def read_if_vcf(params):
"""
Checks if input is VCF and reads in appropriately if it is
"""
ref = None
aln = params.aln
fixed_pi = None
if hasattr(params, 'aln') and params.aln is not None:
if any([params.aln.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not params.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format alignments")
return -1
compress_seq = read_vcf(params.aln, params.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
aln = sequences
if not hasattr(params, 'gtr') or params.gtr=="infer": #if not specified, set it:
alpha = alphabets['aa'] if params.aa else alphabets['nuc']
fixed_pi = [ref.count(base)/len(ref) for base in alpha]
if fixed_pi[-1] == 0:
fixed_pi[-1] = 0.05
fixed_pi = [v-0.01 for v in fixed_pi]
return aln, ref, fixed_pi
def read_if_vcf(params):
"""
Checks if input is VCF and reads in appropriately if it is
"""
ref = None
aln = params.aln
fixed_pi = None
if hasattr(params, 'aln') and params.aln is not None:
if any([params.aln.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not params.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format alignments")
return -1
compress_seq = read_vcf(params.aln, params.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
aln = sequences
if not hasattr(params, 'gtr') or params.gtr=="infer": #if not specified, set it:
alpha = alphabets['aa'] if params.aa else alphabets['nuc']
fixed_pi = [ref.count(base)/len(ref) for base in alpha]
if fixed_pi[-1] == 0:
fixed_pi[-1] = 0.05
fixed_pi = [v-0.01 for v in fixed_pi]
return aln, ref, fixed_pi
def run(args):
'''
This should be modified to work on Fasta-input files!!
'''
print("This method may change in future! Please use 'augur sequence-traits -h' to check the latest options.")
## check file format and read in sequences
is_vcf = False
if ( (args.ancestral_sequences and any([args.ancestral_sequences.lower().endswith(x) for x in ['.vcf', '.vcf.gz']])) or
(args.translations and any([args.translations.lower().endswith(x) for x in ['.vcf', '.vcf.gz']])) ):
if ((args.ancestral_sequences and not args.vcf_reference) or
(args.translations and not args.vcf_translate_reference)):
print("ERROR: a reference Fasta is required with VCF-format alignments")
return 1
is_vcf = True
compress_seq = defaultdict(dict)
if args.translations:
compress_seq = read_in_translate_vcf(args.translations, args.vcf_translate_reference)
if args.ancestral_sequences:
compress_seq["nuc"] = read_vcf(args.ancestral_sequences, args.vcf_reference)
else:
# TO-DO fill in fasta-format processing
aln = args.alignment
features = read_in_features(args.features)
annotations = annotate_strains(features, compress_seq)
#convert the annotations into string label that auspice can display
seq_features = attach_features(annotations, args.label, args.count)
#write out json
with open(args.output, 'w') as results:
json.dump({"nodes":seq_features}, results, indent=1, sort_keys = True)
def run(args):
'''
This should be modified to work on Fasta-input files!!
'''
print("This method may change in future! Please use 'augur sequence-traits -h' to check the latest options.")
print("Unfortunately this method currently only works with VCF input.")
## check file format and read in sequences
is_vcf = False
if ( (args.ancestral_sequences and any([args.ancestral_sequences.lower().endswith(x) for x in ['.vcf', '.vcf.gz']])) or
(args.translations and any([args.translations.lower().endswith(x) for x in ['.vcf', '.vcf.gz']])) ):
if ((args.ancestral_sequences and not args.vcf_reference) or
(args.translations and not args.vcf_translate_reference)):
print("ERROR: a reference Fasta is required with VCF-format alignments")
return 1
is_vcf = True
compress_seq = defaultdict(dict)
if args.translations:
compress_seq = read_in_translate_vcf(args.translations, args.vcf_translate_reference)
if args.ancestral_sequences:
compress_seq["nuc"] = read_vcf(args.ancestral_sequences, args.vcf_reference)
else:
# TO-DO fill in fasta-format processing
aln = args.ancestral_sequences
print("\nERROR: Unfortunately this feature currently only works with VCF input! It will be expanded to work with Fasta-input soon.")
return 1
features = read_in_features(args.features)
annotations = annotate_strains(features, compress_seq)
#convert the annotations into string label that auspice can display
seq_features = attach_features(annotations, args.label, args.count)
#write out json
out_name = get_json_name(args)
write_json({"nodes":seq_features},out_name)
print("sequence traits written to", out_name, file=sys.stdout)
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
if any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print(
"ERROR: a reference Fasta is required with VCF-format alignments"
)
return -1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
aln = sequences
else:
aln = args.alignment
start = time.time()
if args.output:
tree_fname = args.output
else:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '.nwk'
# construct reduced alignment if needed
if is_vcf:
variable_fasta = write_out_informative_fasta(
compress_seq, args.alignment, stripFile=args.strip_sites)
fasta = variable_fasta
else:
fasta = aln
if args.iqmodel and not args.method == 'iqtree':
print(
"Cannot specify model unless using IQTree. Model specification ignored."
)
if args.method == 'raxml':
T = build_raxml(fasta, tree_fname, args.nthreads)
elif args.method == 'iqtree':
T = build_iqtree(fasta, tree_fname, args.iqmodel, args.nthreads)
else: #use fasttree - if add more options, put another check here
T = build_fasttree(fasta, tree_fname)
end = time.time()
print("Building original tree took {} seconds".format(str(end - start)))
if is_vcf and not args.keep_vcf_fasta:
os.remove(variable_fasta)
if T:
import json
tree_success = Phylo.write(T,
tree_fname,
'newick',
format_branch_length='%1.8f')
else:
return -1
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
if any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
# Prepare a multiple sequence alignment from the given variants VCF and
# reference FASTA.
if not args.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format alignments")
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
aln = sequences
elif args.exclude_sites:
# Mask excluded sites from the given multiple sequence alignment.
aln = mask_sites_in_multiple_sequence_alignment(args.alignment, args.exclude_sites)
else:
# Use the multiple sequence alignment as is.
aln = args.alignment
start = time.time()
if args.output:
tree_fname = args.output
else:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '.nwk'
# construct reduced alignment if needed
if is_vcf:
variable_fasta = write_out_informative_fasta(compress_seq, args.alignment, stripFile=args.exclude_sites)
fasta = variable_fasta
else:
fasta = aln
if args.substitution_model and not args.method=='iqtree':
print("Cannot specify model unless using IQTree. Model specification ignored.")
