for i, (newid, newlabel) in enumerate(new_contigs):
if i % 100 == 0:
args.qprint("{} contigs processed".format(i))
if newid in xlabels[:i] or newid in xlabels[i + 1:]:
# if newid in xlabels:
# if xlabels.index(newid) != i:
raise RuntimeError("Error contig id {} is the same as"
" the label for another contig"
" ({})".format(newid,
xlabels.index(newid)))
if newlabel in xids[:i] or newlabel in xids[i + 1:]:
# if newlabel in xids:
# if xids.index(newlabel) != i:
raise RuntimeError("Error contig label {} is the same"
"as the id for another contig"
"({})".format(newlabel,
xids.index(newlabel)))
# PROCESS SAMPLE INFO
args.qprint("Processing samples.")
samplelabels = [args.ref_label] + vcf.metadata['samples'][:]
if args.alleles_from:
args.alleles_from = args.alleles_from.split(':')
samplelabels += args.alleles_from
if args.sample_replace:
newsample = [
x.split(':') if ':' in tuple(x) else tuple([x, x])
for x in args.sample_replace
]
unmatched = list(enumerate(samplelabels))
for old, new in newsample:
labelmatched = False
for j, (i, name) in enumerate(unmatched):
if old in name:
samplelabels[i] = new
labelmatched = j
break
if labelmatched is not False:
del unmatched[labelmatched]
mvf.sample_indices = list(range(len(samplelabels)))
mvf.sample_ids = samplelabels[:]
for i, label in enumerate(samplelabels):
mvf.sample_data[i] = {'id': label}
mvf.metadata['ncol'] = len(mvf.sample_ids)
mvf.max_sample_index = len(mvf.sample_ids)
mvf.metadata['sourceformat'] = vcf.metadata['sourceformat']
# WRITE MVF HEADER
mvf.write_data(mvf.get_header())
mvfentries = []
nentry = 0
args.qprint("Processing VCF entries.")
for vcfrecord in vcf.iterentries(args):
mvfstring = ''.join(vcfrecord['genotypes'])
if args.filter_nonref_empty is True:
if all(x in 'Xx-?' for x in mvfstring[1:]):
continue
mvf_alleles = encode_mvfstring(mvfstring)
if args.out_flavor in ('dnaqual', ):
qual_alleles = encode_mvfstring(''.join(vcfrecord['qscores']))
if mvf_alleles:
mvfentries.append(
(contig_translate.get(vcfrecord['contig'])[0],
vcfrecord['coord'],
((mvf_alleles,
qual_alleles) if args.out_flavor in ('dnaqual', ) else
(mvf_alleles, ))))
nentry += 1
if nentry == args.line_buffer:
mvf.write_entries(mvfentries, encoded=True)
mvfentries = []
nentry = 0
if mvfentries:
mvf.write_entries(mvfentries)
mvfentries = []
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 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 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 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 ''
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))
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.copy_header(first_mvf)
# Open each MVF file, read headers to make unified header
transformers = []
mvfmetadata = []
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()
mvfmetadata.append(mvf.metadata)
for i, sid in enumerate(mvf.get_sample_ids()):
if sid not in concatmvf.get_sample_ids():
new_sindex = concatmvf.max_sample_index + 0
concatmvf.max_sample_index += 1
concatmvf.sample_indices.append(new_sindex)
concatmvf.sample_ids.append(sid)
concatmvf.sample_data[new_sindex] = {}
concatmvf.sample_data[new_sindex]['id'] = sid
concatmvf.sample_id_to_index[sid] = new_sindex
transformer.set_label(i, concatmvf.sample_id_to_index[sid])
for cindex in mvf.contig_indices:
if (mvf.contig_data[cindex]['label']
not in concatmvf.contig_label_to_index):
new_cindex = (mvf.contig_data[cindex]['id']
if mvf.contig_data[cindex]['id']
not in concatmvf.contig_ids else
concatmvf.get_next_contig_index())
concatmvf.contig_data[new_cindex] = (
mvf.contig_data[cindex].copy())
else:
new_cindex = concatmvf.contig_label_to_index[
mvf.contig_data[cindex]['label']]
transformer.set_contig(cindex, new_cindex)
transformers.append(transformer)
inputfiles.append(mvf)
# Write output header
args.qprint("Writing headers to merge output")
concatmvf.reset_max_sample()
concatmvf.notes.append(args.command_string)
concatmvf.write_data(concatmvf.get_header())
# Now loop through each file
blank_entry = '-' * len(concatmvf.sample_indices)
for cons_contig in concatmvf.contig_indices:
contig_merged_entries = {}
