def taxonomy_hash(self):
'''Read in the taxonomy and return as a hash of name: taxonomy,
where taxonomy is an array of strings.'''
gtns = Getaxnseq()
with open(self.taxtastic_taxonomy_path()) as tax:
with open(self.taxtastic_seqinfo_path()) as seqinfo:
return gtns.read_taxtastic_taxonomy_and_seqinfo(tax, seqinfo)
def test_hello_world(self):
with tempfile.NamedTemporaryFile(
prefix='graftm_test_getaxnseq') as tmp_seq:
with tempfile.NamedTemporaryFile(
prefix='graftm_test_getaxnseq') as tmp_tax:
Getaxnseq().write_taxonomy_and_seqinfo_files(
{
'seq1': ['k__me', 'p__you'],
'seq2': []
}, tmp_tax.name, tmp_seq.name)
expected = sorted([
','.join(p) + '\n'
for p in [['seqname', 'tax_id'], ['seq2', 'Root'],
['seq1', 'p__you']]
])
with open(tmp_seq.name) as f:
self.assertEqual(expected, sorted(f.readlines()))
expected = '\n'.join([
"tax_id,parent_id,rank,tax_name,root,rank_0,rank_1",
"Root,Root,root,Root,Root,,",
"k__me,Root,rank_0,k__me,Root,k__me,",
"p__you,k__me,rank_1,p__you,Root,k__me,p__you"
]) + "\n"
with open(tmp_tax.name) as f:
self.assertEqual(expected, f.read())
def test_more_than_seven_levels(self):
with tempfile.NamedTemporaryFile(prefix='graftm_test_getaxnseq') as tmp_seq:
with tempfile.NamedTemporaryFile(prefix='graftm_test_getaxnseq') as tmp_tax:
Getaxnseq().write_taxonomy_and_seqinfo_files({'seq1': string.split('k__me p__you c__came over for great spaghetti extra'),
'seq1.5': string.split('k__me p__you c__came over for great spaghetti'),
'seq2': []},
tmp_tax.name,
tmp_seq.name)
expected = "\n".join([','.join(p) for p in [['seqname','tax_id'],
['seq2','Root'],
['seq1','extra'],
['seq1.5','spaghetti']]])+"\n"
self.assertEqual(expected, open(tmp_seq.name).read())
expected = '\n'.join(["tax_id,parent_id,rank,tax_name,root,rank_0,rank_1,rank_2,rank_3,rank_4,rank_5,rank_6,rank_7",
"Root,Root,root,Root,Root,,,,,,,,",
"k__me,Root,rank_0,k__me,Root,k__me,,,,,,,",
"p__you,k__me,rank_1,p__you,Root,k__me,p__you,,,,,,",
"c__came,p__you,rank_2,c__came,Root,k__me,p__you,c__came,,,,,",
"over,c__came,rank_3,over,Root,k__me,p__you,c__came,over,,,,",
"for,over,rank_4,for,Root,k__me,p__you,c__came,over,for,,,",
"great,for,rank_5,great,Root,k__me,p__you,c__came,over,for,great,,",
"spaghetti,great,rank_6,spaghetti,Root,k__me,p__you,c__came,over,for,great,spaghetti,",
"extra,spaghetti,rank_7,extra,Root,k__me,p__you,c__came,over,for,great,spaghetti,extra"])+"\n"
self.assertEqual(expected, open(tmp_tax.name).read())
def test_more_than_seven_levels(self):
with tempfile.NamedTemporaryFile(
prefix='graftm_test_getaxnseq') as tmp_seq:
with tempfile.NamedTemporaryFile(
prefix='graftm_test_getaxnseq') as tmp_tax:
Getaxnseq().write_taxonomy_and_seqinfo_files(
{
'seq1':
string.split(
'k__me p__you c__came over for great spaghetti extra'
),
'seq1.5':
string.split(
'k__me p__you c__came over for great spaghetti'),
'seq2': []
}, tmp_tax.name, tmp_seq.name)
expected = "\n".join([
','.join(p)
for p in [['seqname', 'tax_id'], ['seq2', 'Root'],
['seq1', 'spaghetti'], ['seq1.5', 'spaghetti']]
]) + "\n"
self.assertEqual(expected, open(tmp_seq.name).read())
expected = '\n'.join([
'tax_id,parent_id,rank,tax_name,root,kingdom,phylum,class,order,family,genus,species',
'Root,Root,root,Root,Root,,,,,,,',
'k__me,Root,kingdom,k__me,Root,k__me,,,,,,',
'p__you,k__me,phylum,p__you,Root,k__me,p__you,,,,,',
'c__came,p__you,class,c__came,Root,k__me,p__you,c__came,,,,',
'over,c__came,order,over,Root,k__me,p__you,c__came,over,,,',
'for,over,family,for,Root,k__me,p__you,c__came,over,for,,',
'great,for,genus,great,Root,k__me,p__you,c__came,over,for,great,',
'spaghetti,great,species,spaghetti,Root,k__me,p__you,c__came,over,for,great,spaghetti',
]) + "\n"
self.assertEqual(expected, open(tmp_tax.name).read())
def test_read_taxtastic_taxonomy_and_seqinfo(self):
tax = StringIO('\n'.join(['tax_id,parent_id,rank,tax_name,root,kingdom,phylum,class,order,family,genus,species',
'Root,Root,root,Root,Root,,,,,,,',
'k__me,Root,kingdom,k__me,Root,k__me,,,,,,',
'p__you,k__me,phylum,p__you,Root,k__me,p__you,,,,,'])+"\n")
seq = StringIO("\n".join([','.join(p) for p in [['seqname','tax_id'],
['seq2','Root'],
['seq1','p__you']]])+"\n")
self.assertEqual({'seq1': ['k__me','p__you'],
'seq2': []},
Getaxnseq().read_taxtastic_taxonomy_and_seqinfo(tax, seq))
def __init__(self, tree, taxonomy, seqinfo=None):
'''
Parameters
----------
tree : dendropy.Tree
dendropy.Tree object
taxonomy : string
Path to a file containing taxonomy information about the tree,
either in Greengenes or taxtastic format (seqinfo file must also
be provided if taxonomy is in taxtastic format).
seqinfo : string
Path to a seqinfo file. This is a .csv file with the first column
denoting the sequence name, and the second column, its most resolved
taxonomic rank.
'''
self.encountered_nodes = {}
self.encountered_taxonomies = set()
self.tree = tree
# Read in taxonomy
logging.info("Reading in taxonomy")
if seqinfo:
logging.info("Importing taxtastic taxonomy from files: %s and %s" %
(taxonomy, seqinfo))
gtns = Getaxnseq()
self.taxonomy = gtns.read_taxtastic_taxonomy_and_seqinfo(
open(taxonomy), open(seqinfo))
else:
try:
logging.info("Reading Greengenes style taxonomy")
self.taxonomy = GreenGenesTaxonomy.read_file(taxonomy).taxonomy
except MalformedGreenGenesTaxonomyException:
raise Exception("Failed to read taxonomy as a Greengenes \
formatted file. Was a taxtastic style \
taxonomy provided with no seqinfo file?")
def __init__(self, tree, taxonomy, seqinfo=None):
'''
Parameters
----------
tree : dendropy.Tree
dendropy.Tree object
taxonomy : string
Path to a file containing taxonomy information about the tree,
either in Greengenes or taxtastic format (seqinfo file must also
be provided if taxonomy is in taxtastic format).
seqinfo : string
Path to a seqinfo file. This is a .csv file with the first column
denoting the sequence name, and the second column, its most resolved
taxonomic rank.