if args.method=='raxml':
T = build_raxml(fasta, tree_fname, nthreads=args.nthreads, tree_builder_args=args.tree_builder_args)
elif args.method=='iqtree':
T = build_iqtree(fasta, tree_fname, args.substitution_model, nthreads=args.nthreads, tree_builder_args=args.tree_builder_args)
elif args.method=='fasttree':
T = build_fasttree(fasta, tree_fname, nthreads=args.nthreads, tree_builder_args=args.tree_builder_args)
else:
print("ERROR: unknown tree builder provided to --method: %s" % args.method, file = sys.stderr)
return 1
end = time.time()
print("\nBuilding original tree took {} seconds".format(str(end-start)))
if T:
import json
tree_success = Phylo.write(T, tree_fname, 'newick', format_branch_length='%1.8f')
else:
return 1
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
if any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
# Prepare a multiple sequence alignment from the given variants VCF and
# reference FASTA.
if not args.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format alignments")
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
aln = sequences
elif args.exclude_sites:
# Mask excluded sites from the given multiple sequence alignment.
aln = mask_sites_in_multiple_sequence_alignment(args.alignment, args.exclude_sites)
else:
# Use the multiple sequence alignment as is.
aln = args.alignment
start = time.time()
if args.output:
tree_fname = args.output
else:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '.nwk'
# construct reduced alignment if needed
if is_vcf:
variable_fasta = write_out_informative_fasta(compress_seq, args.alignment, stripFile=args.exclude_sites)
fasta = variable_fasta
else:
fasta = aln
if args.substitution_model and not args.method=='iqtree':
print("Cannot specify model unless using IQTree. Model specification ignored.")
if args.method=='raxml':
T = build_raxml(fasta, tree_fname, nthreads=args.nthreads)
elif args.method=='iqtree':
T = build_iqtree(fasta, tree_fname, args.substitution_model, nthreads=args.nthreads)
elif args.method=='fasttree':
T = build_fasttree(fasta, tree_fname, nthreads=args.nthreads)
else:
print("ERROR: unknown tree builder provided to --method: %s" % args.method, file = sys.stderr)
return 1
end = time.time()
print("Building original tree took {} seconds".format(str(end-start)))
if T:
import json
tree_success = Phylo.write(T, tree_fname, 'newick', format_branch_length='%1.8f')
else:
return 1
def run(args):
if args.seed is not None:
np.random.seed(args.seed)
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
# node data is the dict that will be exported as json
node_data = {'alignment': args.alignment}
# list of node attributes that are to be exported, will grow
attributes = ['branch_length']
try:
T = read_tree(args.tree)
node_data['input_tree'] = args.tree
except (FileNotFoundError, InvalidTreeError) as error:
print("ERROR: %s" % error, file=sys.stderr)
return 1
if not args.alignment:
if args.timetree:
print(
"ERROR: alignment is required for ancestral reconstruction or timetree inference",
file=sys.stderr)
return 1
if args.divergence_units == 'mutations':
print(
"ERROR: alignment is required for divergence in units of mutations",
file=sys.stderr)
return 1
# fake alignment to appease treetime when only using it for naming nodes...
from Bio import SeqRecord, Seq, Align
seqs = []
for n in T.get_terminals():
seqs.append(
SeqRecord.SeqRecord(seq=Seq.Seq('ACGT'),
id=n.name,
name=n.name,
description=''))
aln = Align.MultipleSeqAlignment(seqs)
elif any([args.alignment.lower().endswith(x)
for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print(
"ERROR: a reference Fasta is required with VCF-format alignments",
file=sys.stderr)
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
from treetime import version as treetime_version
print(f"augur refine is using TreeTime version {treetime_version}")
# if not specified, construct default output file name with suffix _tt.nwk
if args.output_tree:
tree_fname = args.output_tree
elif args.alignment:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '_tt.nwk'
else:
tree_fname = '.'.join(args.tree.split('.')[:-1]) + '_tt.nwk'
if args.root and len(
args.root
) == 1: #if anything but a list of seqs, don't send as a list
args.root = args.root[0]
if args.keep_root: # This flag overrides anything specified by 'root'
args.root = None
if args.timetree:
# load meta data and covert dates to numeric
if args.metadata is None:
print(
"ERROR: meta data with dates is required for time tree reconstruction",
file=sys.stderr)
return 1
metadata, columns = read_metadata(args.metadata)
if args.year_bounds:
args.year_bounds.sort()
dates = get_numerical_dates(metadata,
fmt=args.date_format,
min_max_year=args.year_bounds)
# save input state string for later export
for n in T.get_terminals():
if n.name in metadata and 'date' in metadata[n.name]:
n.raw_date = metadata[n.name]['date']
tt = refine(
tree=T,
aln=aln,
ref=ref,
dates=dates,
confidence=args.date_confidence,
reroot=args.
root, # or 'best', # We now have a default in param spec - this just adds confusion.
Tc=0.01 if args.coalescent is None else
args.coalescent, #use 0.01 as default coalescent time scale
use_marginal=args.date_inference == 'marginal',
branch_length_inference=args.branch_length_inference or 'auto',
precision='auto' if args.precision is None else args.precision,
clock_rate=args.clock_rate,
clock_std=args.clock_std_dev,
clock_filter_iqd=args.clock_filter_iqd,
covariance=args.covariance,
resolve_polytomies=(not args.keep_polytomies))
node_data['clock'] = {
'rate': tt.date2dist.clock_rate,
'intercept': tt.date2dist.intercept,
'rtt_Tmrca': -tt.date2dist.intercept / tt.date2dist.clock_rate
}
if args.coalescent == 'skyline':
try:
skyline, conf = tt.merger_model.skyline_inferred(
gen=args.gen_per_year, confidence=2)
node_data['skyline'] = [[float(x) for x in skyline.x],
[float(y) for y in conf[0]],
[float(y) for y in skyline.y],
[float(y) for y in conf[1]]]
except:
print("ERROR: skyline optimization by TreeTime has failed.",
file=sys.stderr)
return 1
attributes.extend(
['numdate', 'clock_length', 'mutation_length', 'raw_date', 'date'])
if args.date_confidence:
attributes.append('num_date_confidence')
else:
from treetime import TreeAnc
# instantiate treetime for the sole reason to name internal nodes
if args.root:
if args.root == 'best':
print(
"Warning: To root without inferring a timetree, you must specify an explicit outgroup."