args.qprint("Merging Contig Index: {}".format(cons_contig))
for ifile, mvffile in enumerate(inputfiles):
if cons_contig not in transformers[ifile].contigs:
continue
localcontig = transformers[ifile].contigs[cons_contig]
if 'idx' not in mvffile.contig_data[localcontig]:
print("not found")
continue
for _, 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 in '-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:])
if contig_merged_entries:
concatmvf.write_entries(
((cons_contig, coord, (entry, ))
for coord, entry in sorted(contig_merged_entries.items())),
encoded=False)
args.qprint("Entries written for contig {}: {}".format(
cons_contig, len(contig_merged_entries)))
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 vcf2mvf(args=None):
"""Main method for vcf2mvf"""
sepchars = dict([("TAB", "\t"), ("SPACE", " "), ("DBLSPACE", " "),
("COMMA", ","), ("MIXED", None)])
args.fieldsep = sepchars[args.field_sep]
# ESTABLISH VCF
vcf = VariantCallFile(args.vcf, indexcontigs=(not args.no_autoindex))
# ESTABLISH MVF
mvf = MultiVariantFile(args.out, 'write', overwrite=args.overwrite)
# PROCESS CONTIG INFO
vcfcontigs = vcf.metadata['contigs'].copy()
contig_translate = {}
if args.contig_ids:
for cid, cvcf, cmvf in (x.split(';') for x in args.contig_ids):
try:
cid = int(cid)
except ValueError:
pass
assert cvcf in [vcfcontigs[x]['label'] for x in vcfcontigs]
for vid in vcfcontigs:
if vcfcontigs[vid]['label'] == cvcf:
contig_translate[cvcf] = [cid, cmvf]
if cid in mvf.metadata['contigs']:
raise RuntimeError(
'Contig id {} is not unique'.format(cid))
mvf.metadata['contigs'][cid] = vcfcontigs[vid].copy()
if cmvf in mvf.get_contig_labels():
raise RuntimeError(
'Contig label {} is not unique'.format(cmvf))
mvf.metadata['contigs'][cid]['label'] = cmvf[:]
mvf.reset_max_contig_id()
for vcid in vcfcontigs:
vlabel = vcfcontigs[vcid]['label']
if vlabel not in mvf.get_contig_labels():
if ((is_int(vlabel) or len(vlabel) < 3)
and vlabel not in mvf.get_contig_ids()):
newid = vlabel[:]
else:
newid = mvf.get_next_contig_id()
mvf.metadata['contigs'][newid] = vcfcontigs[vcid].copy()
contig_translate[vlabel] = [newid, vlabel]
mvf.reset_max_contig_id()
new_contigs = [(x, mvf.metadata['contigs'][x]['label'])
for x in mvf.metadata['contigs']]
for i, (newid, newlabel) in enumerate(new_contigs):
for j, (xid, xlabel) in enumerate(new_contigs):
if i == j:
continue
if newid == xlabel:
raise RuntimeError("Error contig id {} is the same as"
" the label for another contig"
" ({} {})".format(newid, xid, xlabel))
if newlabel == xid:
raise RuntimeError("Error contig label {} is the same"
"as the id for another contig"
"({} {})".format(newlabel, xid, xlabel))
# PROCESS SAMPLE INFO
samplelabels = [args.ref_label] + vcf.metadata['samples'][:]
if args.alleles_from:
args.alleles_from = args.alleles_from.split(':')
samplelabels += args.alleles_from
if args.sample_replace:
newsample = [
x.split(':') if ':' in tuple(x) else tuple([x, x])
for x in args.sample_replace
]
unmatched = [x for x in enumerate(samplelabels)]
for old, new in newsample:
labelmatched = False
for j, (i, name) in enumerate(unmatched):
if old in name:
samplelabels[i] = new
labelmatched = j
break
if labelmatched is not False:
del unmatched[labelmatched]
mvf.metadata['labels'] = samplelabels[:]
for i, label in enumerate(samplelabels):
mvf.metadata['samples'][i] = {'label': label}
mvf.metadata['ncol'] = len(mvf.metadata['labels'])
mvf.metadata['sourceformat'] = vcf.metadata['sourceformat']
# WRITE MVF HEADER
mvf.write_data(mvf.get_header())
mvfentries = []
nentry = 0
for vcfrecord in vcf.iterentries(args):
# try:
mvf_alleles = encode_mvfstring(''.join(vcfrecord['genotypes']))
if args.out_flavor in ('dnaqual', ):
qual_alleles = encode_mvfstring(''.join(vcfrecord['qscores']))
if mvf_alleles:
mvfentries.append(
(contig_translate.get(vcfrecord['contig'])[0],
vcfrecord['coord'],
((mvf_alleles,
qual_alleles) if args.out_flavor in ('dnaqual', ) else
(mvf_alleles, ))))
nentry += 1
if nentry == args.line_buffer:
mvf.write_entries(mvfentries, encoded=True)
mvfentries = []
nentry = 0
# except Exception as exception:
if mvfentries:
mvf.write_entries(mvfentries)
mvfentries = []
return ''