'''
self.encountered_nodes = {}
self.encountered_taxonomies = set()
self.tree = tree
# Read in taxonomy
logging.info("Reading in taxonomy")
if seqinfo:
logging.info("Importing taxtastic taxonomy from files: %s and %s" % (taxonomy, seqinfo))
gtns = Getaxnseq()
self.taxonomy = gtns.read_taxtastic_taxonomy_and_seqinfo(open(taxonomy), open(seqinfo))
else:
try:
logging.info("Reading Greengenes style taxonomy")
self.taxonomy = GreenGenesTaxonomy.read_file(taxonomy).taxonomy
except MalformedGreenGenesTaxonomyException:
raise Exception("Failed to read taxonomy as a Greengenes \
formatted file. Was a taxtastic style \
taxonomy provided with no seqinfo file?")
def test_hello_world(self):
with tempfile.NamedTemporaryFile(
prefix='graftm_test_getaxnseq') as tmp_seq:
with tempfile.NamedTemporaryFile(
prefix='graftm_test_getaxnseq') as tmp_tax:
Getaxnseq().write_taxonomy_and_seqinfo_files(
{
'seq1': ['k__me', 'p__you'],
'seq2': []
}, tmp_tax.name, tmp_seq.name)
expected = "\n".join([
','.join(p) for p in [['seqname', 'tax_id'],
['seq2', 'Root'], ['seq1', 'p__you']]
]) + "\n"
self.assertEqual(expected, open(tmp_seq.name).read())
expected = '\n'.join([
'tax_id,parent_id,rank,tax_name,root,kingdom,phylum,class,order,family,genus,species',
'Root,Root,root,Root,Root,,,,,,,',
'k__me,Root,kingdom,k__me,Root,k__me,,,,,,',
'p__you,k__me,phylum,p__you,Root,k__me,p__you,,,,,'
]) + "\n"
self.assertEqual(expected, open(tmp_tax.name).read())
def update(self, **kwargs):
'''
Update an existing GraftM package with new sequences and taxonomy. If no
taxonomy is provided, attempt to decorate the new sequences with
pre-existing taxonomy.
Parameters
----------
input_sequence_path: str
Path to FASTA file containing sequences to add to the update GraftM
package
input_taxonomy_path: str
Taxonomy corresponding to the sequences in input_sequence_path. If None,
then attempt to assign taxonomy by decorating the tree made out of all
sequences.
input_graftm_package_path: str
Path to the directory of the GraftM package that is to be updated
output_graftm_package_path: str
Path to the directory to which the new GraftM package will be
written to
'''
input_sequence_path = kwargs.pop('input_sequence_path')
input_taxonomy_path = kwargs.pop('input_taxonomy_path', None)
input_graftm_package_path = kwargs.pop('input_graftm_package_path')
output_graftm_package_path = kwargs.pop('output_graftm_package_path')
threads = kwargs.pop(
'threads',
UpdateDefaultOptions.threads) #TODO: add to user options
if len(kwargs) > 0:
raise Exception("Unexpected arguments detected: %s" % kwargs)
logging.info("Reading previous GraftM package")
old_gpkg = GraftMPackage.acquire(input_graftm_package_path)
min_input_version = 3
if old_gpkg.version < min_input_version:
raise InsufficientGraftMPackageVersion(
"GraftM below version %s cannot be updated using the update function."
% min_input_version +
" Unaligned sequences are not included in these packages, therefore no new"
" alignment/HMM/Tree can be created")
new_gpkg = UpdatedGraftMPackage()
new_gpkg.output = output_graftm_package_path
new_gpkg.name = output_graftm_package_path.replace(".gpkg", "")
#######################################
### Collect all unaligned sequences ###
logging.info("Concatenating unaligned sequence files")
new_gpkg.unaligned_sequences = "%s_sequences.fa" % (
new_gpkg.name
) #TODO: replace hard-coded paths like this with tempfiles
self._concatenate_file(
[old_gpkg.unaligned_sequence_database_path(), input_sequence_path],
new_gpkg.unaligned_sequences)
#########################################################
### Parse taxonomy info up front so errors come early ###
if input_taxonomy_path:
logging.info("Reading new taxonomy information")
input_taxonomy = GreenGenesTaxonomy.read_file(input_taxonomy_path)
original_taxonomy_hash = old_gpkg.taxonomy_hash()
total_taxonomy_hash = original_taxonomy_hash.copy()
total_taxonomy_hash.update(input_taxonomy.taxonomy)
num_duplicate_taxonomies = len(total_taxonomy_hash) - \
len(input_taxonomy.taxonomy) - \
len(original_taxonomy_hash)
logging.debug(
"Found %i taxonomic definitions in common between the previous and updated taxonomies"
% num_duplicate_taxonomies)
if num_duplicate_taxonomies > 0:
logging.warn(
"Found %i taxonomic definitions in common between the previous and updated taxonomies. Using the updated taxonomy in each case."
% num_duplicate_taxonomies)
###############################
### Re-construct alignments ###
logging.info("Multiple sequence aligning all sequences")
new_gpkg.aligned_sequences = "%s_mafft_alignment.fa" % (new_gpkg.name)
self._align_sequences(new_gpkg.unaligned_sequences,
new_gpkg.aligned_sequences, threads)
########################
### Re-construct HMM ###
logging.info("Creating HMM from alignment")
new_gpkg.hmm = "%s.hmm" % (new_gpkg.name)
new_gpkg.hmm_alignment = "%s_hmm_alignment.fa" % (new_gpkg.name)
self._get_hmm_from_alignment(new_gpkg.aligned_sequences, new_gpkg.hmm,
new_gpkg.hmm_alignment)
#########################
### Re-construct tree ###
logging.info("Generating phylogenetic tree")
new_gpkg.unrooted_tree = "%s.tre" % (new_gpkg.name)
new_gpkg.unrooted_tree_log = "%s.tre.log" % (new_gpkg.name)
new_gpkg.package_type, new_gpkg.hmm_length = self._pipe_type(
old_gpkg.alignment_hmm_path())
new_gpkg.unrooted_gpkg_tree_log, new_gpkg.unrooted_gpkg_tree = \
self._build_tree(new_gpkg.hmm_alignment, new_gpkg.name,
new_gpkg.package_type, self.fasttree)
##############################################
### Re-root and decorate tree if necessary ###
if input_taxonomy_path:
new_gpkg.gpkg_tree_log = new_gpkg.unrooted_tree_log
new_gpkg.gpkg_tree = new_gpkg.unrooted_gpkg_tree
else:
logging.info("Finding taxonomy for new sequences")
rerooter = Rerooter()
old_tree = Tree.get(path=old_gpkg.reference_package_tree_path(),
schema='newick')
new_tree = Tree.get(path=new_gpkg.unrooted_gpkg_tree,
schema='newick')
old_tree = rerooter.reroot(old_tree)
new_tree = rerooter.reroot(new_tree)