)
print(
"\tProceeding without re-rooting. To suppress this message, use '--keep-root'.\n"
)
elif args.root in ['least-squares', 'min_dev', 'oldest']:
raise TypeError(
"The rooting option '%s' is only available when inferring a timetree. Please specify an explicit outgroup."
% args.root)
else:
T.root_with_outgroup(args.root)
tt = TreeAnc(tree=T, aln=aln, ref=ref, gtr='JC69', verbose=1)
node_data['nodes'] = collect_node_data(T, attributes)
if args.divergence_units == 'mutations-per-site': #default
pass
elif args.divergence_units == 'mutations':
if not args.timetree:
tt.infer_ancestral_sequences()
nuc_map = profile_maps['nuc']
def are_sequence_states_different(nuc1, nuc2):
'''
determine whether two ancestral states should count as mutation for divergence estimates
while correctly accounting for ambiguous nucleotides
'''
if nuc1 in ['-', 'N'] or nuc2 in ['-', 'N']:
return False
elif nuc1 in nuc_map and nuc2 in nuc_map:
return np.sum(nuc_map[nuc1] * nuc_map[nuc2]) == 0
else:
return False
for node in T.find_clades():
n_muts = len([
position for ancestral, position, derived in node.mutations
if are_sequence_states_different(ancestral, derived)
])
if args.timetree:
node_data['nodes'][node.name]['mutation_length'] = n_muts
node_data['nodes'][node.name]['branch_length'] = n_muts
else:
print("ERROR: divergence unit",
args.divergence_units,
"not supported!",
file=sys.stderr)
return 1
# Export refined tree and node data
import json
tree_success = Phylo.write(T,
tree_fname,
'newick',
format_branch_length='%1.8f')
print("updated tree written to", tree_fname, file=sys.stdout)
if args.output_node_data:
node_data_fname = args.output_node_data
elif args.alignment:
node_data_fname = '.'.join(
args.alignment.split('.')[:-1]) + '.node_data.json'
else:
node_data_fname = '.'.join(
args.tree.split('.')[:-1]) + '.node_data.json'
write_json(node_data, node_data_fname)
print("node attributes written to", node_data_fname, file=sys.stdout)
return 0 if tree_success else 1
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
anc_seqs = {}
try:
T = read_tree(args.tree)
except (FileNotFoundError, InvalidTreeError) as error:
print("ERROR: %s" % error, file=sys.stderr)
return 1
import numpy as np
missing_internal_node_names = [
n.name is None for n in T.get_nonterminals()
]
if np.all(missing_internal_node_names):
print("\n*** WARNING: Tree has no internal node names!")
print(
"*** Without internal node names, ancestral sequences can't be linked up to the correct node later."
)
print(
"*** If you want to use 'augur export' or `augur translate` later, re-run this command with the output of 'augur refine'."
)
print(
"*** If you haven't run 'augur refine', you can add node names to your tree by running:"
)
print("*** augur refine --tree %s --output-tree <filename>.nwk" %
(args.tree))
print(
"*** And use <filename>.nwk as the tree when running 'ancestral', 'translate', and 'traits'"
)
if any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print(
"ERROR: a reference Fasta is required with VCF-format alignments"
)
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
# Only allow recovery of ambig sites for Fasta-input if TreeTime is version 0.5.6 or newer
# Otherwise it returns nonsense.
from distutils.version import StrictVersion
import treetime
if args.keep_ambiguous and not is_vcf and StrictVersion(
treetime.version) < StrictVersion('0.5.6'):
print(
"ERROR: Keeping ambiguous sites for Fasta-input requires TreeTime version 0.5.6 or newer."
+ "\nYour version is " + treetime.version +
"\nUpdate TreeTime or run without the --keep-ambiguous flag.")
return 1
tt = ancestral_sequence_inference(tree=T,
aln=aln,
ref=ref,
marginal=args.inference,
fill_overhangs=not (args.keep_overhangs))
if is_vcf or args.keep_ambiguous:
# TreeTime overwrites ambig sites on tips during ancestral reconst.
# Put these back in tip sequences now, to avoid misleading
tt.recover_var_ambigs()
anc_seqs['nodes'] = collect_sequences_and_mutations(T, is_vcf)
# add reference sequence to json structure. This is the sequence with
# respect to which mutations on the tree are defined.
if is_vcf:
anc_seqs['reference'] = {"nuc": compress_seq['reference']}
else:
anc_seqs['reference'] = {
"nuc":
"".join(T.root.sequence) if hasattr(T.root, 'sequence') else ''
}
out_name = get_json_name(
args, '.'.join(args.alignment.split('.')[:-1]) + '_mutations.json')
write_json(anc_seqs, out_name)
print("ancestral mutations written to", out_name, file=sys.stdout)
if args.output_sequences:
if args.output_vcf:
print(
"WARNING: augur only supports sequence output for FASTA alignments and not for VCFs.",
file=sys.stderr)
else:
records = [
SeqRecord(Seq(node_data["sequence"]),
id=node_name,
description="")
for node_name, node_data in anc_seqs["nodes"].items()
]
SeqIO.write(records, args.output_sequences, "fasta")
print("ancestral sequences FASTA written to",
args.output_sequences,
file=sys.stdout)
# If VCF, output VCF including new ancestral seqs
if is_vcf:
if args.output_vcf:
vcf_fname = args.output_vcf
else:
vcf_fname = '.'.join(args.alignment.split('.')[:-1]) + '.vcf'
write_vcf(tt.get_tree_dict(keep_var_ambigs=True), vcf_fname)
print("ancestral sequences as vcf-file written to",
vcf_fname,
file=sys.stdout)
return 0
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
anc_seqs = {}
try:
T = read_tree(args.tree)
except (FileNotFoundError, InvalidTreeError) as error:
print("ERROR: %s" % error, file=sys.stderr)
return 1
import numpy as np
missing_internal_node_names = [
n.name is None for n in T.get_nonterminals()
]
if np.all(missing_internal_node_names):
print("\n*** WARNING: Tree has no internal node names!")
print(
"*** Without internal node names, ancestral sequences can't be linked up to the correct node later."
)
print(
"*** If you want to use 'augur export' or `augur translate` later, re-run this command with the output of 'augur refine'."
)
print(
"*** If you haven't run 'augur refine', you can add node names to your tree by running:"
)
print("*** augur refine --tree %s --output-tree <filename>.nwk" %
(args.tree))
print(
"*** And use <filename>.nwk as the tree when running 'ancestral', 'translate', and 'traits'"
)
if any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print(
"ERROR: a reference Fasta is required with VCF-format alignments"
)
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
# Enfore treetime 0.7 or later
from distutils.version import StrictVersion
import treetime
if StrictVersion(treetime.version) < StrictVersion('0.7.0'):
print("ERROR: this version of augur requires TreeTime 0.7 or later.")
return 1
# Infer ambiguous bases if the user has requested that we infer them (either
# explicitly or by default) and the user has not explicitly requested that
# we keep them.
infer_ambiguous = args.infer_ambiguous and not args.keep_ambiguous
tt = ancestral_sequence_inference(tree=T,
aln=aln,
ref=ref,
marginal=args.inference,
fill_overhangs=not (args.keep_overhangs),
infer_tips=infer_ambiguous)
character_map = {}
for x in tt.gtr.profile_map:
if tt.gtr.profile_map[x].sum() == tt.gtr.n_states:
# TreeTime treats all characters that are not valid IUPAC nucleotide chars as fully ambiguous
# To clean up auspice output, we map all those to 'N'
character_map[x] = 'N'
else:
character_map[x] = x
anc_seqs['nodes'] = collect_mutations_and_sequences(
tt,
full_sequences=not is_vcf,
infer_tips=infer_ambiguous,
character_map=character_map)
# add reference sequence to json structure. This is the sequence with
# respect to which mutations on the tree are defined.
if is_vcf:
anc_seqs['reference'] = {"nuc": compress_seq['reference']}
else:
anc_seqs['reference'] = {
"nuc":
"".join(T.root.sequence) if hasattr(T.root, 'sequence') else ''
}
out_name = get_json_name(
args, '.'.join(args.alignment.split('.')[:-1]) + '_mutations.json')
write_json(anc_seqs, out_name)
print("ancestral mutations written to", out_name, file=sys.stdout)
if args.output_sequences:
if args.output_vcf:
print(
"WARNING: augur only supports sequence output for FASTA alignments and not for VCFs.",
file=sys.stderr)
else:
records = [
SeqRecord(Seq(node_data["sequence"]),
id=node_name,
description="")
for node_name, node_data in anc_seqs["nodes"].items()
]
SeqIO.write(records, args.output_sequences, "fasta")
print("ancestral sequences FASTA written to",
args.output_sequences,
file=sys.stdout)
# If VCF, output VCF including new ancestral seqs
if is_vcf:
if args.output_vcf:
vcf_fname = args.output_vcf
else:
vcf_fname = '.'.join(args.alignment.split('.')[:-1]) + '.vcf'
write_vcf(tt.get_tree_dict(keep_var_ambigs=True), vcf_fname)
print("ancestral sequences as vcf-file written to",
vcf_fname,
file=sys.stdout)
return 0
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
tree_meta = {'alignment': args.alignment}
attributes = ['branch_length']
# check if tree is provided an can be read
for fmt in ["newick", "nexus"]:
try:
T = Phylo.read(args.tree, fmt)
tree_meta['input_tree'] = args.tree
break
except:
pass
if T is None:
print("ERROR: reading tree from %s failed." % args.tree)
return -1
if not args.alignment:
# fake alignment to appease treetime when only using it for naming nodes...
if args.ancestral or args.timetree:
print(
"ERROR: alignment is required for ancestral reconstruction or timetree inference"
)
return -1
from Bio import SeqRecord, Seq, Align
seqs = []
for n in T.get_terminals():
seqs.append(
SeqRecord.SeqRecord(seq=Seq.Seq('ACGT'),
id=n.name,
name=n.name,
description=''))
aln = Align.MultipleSeqAlignment(seqs)
elif any([args.alignment.lower().endswith(x)
for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print(
"ERROR: a reference Fasta is required with VCF-format alignments"
)
return -1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
aln = sequences
else:
aln = args.alignment
if args.output:
tree_fname = args.output
else:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '_tt.nwk'
if args.timetree and T:
if args.metadata is None:
print(
"ERROR: meta data with dates is required for time tree reconstruction"
)
return -1
metadata, columns = read_metadata(args.metadata)
if args.year_limit:
args.year_limit.sort()
dates = get_numerical_dates(metadata,
fmt=args.date_fmt,
min_max_year=args.year_limit)
for n in T.get_terminals():
if n.name in metadata and 'date' in metadata[n.name]:
n.raw_date = metadata[n.name]['date']
if args.root and len(
args.root
) == 1: #if anything but a list of seqs, don't send as a list
args.root = args.root[0]
tt = timetree(
tree=T,
aln=aln,
ref=ref,
dates=dates,
confidence=args.date_confidence,
reroot=args.root or 'best',
Tc=args.coalescent if args.coalescent is not None else
0.01, #Otherwise can't set to 0
use_marginal=args.time_marginal or False,
branch_length_mode=args.branch_length_mode or 'auto',
clock_rate=args.clock_rate,
n_iqd=args.n_iqd)
tree_meta['clock'] = {
'rate': tt.date2dist.clock_rate,
'intercept': tt.date2dist.intercept,
'rtt_Tmrca': -tt.date2dist.intercept / tt.date2dist.clock_rate
}
attributes.extend([
'numdate', 'clock_length', 'mutation_length', 'mutations',
'raw_date', 'date'
])
if not is_vcf:
attributes.extend(['sequence'
]) #don't add sequences if VCF - huge!
if args.date_confidence:
attributes.append('num_date_confidence')
elif args.ancestral in ['joint', 'marginal']:
tt = ancestral_sequence_inference(
tree=T,
aln=aln,
ref=ref,
marginal=args.ancestral,
optimize_branch_length=args.branchlengths,
branch_length_mode=args.branch_length_mode)
attributes.extend(['mutation_length', 'mutations'])
if not is_vcf:
attributes.extend(['sequence'
]) #don't add sequences if VCF - huge!
else:
from treetime import TreeAnc
# instantiate treetime for the sole reason to name internal nodes
tt = TreeAnc(tree=T, aln=aln, ref=ref, gtr='JC69', verbose=1)
if is_vcf:
#TreeTime overwrites ambig sites on tips during ancestral reconst.