# TODO: Shouldn't call an underscore method, eventually use
# Rerooter instead.
rerooted_tree = rerooter.reroot_by_tree(old_tree, new_tree)
new_gpkg.gpkg_tree = "%s_gpkg.tree" % new_gpkg.name
td = TreeDecorator(rerooted_tree,
old_gpkg.taxtastic_taxonomy_path(),
old_gpkg.taxtastic_seqinfo_path())
with tempfile.NamedTemporaryFile(suffix='tsv') as taxonomy:
td.decorate(new_gpkg.gpkg_tree, taxonomy.name, True)
total_taxonomy_hash = GreenGenesTaxonomy.read_file(
taxonomy.name).taxonomy
################################
### Generating tree log file ###
logging.info("Generating phylogenetic tree log file")
new_gpkg.gpkg_tree = "%s_gpkg.tree" % new_gpkg.name
new_gpkg.gpkg_tree_log = "%s_gpkg.tree.log" % new_gpkg.name
self._generate_tree_log_file(new_gpkg.unrooted_tree,
new_gpkg.hmm_alignment,
new_gpkg.gpkg_tree,
new_gpkg.gpkg_tree_log,
new_gpkg.package_type, self.fasttree)
################################
### Creating taxtastic files ###
logging.info("Writing new taxonomy files")
new_gpkg.tt_seqinfo = "%s_seqinfo.csv" % new_gpkg.name
new_gpkg.tt_taxonomy = "%s_taxonomy.csv" % new_gpkg.name
gtns = Getaxnseq()
gtns.write_taxonomy_and_seqinfo_files(total_taxonomy_hash,
new_gpkg.tt_taxonomy,
new_gpkg.tt_seqinfo)
######################
### Compile refpkg ###
logging.info("Compiling pplacer refpkg")
new_gpkg.refpkg = "%s.refpkg" % (new_gpkg.name)
refpkg = self._taxit_create(new_gpkg.name, new_gpkg.hmm_alignment,
new_gpkg.gpkg_tree, new_gpkg.gpkg_tree_log,
new_gpkg.tt_taxonomy, new_gpkg.tt_seqinfo,
new_gpkg.refpkg, True)
#####################################
### Re-construct diamond database ###
logging.info("Recreating DIAMOND DB")
new_gpkg.diamond_database = "%s.dmnd" % (new_gpkg.name)
self._create_dmnd_database(new_gpkg.unaligned_sequences, new_gpkg.name)
####################
### Compile gpkg ###
logging.info("Compiling GraftM package")
new_gpkg.name = "%s.gpkg" % new_gpkg.name
GraftMPackageVersion3.compile(
new_gpkg.name,
new_gpkg.refpkg,
new_gpkg.hmm,
new_gpkg.diamond_database,
self._define_range(new_gpkg.unaligned_sequences),
new_gpkg.unaligned_sequences,
search_hmm_files=old_gpkg.search_hmm_paths())
###################
### Test it out ###
logging.info("Testing newly updated GraftM package works")
self._test_package(new_gpkg.name)
logging.info("Finished")
def main(self, **kwargs):
alignment = kwargs.pop('alignment',None)
sequences = kwargs.pop('sequences',None)
taxonomy = kwargs.pop('taxonomy',None)
rerooted_tree = kwargs.pop('rerooted_tree',None)
unrooted_tree = kwargs.pop('unrooted_tree',None)
tree_log = kwargs.pop('tree_log', None)
prefix = kwargs.pop('prefix', None)
rerooted_annotated_tree = kwargs.pop('rerooted_annotated_tree', None)
user_hmm = kwargs.pop('hmm', None)
search_hmm_files = kwargs.pop('search_hmm_files',None)
min_aligned_percent = kwargs.pop('min_aligned_percent',0.01)
taxtastic_taxonomy = kwargs.pop('taxtastic_taxonomy', None)
taxtastic_seqinfo = kwargs.pop('taxtastic_seqinfo', None)
force_overwrite = kwargs.pop('force',False)
graftm_package = kwargs.pop('graftm_package',False)
dereplication_level = kwargs.pop('dereplication_level',False)
threads = kwargs.pop('threads',5)
if len(kwargs) > 0:
raise Exception("Unexpected arguments detected: %s" % kwargs)
seqio = SequenceIO()
locus_name = (os.path.basename(sequences).split('.')[0]
if sequences
else os.path.basename(alignment).split('.')[0])
tmp = tempdir.TempDir()
base = os.path.join(tmp.name, locus_name)
insufficiently_aligned_sequences = [None]
removed_sequence_names = []
tempfiles_to_close = []
if prefix:
output_gpkg_path = prefix
else:
output_gpkg_path = "%s.gpkg" % locus_name
if os.path.exists(output_gpkg_path):
if force_overwrite:
logging.warn("Deleting previous directory %s" % output_gpkg_path)
shutil.rmtree(output_gpkg_path)
else:
raise Exception("Cowardly refusing to overwrite gpkg to already existing %s" % output_gpkg_path)
logging.info("Building gpkg for %s" % output_gpkg_path)
# Read in taxonomy somehow
gtns = Getaxnseq()
if rerooted_annotated_tree:
logging.info("Building seqinfo and taxonomy file from input annotated tree")
taxonomy_definition = TaxonomyExtractor().taxonomy_from_annotated_tree(\
Tree.get(path=rerooted_annotated_tree, schema='newick'))
elif taxonomy:
logging.info("Building seqinfo and taxonomy file from input taxonomy")
taxonomy_definition = GreenGenesTaxonomy.read_file(taxonomy).taxonomy
elif taxtastic_seqinfo and taxtastic_taxonomy:
logging.info("Reading taxonomy from taxtastic taxonomy and seqinfo files")
taxonomy_definition = gtns.read_taxtastic_taxonomy_and_seqinfo\
(open(taxtastic_taxonomy),
open(taxtastic_seqinfo))
else:
raise Exception("Taxonomy is required somehow e.g. by --taxonomy or --rerooted_annotated_tree")
# Check for duplicates
logging.info("Checking for duplicate sequences")
dup = self._check_for_duplicate_sequence_names(sequences)
if dup:
raise Exception("Found duplicate sequence name '%s' in sequences input file" % dup)
output_alignment_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='.aln.faa')
tempfiles_to_close.append(output_alignment_fh)
output_alignment = output_alignment_fh.name
if user_hmm:
align_hmm = user_hmm
else:
align_hmm_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='_align.hmm')
tempfiles_to_close.append(align_hmm_fh)
align_hmm = align_hmm_fh.name
if alignment:
dup = self._check_for_duplicate_sequence_names(alignment)
if dup:
raise Exception("Found duplicate sequence name '%s' in alignment input file" % dup)
ptype = self._get_hmm_from_alignment(alignment,
align_hmm,
output_alignment)
else:
logging.info("Aligning sequences to create aligned FASTA file")
ptype, output_alignment = self._align_and_create_hmm(sequences, alignment, user_hmm,
align_hmm, output_alignment, threads)
logging.info("Checking for incorrect or fragmented reads")
insufficiently_aligned_sequences = self._check_reads_hit(open(output_alignment),
min_aligned_percent)
while len(insufficiently_aligned_sequences) > 0:
logging.warn("One or more alignments do not span > %.2f %% of HMM" % (min_aligned_percent*100))
for s in insufficiently_aligned_sequences:
logging.warn("Insufficient alignment of %s, not including this sequence" % s)
sequences2_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='.faa')
tempfiles_to_close.append(sequences2_fh)
sequences2 = sequences2_fh.name
num_sequences = self._remove_sequences_from_alignment(insufficiently_aligned_sequences,
sequences,
sequences2)
sequences = sequences2
if alignment:
alignment2_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='.aln.faa')
tempfiles_to_close.append(alignment2_fh)
alignment2 = alignment2_fh.name
num_sequences = self._remove_sequences_from_alignment(insufficiently_aligned_sequences,
alignment,
alignment2)
alignment = alignment2
for name in insufficiently_aligned_sequences:
if rerooted_tree or rerooted_annotated_tree:
logging.warning('''Sequence %s in provided alignment does not meet the --min_aligned_percent cutoff. This sequence will be removed from the tree
in the final GraftM package. If you are sure these sequences are correct, turn off the --min_aligned_percent cutoff, provide it with a 0 (e.g. --min_aligned_percent 0) ''' % name)
removed_sequence_names.append(name)
logging.info("After removing %i insufficiently aligned sequences, left with %i sequences" % (len(insufficiently_aligned_sequences), num_sequences))
if num_sequences < 4:
raise Exception("Too few sequences remaining in alignment after removing insufficiently aligned sequences: %i" % num_sequences)
else:
logging.info("Reconstructing the alignment and HMM from remaining sequences")
output_alignment_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='.aln.faa')
tempfiles_to_close.append(output_alignment_fh)
output_alignment = output_alignment_fh.name
if not user_hmm:
align_hmm_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='.hmm')
tempfiles_to_close.append(align_hmm_fh)
align_hmm = align_hmm_fh.name
ptype, output_alignment= self._align_and_create_hmm(sequences, alignment, user_hmm,
align_hmm, output_alignment, threads)
logging.info("Checking for incorrect or fragmented reads")
insufficiently_aligned_sequences = self._check_reads_hit(open(output_alignment),
min_aligned_percent)
if not search_hmm_files:
search_hmm_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='_search.hmm')
tempfiles_to_close.append(search_hmm_fh)
search_hmm = search_hmm_fh.name
self._create_search_hmm(sequences, taxonomy_definition, search_hmm, dereplication_level, threads)
search_hmm_files = [search_hmm]
# Make sure each sequence has been assigned a taxonomy:
aligned_sequence_objects = seqio.read_fasta_file(output_alignment)
unannotated = []
for s in aligned_sequence_objects:
if s.name not in taxonomy_definition:
unannotated.append(s.name)
if len(unannotated) > 0:
for s in unannotated:
logging.error("Unable to find sequence '%s' in the taxonomy definition" % s)
raise Exception("All sequences must be assigned a taxonomy, cannot continue")
logging.debug("Looking for non-standard characters in aligned sequences")
self._mask_strange_sequence_letters(aligned_sequence_objects, ptype)
# Deduplicate sequences - pplacer cannot handle these
logging.info("Deduplicating sequences")
dedup = Deduplicator()
deduplicated_arrays = dedup.deduplicate(aligned_sequence_objects)
deduplicated_taxonomy = dedup.lca_taxonomy(deduplicated_arrays, taxonomy_definition)
deduplicated_taxonomy_hash = {}
for i, tax in enumerate(deduplicated_taxonomy):
deduplicated_taxonomy_hash[deduplicated_arrays[i][0].name] = tax
deduplicated_alignment_file = base+"_deduplicated_aligned.fasta"
seqio.write_fasta_file([seqs[0] for seqs in deduplicated_arrays],
deduplicated_alignment_file)
logging.info("Removed %i sequences as duplicates, leaving %i non-identical sequences"\
% ((len(aligned_sequence_objects)-len(deduplicated_arrays)),
len(deduplicated_arrays)))
# Get corresponding unaligned sequences
filtered_names=[]
for list in [x for x in [x[1:] for x in deduplicated_arrays] if x]:
for seq in list:
filtered_names.append(seq.name)
sequences2_fh = tempfile.NamedTemporaryFile(prefix='graftm', suffix='.faa')
tempfiles_to_close.append(sequences2_fh)
sequences2 = sequences2_fh.name
# Create tree unless one was provided
if not rerooted_tree and not rerooted_annotated_tree and not unrooted_tree:
logging.debug("No tree provided")
logging.info("Building tree")
log_file, tre_file = self._build_tree(deduplicated_alignment_file,
base, ptype,
self.fasttree)
no_reroot = False
else:
if rerooted_tree:
logging.debug("Found unannotated pre-rerooted tree file %s" % rerooted_tree)
tre_file=rerooted_tree
no_reroot = True
elif rerooted_annotated_tree:
logging.debug("Found annotated pre-rerooted tree file %s" % rerooted_tree)
tre_file=rerooted_annotated_tree
no_reroot = True
elif unrooted_tree:
logging.info("Using input unrooted tree")
tre_file = unrooted_tree
no_reroot = False
else:
raise
# Remove any sequences from the tree that are duplicates
cleaner = DendropyTreeCleaner()
tree = Tree.get(path=tre_file, schema='newick')
for group in deduplicated_arrays:
[removed_sequence_names.append(s.name) for s in group[1:]]
cleaner.remove_sequences(tree, removed_sequence_names)
# Ensure there is nothing amiss now as a user-interface thing
cleaner.match_alignment_and_tree_sequence_ids(\
[g[0].name for g in deduplicated_arrays], tree)
if tree_log:
# User specified a log file, go with that
logging.debug("Using user-specified log file %s" % tree_log)
log_file = tree_log
else:
logging.info("Generating log file")
log_file_tempfile = tempfile.NamedTemporaryFile(suffix='.tree_log', prefix='graftm')
tempfiles_to_close.append(log_file_tempfile)
log_file = log_file_tempfile.name
tre_file_tempfile = tempfile.NamedTemporaryFile(suffix='.tree', prefix='graftm')
tempfiles_to_close.append(tre_file_tempfile)
tre_file = tre_file_tempfile.name
with tempfile.NamedTemporaryFile(suffix='.tree', prefix='graftm') as f:
# Make the newick file simple (ie. un-arb it) for fasttree.
cleaner.write_fasttree_newick(tree, f)
f.flush()
self._generate_tree_log_file(f.name, deduplicated_alignment_file,
tre_file, log_file, ptype, self.fasttree)
# Create tax and seqinfo .csv files
taxonomy_to_keep=[
seq.name for seq in
[x for x in [x[0] for x in deduplicated_arrays]
if x]
]
refpkg = "%s.refpkg" % output_gpkg_path
self.the_trash.append(refpkg)
if taxtastic_taxonomy and taxtastic_seqinfo:
logging.info("Creating reference package")
refpkg = self._taxit_create(base, deduplicated_alignment_file,
tre_file, log_file, taxtastic_taxonomy,
taxtastic_seqinfo, refpkg, no_reroot)
else:
gtns = Getaxnseq()
seq = base+"_seqinfo.csv"
tax = base+"_taxonomy.csv"
self.the_trash += [seq, tax]
if rerooted_annotated_tree:
logging.info("Building seqinfo and taxonomy file from input annotated tree")
taxonomy_definition = TaxonomyExtractor().taxonomy_from_annotated_tree(
Tree.get(path=rerooted_annotated_tree, schema='newick'))
elif taxonomy:
logging.info("Building seqinfo and taxonomy file from input taxonomy")
taxonomy_definition = GreenGenesTaxonomy.read_file(taxonomy).taxonomy
else:
raise Exception("Programming error: Taxonomy is required somehow e.g. by --taxonomy or --rerooted_annotated_tree")
taxonomy_definition = {x:taxonomy_definition[x]
for x in taxonomy_definition
if x in taxonomy_to_keep}
gtns.write_taxonomy_and_seqinfo_files(taxonomy_definition,
tax,
seq)
# Create the reference package
logging.info("Creating reference package")
refpkg = self._taxit_create(base, deduplicated_alignment_file,
tre_file, log_file, tax, seq, refpkg,
no_reroot)
if sequences:
# Run diamond makedb
logging.info("Creating diamond database")
if ptype == Create._PROTEIN_PACKAGE_TYPE:
cmd = "diamond makedb --in '%s' -d '%s'" % (sequences, base)
extern.run(cmd)
diamondb = '%s.dmnd' % base
elif ptype == Create._NUCLEOTIDE_PACKAGE_TYPE:
diamondb = None
else: raise Exception("Programming error")
else:
diamondb = None
if sequences:
# Get range
max_range = self._define_range(sequences)
else:
max_range = self._define_range(alignment)
# Compile the gpkg
logging.info("Compiling gpkg")
GraftMPackageVersion3.compile(output_gpkg_path, refpkg, align_hmm, diamondb,
max_range, sequences, search_hmm_files=search_hmm_files)
logging.info("Cleaning up")
self._cleanup(self.the_trash)
for tf in tempfiles_to_close:
tf.close()
# Test out the gpkg just to be sure.
#
# TODO: Use graftM through internal means rather than via extern. This
# requires some refactoring so that graft() can be called easily with
# sane defaults.
logging.info("Testing gpkg package works")
self._test_package(output_gpkg_path)
logging.info("Finished\n")
def main(self, **kwargs):
alignment = kwargs.pop('alignment', None)
sequences = kwargs.pop('sequences', None)
taxonomy = kwargs.pop('taxonomy', None)
rerooted_tree = kwargs.pop('rerooted_tree', None)
unrooted_tree = kwargs.pop('unrooted_tree', None)
tree_log = kwargs.pop('tree_log', None)
prefix = kwargs.pop('prefix', None)
rerooted_annotated_tree = kwargs.pop('rerooted_annotated_tree', None)
user_hmm = kwargs.pop('hmm', None)
search_hmm_files = kwargs.pop('search_hmm_files', None)
min_aligned_percent = kwargs.pop('min_aligned_percent', 0.01)
taxtastic_taxonomy = kwargs.pop('taxtastic_taxonomy', None)
taxtastic_seqinfo = kwargs.pop('taxtastic_seqinfo', None)
force_overwrite = kwargs.pop('force', False)
graftm_package = kwargs.pop('graftm_package', False)
dereplication_level = kwargs.pop('dereplication_level', False)
threads = kwargs.pop('threads', 5)
if len(kwargs) > 0:
raise Exception("Unexpected arguments detected: %s" % kwargs)
seqio = SequenceIO()
locus_name = (os.path.basename(sequences).split('.')[0] if sequences
else os.path.basename(alignment).split('.')[0])
tmp = tempdir.TempDir()
base = os.path.join(tmp.name, locus_name)
insufficiently_aligned_sequences = [None]
removed_sequence_names = []
if prefix:
output_gpkg_path = prefix
else:
output_gpkg_path = "%s.gpkg" % locus_name
if os.path.exists(output_gpkg_path):
if force_overwrite:
logging.warn("Deleting previous directory %s" %
output_gpkg_path)
shutil.rmtree(output_gpkg_path)
else:
raise Exception(
"Cowardly refusing to overwrite gpkg to already existing %s"
% output_gpkg_path)
logging.info("Building gpkg for %s" % output_gpkg_path)
# Read in taxonomy somehow
gtns = Getaxnseq()
if rerooted_annotated_tree:
logging.info(
"Building seqinfo and taxonomy file from input annotated tree")
taxonomy_definition = TaxonomyExtractor().taxonomy_from_annotated_tree(\
Tree.get(path=rerooted_annotated_tree, schema='newick'))
elif taxonomy:
logging.info(
"Building seqinfo and taxonomy file from input taxonomy")
taxonomy_definition = GreenGenesTaxonomy.read_file(
taxonomy).taxonomy
elif taxtastic_seqinfo and taxtastic_taxonomy:
logging.info(
"Reading taxonomy from taxtastic taxonomy and seqinfo files")
taxonomy_definition = gtns.read_taxtastic_taxonomy_and_seqinfo\
(open(taxtastic_taxonomy),
open(taxtastic_seqinfo))
else:
raise Exception(
"Taxonomy is required somehow e.g. by --taxonomy or --rerooted_annotated_tree"
)
# Check for duplicates
logging.info("Checking for duplicate sequences")
dup = self._check_for_duplicate_sequence_names(sequences)
if dup:
raise Exception(
"Found duplicate sequence name '%s' in sequences input file" %
dup)
output_alignment = tempfile.NamedTemporaryFile(prefix='graftm',
suffix='.aln.faa').name
align_hmm = (user_hmm if user_hmm else tempfile.NamedTemporaryFile(
prefix='graftm', suffix='_align.hmm').name)
if alignment:
dup = self._check_for_duplicate_sequence_names(alignment)
if dup:
raise Exception(
"Found duplicate sequence name '%s' in alignment input file"
% dup)
ptype = self._get_hmm_from_alignment(alignment, align_hmm,
output_alignment)
else:
logging.info("Aligning sequences to create aligned FASTA file")
ptype, output_alignment = self._align_and_create_hmm(
sequences, alignment, user_hmm, align_hmm, output_alignment,
threads)
logging.info("Checking for incorrect or fragmented reads")
insufficiently_aligned_sequences = self._check_reads_hit(
open(output_alignment), min_aligned_percent)
while len(insufficiently_aligned_sequences) > 0:
logging.warn(
"One or more alignments do not span > %.2f %% of HMM" %
(min_aligned_percent * 100))
for s in insufficiently_aligned_sequences:
logging.warn(
"Insufficient alignment of %s, not including this sequence"
% s)
_, sequences2 = tempfile.mkstemp(prefix='graftm', suffix='.faa')
num_sequences = self._remove_sequences_from_alignment(
insufficiently_aligned_sequences, sequences, sequences2)
sequences = sequences2
if alignment:
_, alignment2 = tempfile.mkstemp(prefix='graftm',
suffix='.aln.faa')
num_sequences = self._remove_sequences_from_alignment(
insufficiently_aligned_sequences, alignment, alignment2)
alignment = alignment2
for name in insufficiently_aligned_sequences:
if rerooted_tree or rerooted_annotated_tree:
logging.warning(
'''Sequence %s in provided alignment does not meet the --min_aligned_percent cutoff. This sequence will be removed from the tree
in the final GraftM package. If you are sure these sequences are correct, turn off the --min_aligned_percent cutoff, provide it with a 0 (e.g. --min_aligned_percent 0) '''
% name)
removed_sequence_names.append(name)
logging.info(
"After removing %i insufficiently aligned sequences, left with %i sequences"
% (len(insufficiently_aligned_sequences), num_sequences))
if num_sequences < 4:
raise Exception(
"Too few sequences remaining in alignment after removing insufficiently aligned sequences: %i"
% num_sequences)
else:
logging.info(
"Reconstructing the alignment and HMM from remaining sequences"
)
output_alignment = tempfile.NamedTemporaryFile(
prefix='graftm', suffix='.aln.faa').name
if not user_hmm:
align_hmm = tempfile.NamedTemporaryFile(prefix='graftm',
suffix='.hmm').name
ptype, output_alignment = self._align_and_create_hmm(
sequences, alignment, user_hmm, align_hmm,
output_alignment, threads)
logging.info("Checking for incorrect or fragmented reads")
insufficiently_aligned_sequences = self._check_reads_hit(
open(output_alignment), min_aligned_percent)
if not search_hmm_files:
search_hmm = tempfile.NamedTemporaryFile(prefix='graftm',
suffix='_search.hmm').name
self._create_search_hmm(sequences, taxonomy_definition, search_hmm,
dereplication_level, threads)
search_hmm_files = [search_hmm]
# Make sure each sequence has been assigned a taxonomy:
aligned_sequence_objects = seqio.read_fasta_file(output_alignment)
unannotated = []
for s in aligned_sequence_objects:
if s.name not in taxonomy_definition:
unannotated.append(s.name)
if len(unannotated) > 0:
for s in unannotated:
logging.error(
"Unable to find sequence '%s' in the taxonomy definition" %
s)
raise Exception(
"All sequences must be assigned a taxonomy, cannot continue")
logging.debug(
"Looking for non-standard characters in aligned sequences")
self._mask_strange_sequence_letters(aligned_sequence_objects, ptype)
# Deduplicate sequences - pplacer cannot handle these
logging.info("Deduplicating sequences")
dedup = Deduplicator()
deduplicated_arrays = dedup.deduplicate(aligned_sequence_objects)
deduplicated_taxonomy = dedup.lca_taxonomy(deduplicated_arrays,
taxonomy_definition)
deduplicated_taxonomy_hash = {}
for i, tax in enumerate(deduplicated_taxonomy):
deduplicated_taxonomy_hash[deduplicated_arrays[i][0].name] = tax
deduplicated_alignment_file = base + "_deduplicated_aligned.fasta"
seqio.write_fasta_file([seqs[0] for seqs in deduplicated_arrays],
deduplicated_alignment_file)
logging.info("Removed %i sequences as duplicates, leaving %i non-identical sequences"\
% ((len(aligned_sequence_objects)-len(deduplicated_arrays)),
len(deduplicated_arrays)))
# Get corresponding unaligned sequences
filtered_names = []
for list in [x for x in [x[1:] for x in deduplicated_arrays] if x]:
for seq in list:
filtered_names.append(seq.name)
_, sequences2 = tempfile.mkstemp(prefix='graftm', suffix='.faa')
# Create tree unless one was provided
if not rerooted_tree and not rerooted_annotated_tree and not unrooted_tree:
logging.debug("No tree provided")
logging.info("Building tree")
log_file, tre_file = self._build_tree(deduplicated_alignment_file,
base, ptype, self.fasttree)
no_reroot = False
else:
if rerooted_tree:
logging.debug("Found unannotated pre-rerooted tree file %s" %
rerooted_tree)
tre_file = rerooted_tree
no_reroot = True
elif rerooted_annotated_tree:
logging.debug("Found annotated pre-rerooted tree file %s" %
rerooted_tree)
tre_file = rerooted_annotated_tree
no_reroot = True
elif unrooted_tree:
logging.info("Using input unrooted tree")
tre_file = unrooted_tree
no_reroot = False
else:
raise
# Remove any sequences from the tree that are duplicates
cleaner = DendropyTreeCleaner()
tree = Tree.get(path=tre_file, schema='newick')
for group in deduplicated_arrays:
[removed_sequence_names.append(s.name) for s in group[1:]]
cleaner.remove_sequences(tree, removed_sequence_names)
# Ensure there is nothing amiss now as a user-interface thing
cleaner.match_alignment_and_tree_sequence_ids(\
[g[0].name for g in deduplicated_arrays], tree)
if tree_log:
# User specified a log file, go with that
logging.debug("Using user-specified log file %s" % tree_log)
log_file = tree_log
else:
logging.info("Generating log file")
log_file_tempfile = tempfile.NamedTemporaryFile(
suffix='.tree_log', prefix='graftm')
log_file = log_file_tempfile.name
tre_file_tempfile = tempfile.NamedTemporaryFile(
suffix='.tree', prefix='graftm')
tre_file = tre_file_tempfile.name
with tempfile.NamedTemporaryFile(suffix='.tree',
prefix='graftm') as f:
# Make the newick file simple (ie. un-arb it) for fasttree.
cleaner.write_fasttree_newick(tree, f)
f.flush()
self._generate_tree_log_file(f.name,
deduplicated_alignment_file,
tre_file, log_file, ptype,
self.fasttree)
# Create tax and seqinfo .csv files
taxonomy_to_keep = [
seq.name
for seq in [x for x in [x[0] for x in deduplicated_arrays] if x]
]
refpkg = "%s.refpkg" % output_gpkg_path
self.the_trash.append(refpkg)
if taxtastic_taxonomy and taxtastic_seqinfo:
logging.info("Creating reference package")
refpkg = self._taxit_create(base, deduplicated_alignment_file,
tre_file, log_file, taxtastic_taxonomy,
taxtastic_seqinfo, refpkg, no_reroot)
else:
gtns = Getaxnseq()
seq = base + "_seqinfo.csv"
tax = base + "_taxonomy.csv"
self.the_trash += [seq, tax]
if rerooted_annotated_tree:
logging.info(
"Building seqinfo and taxonomy file from input annotated tree"
)
taxonomy_definition = TaxonomyExtractor(
).taxonomy_from_annotated_tree(
Tree.get(path=rerooted_annotated_tree, schema='newick'))
elif taxonomy:
logging.info(
"Building seqinfo and taxonomy file from input taxonomy")
taxonomy_definition = GreenGenesTaxonomy.read_file(
taxonomy).taxonomy
else:
raise Exception(
"Programming error: Taxonomy is required somehow e.g. by --taxonomy or --rerooted_annotated_tree"
)
taxonomy_definition = {
x: taxonomy_definition[x]
for x in taxonomy_definition if x in taxonomy_to_keep
}
gtns.write_taxonomy_and_seqinfo_files(taxonomy_definition, tax,
seq)
# Create the reference package
logging.info("Creating reference package")
refpkg = self._taxit_create(base, deduplicated_alignment_file,
tre_file, log_file, tax, seq, refpkg,
no_reroot)
if sequences:
# Run diamond makedb
logging.info("Creating diamond database")
if ptype == Create._PROTEIN_PACKAGE_TYPE:
cmd = "diamond makedb --in '%s' -d '%s'" % (sequences, base)
extern.run(cmd)
diamondb = '%s.dmnd' % base
elif ptype == Create._NUCLEOTIDE_PACKAGE_TYPE:
diamondb = None
else:
raise Exception("Programming error")
else:
diamondb = None
if sequences:
# Get range
max_range = self._define_range(sequences)
else:
max_range = self._define_range(alignment)
# Compile the gpkg
logging.info("Compiling gpkg")
GraftMPackageVersion3.compile(output_gpkg_path,
refpkg,
align_hmm,
diamondb,
max_range,
sequences,
search_hmm_files=search_hmm_files)
logging.info("Cleaning up")
self._cleanup(self.the_trash)
# Test out the gpkg just to be sure.
#
# TODO: Use graftM through internal means rather than via extern. This
# requires some refactoring so that graft() can be called easily with
# sane defaults.
logging.info("Testing gpkg package works")
self._test_package(output_gpkg_path)
logging.info("Finished\n")
def update(self, **kwargs):
'''
Update an existing GraftM package with new sequences and taxonomy. If no
taxonomy is provided, attempt to decorate the new sequences with
pre-existing taxonomy.
Parameters
----------
input_sequence_path: str
Path to FASTA file containing sequences to add to the update GraftM
package
input_taxonomy_path: str
Taxonomy corresponding to the sequences in input_sequence_path. If None,
then attempt to assign taxonomy by decorating the tree made out of all
sequences.
input_graftm_package_path: str
Path to the directory of the GraftM package that is to be updated
output_graftm_package_path: str
Path to the directory to which the new GraftM package will be
written to
'''
input_sequence_path = kwargs.pop('input_sequence_path')
input_taxonomy_path = kwargs.pop('input_taxonomy_path', None)
input_graftm_package_path = kwargs.pop('input_graftm_package_path')
output_graftm_package_path = kwargs.pop('output_graftm_package_path')
threads = kwargs.pop('threads', UpdateDefaultOptions.threads) #TODO: add to user options
if len(kwargs) > 0:
raise Exception("Unexpected arguments detected: %s" % kwargs)
logging.info("Reading previous GraftM package")
old_gpkg = GraftMPackage.acquire(input_graftm_package_path)
min_input_version = 3
if old_gpkg.version < min_input_version:
raise InsufficientGraftMPackageVersion(
"GraftM below version %s cannot be updated using the update function." % min_input_version +
" Unaligned sequences are not included in these packages, therefore no new"
" alignment/HMM/Tree can be created")
new_gpkg = UpdatedGraftMPackage()
new_gpkg.output = output_graftm_package_path
new_gpkg.name = output_graftm_package_path.replace(".gpkg", "")
#######################################
### Collect all unaligned sequences ###
logging.info("Concatenating unaligned sequence files")
new_gpkg.unaligned_sequences = "%s_sequences.fa" % (new_gpkg.name) #TODO: replace hard-coded paths like this with tempfiles
self._concatenate_file([old_gpkg.unaligned_sequence_database_path(),
input_sequence_path],
new_gpkg.unaligned_sequences)
#########################################################
### Parse taxonomy info up front so errors come early ###
if input_taxonomy_path:
logging.info("Reading new taxonomy information")
input_taxonomy = GreenGenesTaxonomy.read_file(input_taxonomy_path)
original_taxonomy_hash = old_gpkg.taxonomy_hash()
total_taxonomy_hash = original_taxonomy_hash.copy()
total_taxonomy_hash.update(input_taxonomy.taxonomy)
num_duplicate_taxonomies = len(total_taxonomy_hash) - \
len(input_taxonomy.taxonomy) - \
len(original_taxonomy_hash)
logging.debug("Found %i taxonomic definitions in common between the previous and updated taxonomies" % num_duplicate_taxonomies)
if num_duplicate_taxonomies > 0:
logging.warn("Found %i taxonomic definitions in common between the previous and updated taxonomies. Using the updated taxonomy in each case." % num_duplicate_taxonomies)
###############################
### Re-construct alignments ###
logging.info("Multiple sequence aligning all sequences")
new_gpkg.aligned_sequences = "%s_mafft_alignment.fa" % (new_gpkg.name)
self._align_sequences(new_gpkg.unaligned_sequences, new_gpkg.aligned_sequences, threads)
########################
### Re-construct HMM ###
logging.info("Creating HMM from alignment")
new_gpkg.hmm = "%s.hmm" % (new_gpkg.name)
new_gpkg.hmm_alignment = "%s_hmm_alignment.fa" % (new_gpkg.name)
self._get_hmm_from_alignment(new_gpkg.aligned_sequences, new_gpkg.hmm, new_gpkg.hmm_alignment)
#########################
### Re-construct tree ###
logging.info("Generating phylogenetic tree")
new_gpkg.unrooted_tree = "%s.tre" % (new_gpkg.name)
new_gpkg.unrooted_tree_log = "%s.tre.log" % (new_gpkg.name)
new_gpkg.package_type, new_gpkg.hmm_length = self._pipe_type(old_gpkg.alignment_hmm_path())
new_gpkg.unrooted_gpkg_tree_log, new_gpkg.unrooted_gpkg_tree = \
self._build_tree(new_gpkg.hmm_alignment, new_gpkg.name,
new_gpkg.package_type, self.fasttree)
##############################################
### Re-root and decorate tree if necessary ###
if input_taxonomy_path:
new_gpkg.gpkg_tree_log = new_gpkg.unrooted_tree_log
new_gpkg.gpkg_tree = new_gpkg.unrooted_gpkg_tree
else:
logging.info("Finding taxonomy for new sequences")
rerooter = Rerooter()
old_tree = Tree.get(path=old_gpkg.reference_package_tree_path(),
schema='newick')
new_tree = Tree.get(path=new_gpkg.unrooted_gpkg_tree,
schema='newick')
old_tree = rerooter.reroot(old_tree)
new_tree = rerooter.reroot(new_tree)