#Put these back in tip sequences now, to avoid misleading
tt.recover_var_ambigs()
tree_meta['nodes'] = prep_tree(T, attributes, is_vcf)
if T:
import json
tree_success = Phylo.write(T,
tree_fname,
'newick',
format_branch_length='%1.8f')
if args.node_data:
node_data_fname = args.node_data
else:
node_data_fname = '.'.join(
args.alignment.split('.')[:-1]) + '.node_data'
with open(node_data_fname, 'w') as ofile:
meta_success = json.dump(tree_meta, ofile)
#If VCF and ancestral reconst. was done, output VCF including new ancestral seqs
if is_vcf and (args.ancestral or args.timetree):
if args.output_vcf:
vcf_fname = args.output_vcf
else:
vcf_fname = '.'.join(args.alignment.split('.')[:-1]) + '.vcf'
write_vcf(tt.get_tree_dict(keep_var_ambigs=True), vcf_fname)
return 0 if (tree_success and meta_success) else -1
else:
return -1
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
anc_seqs = {}
# check if tree is provided and can be read
for fmt in ["newick", "nexus"]:
try:
T = Phylo.read(args.tree, fmt)
break
except:
pass
if T is None:
print("ERROR: reading tree from %s failed."%args.tree)
return 1
if any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format alignments")
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
# Only allow recovery of ambig sites for Fasta-input if TreeTime is version 0.5.6 or newer
# Otherwise it returns nonsense.
from distutils.version import StrictVersion
import treetime
if args.keep_ambiguous and not is_vcf and StrictVersion(treetime.version) < StrictVersion('0.5.6'):
print("ERROR: Keeping ambiguous sites for Fasta-input requires TreeTime version 0.5.6 or newer."+
"\nYour version is "+treetime.version+
"\nUpdate TreeTime or run without the --keep-ambiguous flag.")
return 1
tt = ancestral_sequence_inference(tree=T, aln=aln, ref=ref, marginal=args.inference,
fill_overhangs = not(args.keep_overhangs))
if is_vcf or args.keep_ambiguous:
# TreeTime overwrites ambig sites on tips during ancestral reconst.
# Put these back in tip sequences now, to avoid misleading
tt.recover_var_ambigs()
anc_seqs['nodes'] = collect_sequences_and_mutations(T, is_vcf)
if args.output:
anc_seqs_fname = args.output
else:
anc_seqs_fname = '.'.join(args.alignment.split('.')[:-1]) + '.anc_seqs.json'
write_json(anc_seqs, anc_seqs_fname)
print("ancestral sequences written to",anc_seqs_fname, file=sys.stdout)
# If VCF, output VCF including new ancestral seqs
if is_vcf:
if args.output_vcf:
vcf_fname = args.output_vcf
else:
vcf_fname = '.'.join(args.alignment.split('.')[:-1]) + '.vcf'
write_vcf(tt.get_tree_dict(keep_var_ambigs=True), vcf_fname)
print("ancestral sequences as vcf-file written to",vcf_fname, file=sys.stdout)
return 0
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
# node data is the dict that will be exported as json
node_data = {'alignment': args.alignment}
# list of node attributes that are to be exported, will grow
attributes = ['branch_length']
# check if tree is provided an can be read
for fmt in ["newick", "nexus"]:
try:
T = Phylo.read(args.tree, fmt)
node_data['input_tree'] = args.tree
break
except:
pass
if T is None:
print("ERROR: reading tree from %s failed."%args.tree)
return 1
if not args.alignment:
# fake alignment to appease treetime when only using it for naming nodes...
if args.timetree:
print("ERROR: alignment is required for ancestral reconstruction or timetree inference")
return 1
from Bio import SeqRecord, Seq, Align
seqs = []
for n in T.get_terminals():
seqs.append(SeqRecord.SeqRecord(seq=Seq.Seq('ACGT'), id=n.name, name=n.name, description=''))
aln = Align.MultipleSeqAlignment(seqs)
elif any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format alignments")
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
# if not specified, construct default output file name with suffix _tt.nwk
if args.output_tree:
tree_fname = args.output_tree
else:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '_tt.nwk'
if args.timetree:
# load meta data and covert dates to numeric
if args.metadata is None:
print("ERROR: meta data with dates is required for time tree reconstruction")
return 1
metadata, columns = read_metadata(args.metadata)
if args.year_bounds:
args.year_bounds.sort()
dates = get_numerical_dates(metadata, fmt=args.date_format,
min_max_year=args.year_bounds)
# save input state string for later export
for n in T.get_terminals():
if n.name in metadata and 'date' in metadata[n.name]:
n.raw_date = metadata[n.name]['date']
if args.root and len(args.root) == 1: #if anything but a list of seqs, don't send as a list
args.root = args.root[0]
tt = refine(tree=T, aln=aln, ref=ref, dates=dates, confidence=args.date_confidence,
reroot=args.root or 'best',
Tc=0.01 if args.coalescent is None else args.coalescent, #use 0.01 as default coalescent time scale
use_marginal = args.date_inference == 'marginal',
branch_length_inference = args.branch_length_inference or 'auto',
clock_rate=args.clock_rate, clock_std=args.clock_std_dev,
clock_filter_iqd=args.clock_filter_iqd)
node_data['clock'] = {'rate': tt.date2dist.clock_rate,
'intercept': tt.date2dist.intercept,
'rtt_Tmrca': -tt.date2dist.intercept/tt.date2dist.clock_rate}
attributes.extend(['numdate', 'clock_length', 'mutation_length', 'raw_date', 'date'])
if args.date_confidence:
attributes.append('num_date_confidence')
else:
from treetime import TreeAnc
# instantiate treetime for the sole reason to name internal nodes
tt = TreeAnc(tree=T, aln=aln, ref=ref, gtr='JC69', verbose=1)
node_data['nodes'] = collect_node_data(T, attributes)
# Export refined tree and node data
import json
tree_success = Phylo.write(T, tree_fname, 'newick', format_branch_length='%1.8f')
print("updated tree written to",tree_fname, file=sys.stdout)
if args.output_node_data:
node_data_fname = args.output_node_data
else:
node_data_fname = '.'.join(args.alignment.split('.')[:-1]) + '.node_data.json'
json_success = write_json(node_data, node_data_fname)
print("node attributes written to",node_data_fname, file=sys.stdout)
return 0 if (tree_success and json_success) else 1
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
# node data is the dict that will be exported as json
node_data = {'alignment': args.alignment}
# list of node attributes that are to be exported, will grow
attributes = ['branch_length']
# check if tree is provided an can be read
for fmt in ["newick", "nexus"]:
try:
T = Phylo.read(args.tree, fmt)
node_data['input_tree'] = args.tree
break
except:
pass
if T is None:
print("ERROR: reading tree from %s failed."%args.tree)
return -1
if not args.alignment:
# fake alignment to appease treetime when only using it for naming nodes...
if args.timetree:
print("ERROR: alignment is required for ancestral reconstruction or timetree inference")
return -1
from Bio import SeqRecord, Seq, Align
seqs = []
for n in T.get_terminals():
seqs.append(SeqRecord.SeqRecord(seq=Seq.Seq('ACGT'), id=n.name, name=n.name, description=''))
aln = Align.MultipleSeqAlignment(seqs)
elif any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format alignments")
return -1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
# if not specified, construct default output file name with suffix _tt.nwk
if args.output_tree:
tree_fname = args.output_tree
else:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '_tt.nwk'
if args.timetree:
# load meta data and covert dates to numeric
if args.metadata is None:
print("ERROR: meta data with dates is required for time tree reconstruction")
return -1
metadata, columns = read_metadata(args.metadata)
if args.year_bounds:
args.year_bounds.sort()
dates = get_numerical_dates(metadata, fmt=args.date_format,
min_max_year=args.year_bounds)
# save input state string for later export
for n in T.get_terminals():
if n.name in metadata and 'date' in metadata[n.name]:
n.raw_date = metadata[n.name]['date']
if args.root and len(args.root) == 1: #if anything but a list of seqs, don't send as a list
args.root = args.root[0]
tt = refine(tree=T, aln=aln, ref=ref, dates=dates, confidence=args.date_confidence,
reroot=args.root or 'best',
Tc=0.01 if args.coalescent is None else args.coalescent, #use 0.01 as default coalescent time scale
use_marginal = args.date_inference == 'marginal',
branch_length_inference = args.branch_length_inference or 'auto',
clock_rate=args.clock_rate, clock_filter_iqd=args.clock_filter_iqd)
node_data['clock'] = {'rate': tt.date2dist.clock_rate,
'intercept': tt.date2dist.intercept,
'rtt_Tmrca': -tt.date2dist.intercept/tt.date2dist.clock_rate}
attributes.extend(['numdate', 'clock_length', 'mutation_length', 'raw_date', 'date'])
if args.date_confidence:
attributes.append('num_date_confidence')
else:
from treetime import TreeAnc
# instantiate treetime for the sole reason to name internal nodes
tt = TreeAnc(tree=T, aln=aln, ref=ref, gtr='JC69', verbose=1)
node_data['nodes'] = collect_node_data(T, attributes)
# Export refined tree and node data
import json
tree_success = Phylo.write(T, tree_fname, 'newick', format_branch_length='%1.8f')
print("updated tree written to",tree_fname, file=sys.stdout)
if args.output_node_data:
node_data_fname = args.output_node_data
else:
node_data_fname = '.'.join(args.alignment.split('.')[:-1]) + '.node_data.json'
json_success = write_json(node_data, node_data_fname)
print("node attributes written to",node_data_fname, file=sys.stdout)
return 0 if (tree_success and json_success) else 1
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
# node data is the dict that will be exported as json
node_data = {'alignment': args.alignment}
# list of node attributes that are to be exported, will grow
attributes = ['branch_length']
try:
T = read_tree(args.tree)
node_data['input_tree'] = args.tree
except (FileNotFoundError, InvalidTreeError) as error:
print("ERROR: %s" % error, file=sys.stderr)
return 1
if not args.alignment:
# fake alignment to appease treetime when only using it for naming nodes...
if args.timetree:
print(
"ERROR: alignment is required for ancestral reconstruction or timetree inference"
)
return 1
from Bio import SeqRecord, Seq, Align
seqs = []
for n in T.get_terminals():
seqs.append(
SeqRecord.SeqRecord(seq=Seq.Seq('ACGT'),
id=n.name,
name=n.name,
description=''))
aln = Align.MultipleSeqAlignment(seqs)
elif any([args.alignment.lower().endswith(x)
for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print(
"ERROR: a reference Fasta is required with VCF-format alignments"
)
return 1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
# if not specified, construct default output file name with suffix _tt.nwk
if args.output_tree:
tree_fname = args.output_tree
elif args.alignment:
tree_fname = '.'.join(args.alignment.split('.')[:-1]) + '_tt.nwk'
else:
tree_fname = '.'.join(args.tree.split('.')[:-1]) + '_tt.nwk'
if args.root and len(
args.root
) == 1: #if anything but a list of seqs, don't send as a list
args.root = args.root[0]
if args.keep_root: # This flag overrides anything specified by 'root'
args.root = None
if args.timetree:
# load meta data and covert dates to numeric
if args.metadata is None:
print(
"ERROR: meta data with dates is required for time tree reconstruction"
)
return 1
metadata, columns = read_metadata(args.metadata)
if args.year_bounds:
args.year_bounds.sort()
dates = get_numerical_dates(metadata,
fmt=args.date_format,
min_max_year=args.year_bounds)
# save input state string for later export
for n in T.get_terminals():
if n.name in metadata and 'date' in metadata[n.name]:
n.raw_date = metadata[n.name]['date']
tt = refine(
tree=T,
aln=aln,
ref=ref,
dates=dates,
confidence=args.date_confidence,
reroot=args.
root, # or 'best', # We now have a default in param spec - this just adds confusion.
Tc=0.01 if args.coalescent is None else
args.coalescent, #use 0.01 as default coalescent time scale
use_marginal=args.date_inference == 'marginal',
branch_length_inference=args.branch_length_inference or 'auto',
clock_rate=args.clock_rate,
clock_std=args.clock_std_dev,
clock_filter_iqd=args.clock_filter_iqd,
covariance=args.covariance,
resolve_polytomies=(not args.keep_polytomies))
node_data['clock'] = {
'rate': tt.date2dist.clock_rate,
'intercept': tt.date2dist.intercept,
'rtt_Tmrca': -tt.date2dist.intercept / tt.date2dist.clock_rate
}
attributes.extend(
['numdate', 'clock_length', 'mutation_length', 'raw_date', 'date'])
if args.date_confidence:
attributes.append('num_date_confidence')
else:
from treetime import TreeAnc
# instantiate treetime for the sole reason to name internal nodes
if args.root:
if args.root == 'best':
print(
"Warning: To root without inferring a timetree, you must specify an explicit outgroup."
)
print(
"\tProceeding without re-rooting. To suppress this message, use '--keep-root'.\n"
)
elif args.root in ['least-squares', 'min_dev', 'oldest']:
raise TypeError(
"The rooting option '%s' is only available when inferring a timetree. Please specify an explicit outgroup."
% args.root)
else:
T.root_with_outgroup(args.root)
tt = TreeAnc(tree=T, aln=aln, ref=ref, gtr='JC69', verbose=1)
node_data['nodes'] = collect_node_data(T, attributes)
# Export refined tree and node data
import json
tree_success = Phylo.write(T,
tree_fname,
'newick',
format_branch_length='%1.8f')
print("updated tree written to", tree_fname, file=sys.stdout)
if args.output_node_data:
node_data_fname = args.output_node_data
elif args.alignment:
node_data_fname = '.'.join(
args.alignment.split('.')[:-1]) + '.node_data.json'
else:
node_data_fname = '.'.join(
args.tree.split('.')[:-1]) + '.node_data.json'
write_json(node_data, node_data_fname)
print("node attributes written to", node_data_fname, file=sys.stdout)
return 0 if tree_success else 1
def run(args):
## read tree and data, if reading data fails, return with error code
tree = Phylo.read(args.tree, 'newick')
# If genes is a file, read in the genes to translate
if args.genes and len(args.genes) == 1 and os.path.isfile(args.genes[0]):
genes = get_genes_from_file(args.genes[0])
else:
genes = args.genes
## check file format and read in sequences
is_vcf = False
if any([args.ancestral_sequences.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format input")
return -1
compress_seq = read_vcf(args.ancestral_sequences, args.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
node_data = read_node_data(args.ancestral_sequences, args.tree)
if node_data is None:
print("ERROR: could not read node data (incl sequences)")
return -1
# extract sequences from node meta data
sequences = {}
for k,v in node_data['nodes'].items():
if 'sequence' in v:
sequences[k] = v['sequence']
## load features; only requested features if genes given
features = load_features(args.reference_sequence, genes)
print("Read in {} features from reference sequence file".format(len(features)))
if features is None:
print("ERROR: could not read features of reference sequence file")
return -1
### translate every feature - but not 'nuc'!
translations = {}
deleted = []
for fname, feat in features.items():
if is_vcf:
trans = translate_vcf_feature(sequences, ref, feat)
if trans:
translations[fname] = trans
else:
deleted.append(fname)
else:
if feat.type != 'source':
translations[fname] = translate_feature(sequences, feat)
if len(deleted) != 0:
print("{} genes had no mutations and so have been be excluded.".format(len(deleted)))
## glob the annotations for later auspice export
annotations = {}
for fname, feat in features.items():
increment = 0 if feat.type != 'source' else 1 #'nuc' goes to 0, unsure why - make 1
annotations[fname] = {'start':int(feat.location.start)+increment,
'end':int(feat.location.end),
'strand': feat.location.strand}
if is_vcf: #need to add our own nuc
annotations['nuc'] = {'start': 0,
'end': len(ref),
'strand': 1}
## determine amino acid mutations for each node
if is_vcf:
aa_muts = assign_aa_vcf(tree, translations)
else:
aa_muts = {}
for n in tree.get_nonterminals():
for c in n:
aa_muts[c.name]={"aa_muts":{}}
for fname, aln in translations.items():
for c in n:
if c.name in aln and n.name in aln:
tmp = [construct_mut(a, int(pos+1), d) for pos, (a,d) in
enumerate(zip(aln[n.name], aln[c.name])) if a!=d]
aa_muts[c.name]["aa_muts"][fname] = tmp
else:
print("no sequence pair for nodes %s-%s"%(c.name, n.name))
write_json({'annotations':annotations, 'nodes':aa_muts}, args.output)
print("amino acid mutations written to",args.output, file=sys.stdout)
## write alignments to file is requested
if args.alignment_output:
if is_vcf:
## write VCF-style output if requested
fileEndings = -1
if args.alignment_output.lower().endswith('.gz'):
fileEndings = -2
vcf_out_ref = '.'.join(args.alignment_output.split('.')[:fileEndings]) + '_reference.fasta'
write_VCF_translation(translations, args.alignment_output, vcf_out_ref)
else:
## write fasta-style output if requested
if '%GENE' in args.alignment_output:
for fname, seqs in translations.items():
SeqIO.write([SeqRecord.SeqRecord(seq=Seq.Seq(s), id=sname, name=sname, description='')
for sname, s in seqs.items()],
args.alignment_output.replace('%GENE', fname), 'fasta')
else:
print("ERROR: alignment output file does not contain '%GENE', so will not be written.")