# TODO: Shouldn't call an underscore method, eventually use
# Rerooter instead.
rerooted_tree = rerooter.reroot_by_tree(old_tree, new_tree)
new_gpkg.gpkg_tree = "%s_gpkg.tree" % new_gpkg.name
td = TreeDecorator(
rerooted_tree,
old_gpkg.taxtastic_taxonomy_path(),
old_gpkg.taxtastic_seqinfo_path())
with tempfile.NamedTemporaryFile(suffix='tsv') as taxonomy:
td.decorate(new_gpkg.gpkg_tree, taxonomy.name, True)
total_taxonomy_hash = GreenGenesTaxonomy.read_file(taxonomy.name).taxonomy
################################
### Generating tree log file ###
logging.info("Generating phylogenetic tree log file")
new_gpkg.gpkg_tree = "%s_gpkg.tree" % new_gpkg.name
new_gpkg.gpkg_tree_log = "%s_gpkg.tree.log" % new_gpkg.name
self._generate_tree_log_file(new_gpkg.unrooted_tree,
new_gpkg.hmm_alignment,
new_gpkg.gpkg_tree,
new_gpkg.gpkg_tree_log,
new_gpkg.package_type,
self.fasttree)
################################
### Creating taxtastic files ###
logging.info("Writing new taxonomy files")
new_gpkg.tt_seqinfo = "%s_seqinfo.csv" % new_gpkg.name
new_gpkg.tt_taxonomy = "%s_taxonomy.csv" % new_gpkg.name
gtns = Getaxnseq()
gtns.write_taxonomy_and_seqinfo_files(
total_taxonomy_hash,
new_gpkg.tt_taxonomy,
new_gpkg.tt_seqinfo)
######################
### Compile refpkg ###
logging.info("Compiling pplacer refpkg")
new_gpkg.refpkg = "%s.refpkg" % (new_gpkg.name)
refpkg = self._taxit_create(new_gpkg.name,
new_gpkg.hmm_alignment,
new_gpkg.gpkg_tree,
new_gpkg.gpkg_tree_log,
new_gpkg.tt_taxonomy,
new_gpkg.tt_seqinfo,
new_gpkg.refpkg,
True)
#####################################
### Re-construct diamond database ###
logging.info("Recreating DIAMOND DB")
new_gpkg.diamond_database = "%s.dmnd" % (new_gpkg.name)
self._create_dmnd_database(new_gpkg.unaligned_sequences, new_gpkg.name)
####################
### Compile gpkg ###
logging.info("Compiling GraftM package")
new_gpkg.name = "%s.gpkg" % new_gpkg.name
GraftMPackageVersion3.compile(new_gpkg.name, new_gpkg.refpkg,
new_gpkg.hmm, new_gpkg.diamond_database,
self._define_range(new_gpkg.unaligned_sequences),
new_gpkg.unaligned_sequences,
search_hmm_files=old_gpkg.search_hmm_paths())
###################
### Test it out ###
logging.info("Testing newly updated GraftM package works")
self._test_package(new_gpkg.name)
logging.info("Finished")
"cog_ids":cog_ids,
"cog_classifications":cog_classifications,
"tigrfam_ids":tigrfam_ids,
"tigrfam_classifications":tigrfam_classifications,
"source":"IMG",
"swiss_prot": swiss_prot}
arb_db[seq_name].update(tmp)
arb_db[seq_id]["Classification"] = '_'.join(parsed_gff_file[seq_name].split())
parsed_gtdb_pfam_annotation = parse_pfam_annotation_hmmoutput(os.path.join(pfam_annotations, KO_ID+'_gtdb_pfam_annotation.domtblout.txt.gz'))
parsed_unaligned_sequences = SeqIO.to_dict(SeqIO.parse(open(unaligned_sequences), "fasta"))
parsed_aligned_sequences=SeqIO.to_dict(SeqIO.parse(open(aligned_sequences), "fasta"))
gtns = Getaxnseq()
parsed_taxonomy = {}
ids =[]
for id, tax in gtns.\
read_taxtastic_taxonomy_and_seqinfo(open(taxonomy_path),
open(seqinfo_path)).iteritems():
ids.append(id)
if '~' in id:
gene_name, genome_id = id, id.split('~')[1]
if genome_id in gene_id_to_tax:
raise Exception("Genome ID encountered twice: %s" % genome_id)
else:
gene_id_to_tax[id] = genome_id
def _assign_taxonomy_with_diamond(self, base_list, db_search_results,
graftm_package, graftm_files,
diamond_performance_parameters):
'''Run diamond to assign taxonomy
Parameters
----------
base_list: list of str
list of sequence block names
db_search_results: list of DBSearchResult
the result of running hmmsearches
graftm_package: GraftMPackage object
Diamond is run against this database
graftm_files: GraftMFiles object
Result files are written here
diamond_performance_parameters : str
extra args for DIAMOND
Returns
-------
list of
1. time taken for assignment
2. assignments i.e. dict of base_list entry to dict of read names to
to taxonomies, or None if there was no hit detected.
'''
runner = Diamond(graftm_package.diamond_database_path(),
self.args.threads, self.args.evalue)
taxonomy_definition = Getaxnseq().read_taxtastic_taxonomy_and_seqinfo\
(open(graftm_package.taxtastic_taxonomy_path()),
open(graftm_package.taxtastic_seqinfo_path()))
results = {}
# For each of the search results,
for i, search_result in enumerate(db_search_results):
if search_result.hit_fasta() is None:
sequence_id_to_taxonomy = {}
else:
sequence_id_to_hit = {}
# Run diamond
logging.debug("Running diamond on %s" %
search_result.hit_fasta())
diamond_result = runner.run(
search_result.hit_fasta(),
UnpackRawReads.PROTEIN_SEQUENCE_TYPE,
daa_file_basename=graftm_files.
diamond_assignment_output_basename(base_list[i]),
extra_args=diamond_performance_parameters)
for res in diamond_result.each([
SequenceSearchResult.QUERY_ID_FIELD,
SequenceSearchResult.HIT_ID_FIELD
]):
if res[0] in sequence_id_to_hit:
# do not accept duplicates
if sequence_id_to_hit[res[0]] != res[1]:
raise Exception(
"Diamond unexpectedly gave two hits for a single query sequence for %s"
% res[0])
else:
sequence_id_to_hit[res[0]] = res[1]
# Extract taxonomy of the best hit, and add in the no hits
sequence_id_to_taxonomy = {}
for seqio in SequenceIO().read_fasta_file(
search_result.hit_fasta()):
name = seqio.name
if name in sequence_id_to_hit:
# Add Root; to be in line with pplacer assignment method
sequence_id_to_taxonomy[name] = [
'Root'
] + taxonomy_definition[sequence_id_to_hit[name]]
else:
# picked up in the initial search (by hmmsearch, say), but diamond misses it
sequence_id_to_taxonomy[name] = ['Root']
results[base_list[i]] = sequence_id_to_taxonomy
return results