def run(args):
## read tree and data, if reading data fails, return with error code
tree = Phylo.read(args.tree, 'newick')
# If genes is a file, read in the genes to translate
if args.genes and len(args.genes) == 1 and os.path.isfile(args.genes[0]):
genes = get_genes_from_file(args.genes[0])
else:
genes = args.genes
## check file format and read in sequences
is_vcf = False
if any([
args.ancestral_sequences.lower().endswith(x)
for x in ['.vcf', '.vcf.gz']
]):
if not args.vcf_reference:
print("ERROR: a reference Fasta is required with VCF-format input")
return 1
compress_seq = read_vcf(args.ancestral_sequences, args.vcf_reference)
sequences = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
node_data = read_node_data(args.ancestral_sequences, args.tree)
if node_data is None:
print("ERROR: could not read node data (incl sequences)")
return 1
# extract sequences from node meta data
sequences = {}
for k, v in node_data['nodes'].items():
if 'sequence' in v:
sequences[k] = v['sequence']
## load features; only requested features if genes given
features = load_features(args.reference_sequence, genes)
print("Read in {} features from reference sequence file".format(
len(features)))
if features is None:
print("ERROR: could not read features of reference sequence file")
return 1
### translate every feature - but not 'nuc'!
translations = {}
deleted = []
for fname, feat in features.items():
if is_vcf:
trans = translate_vcf_feature(sequences, ref, feat)
if trans:
translations[fname] = trans
else:
deleted.append(fname)
else:
if feat.type != 'source':
translations[fname] = translate_feature(sequences, feat)
if len(deleted) != 0:
print("{} genes had no mutations and so have been be excluded.".format(
len(deleted)))
## glob the annotations for later auspice export
#
# Note that BioPython FeatureLocations use
# "Pythonic" coordinates: [zero-origin, half-open)
# Starting with augur v6 we use GFF coordinates: [one-origin, inclusive]
annotations = {}
for fname, feat in features.items():
annotations[fname] = {
'seqid': args.reference_sequence,
'type': feat.type,
'start': int(feat.location.start) + 1,
'end': int(feat.location.end),
'strand': '+' if feat.location.strand else '-'
}
if is_vcf: #need to add our own nuc
annotations['nuc'] = {
'seqid': args.reference_sequence,
'type': feat.type,
'start': 1,
'end': len(ref),
'strand': '+'
}
## determine amino acid mutations for each node
try:
if is_vcf:
aa_muts = assign_aa_vcf(tree, translations)
else:
aa_muts = assign_aa_fasta(tree, translations)
except MissingNodeError as err:
print("\n*** ERROR: Some/all nodes have no node names!")
print(
"*** Please check you are providing the tree output by 'augur refine'."
)
print(
"*** If you haven't run 'augur refine', please add node names to your tree by running:"
)
print("*** augur refine --tree %s --output-tree <filename>.nwk" %
(args.tree))
print(
"*** And use <filename>.nwk as the tree when running 'ancestral', 'translate', and 'traits'"
)
return 1
except MismatchNodeError as err:
print("\n*** ERROR: Mismatch between node names in %s and in %s" %
(args.tree, args.ancestral_sequences))
print(
"*** Ensure you are using the same tree you used to run 'ancestral' as input here."
)
print(
"*** Or, re-run 'ancestral' using %s, then use the new %s as input here."
% (args.tree, args.ancestral_sequences))
return 1
output_data = {'annotations': annotations, 'nodes': aa_muts}
if is_vcf:
output_data['reference'] = {}
for fname in translations:
output_data['reference'][fname] = translations[fname]['reference']
else:
output_data['reference'] = aa_muts[tree.root.name]['aa_sequences']
out_name = get_json_name(
args, '.'.join(args.tree.split('.')[:-1]) + '_aa-mutations.json')
write_json(output_data, out_name)
print("amino acid mutations written to", out_name, file=sys.stdout)
## write alignments to file is requested
if args.alignment_output:
if is_vcf:
## write VCF-style output if requested
fileEndings = -1
if args.alignment_output.lower().endswith('.gz'):
fileEndings = -2
vcf_out_ref = args.vcf_reference_output or '.'.join(
args.alignment_output.split('.')
[:fileEndings]) + '_reference.fasta'
write_VCF_translation(translations, args.alignment_output,
vcf_out_ref)
else:
## write fasta-style output if requested
if '%GENE' in args.alignment_output:
for fname, seqs in translations.items():
SeqIO.write([
SeqRecord.SeqRecord(seq=Seq.Seq(s),
id=sname,
name=sname,
description='')
for sname, s in seqs.items()
], args.alignment_output.replace('%GENE', fname), 'fasta')
else:
print(
"ERROR: alignment output file does not contain '%GENE', so will not be written."
)
def run(args):
# check alignment type, set flags, read in if VCF
is_vcf = False
ref = None
anc_seqs = {}
# check if tree is provided and can be read
for fmt in ["newick", "nexus"]:
try:
T = Phylo.read(args.tree, fmt)
break
except:
pass
if T is None:
print("ERROR: reading tree from %s failed." % args.tree)
return -1
if any([args.alignment.lower().endswith(x) for x in ['.vcf', '.vcf.gz']]):
if not args.vcf_reference:
print(
"ERROR: a reference Fasta is required with VCF-format alignments"
)
return -1
compress_seq = read_vcf(args.alignment, args.vcf_reference)
aln = compress_seq['sequences']
ref = compress_seq['reference']
is_vcf = True
else:
aln = args.alignment
tt = ancestral_sequence_inference(tree=T,
aln=aln,
ref=ref,
marginal=args.inference)
if is_vcf:
# TreeTime overwrites ambig sites on tips during ancestral reconst.
# Put these back in tip sequences now, to avoid misleading
tt.recover_var_ambigs()
anc_seqs['nodes'] = collect_sequences_and_mutations(T, is_vcf)
if args.output:
anc_seqs_fname = args.output
else:
anc_seqs_fname = '.'.join(
args.alignment.split('.')[:-1]) + '.anc_seqs.json'
anc_seqs_success = write_json(anc_seqs, anc_seqs_fname)
print("ancestral sequences written to", anc_seqs_fname, file=sys.stdout)
# If VCF, output VCF including new ancestral seqs
if is_vcf:
if args.output_vcf:
vcf_fname = args.output_vcf
else:
vcf_fname = '.'.join(args.alignment.split('.')[:-1]) + '.vcf'
write_vcf(tt.get_tree_dict(keep_var_ambigs=True), vcf_fname)
print("ancestral sequences as vcf-file written to",
vcf_fname,
file=sys.stdout)
if anc_seqs_success:
return 0
else:
return 1