def __init__(self, top_level_directory, reference_fname, assembler_name, protein_identity, alignment_length, min_gene_coverage, do_not_trim=False, testmode='none') :
self.alignments_dir = join(top_level_directory, 'alignments')
self.output_dir = join(top_level_directory, 'postprocessing')
self.protein_identity = protein_identity
self.alignment_length = alignment_length
self.min_gene_coverage = min_gene_coverage
self.trim = not do_not_trim
self.testmode = testmode
self.scaffold_dir = join(self.output_dir, 'scaffolds')
self.genefamily_msa_dir = join(self.output_dir, 'genefamily_msa')
self.gene_msa_dir = join(self.output_dir, 'gene_msa')
check_dir(self.output_dir, create=True)
check_dir(self.scaffold_dir, create=True)
check_dir(self.genefamily_msa_dir, create=True)
check_dir(self.gene_msa_dir, create=True)
self.log = get_log()
self.param = GluttonParameters(top_level_directory)
self.db = GluttonDB(reference_fname)
self.info = GluttonInformation(self.alignments_dir, self.param, self.db)
# check reference was the same
if not self.param.same_reference(self.db) :
self.log.error("current reference is %s, alignments were performed using %s" % (reference_fname, self.db.filename))
exit(1);
# perhaps slightly overambitious to exit, just stick to a warning
pending,failures = self.info.num_alignments_not_done()
if pending != 0 :
self.log.warn("%d alignments were not run!" % pending)
self.assembler = AssemblerOutput(assembler_name)
# e.g. query39806_orf1
self.orfname_regex = re.compile("^(query\d+)\_orf(\d)$")
class Scaffolder(object) :
def __init__(self, top_level_directory, reference_fname, assembler_name, protein_identity, alignment_length, min_gene_coverage, do_not_trim=False, testmode='none') :
self.alignments_dir = join(top_level_directory, 'alignments')
self.output_dir = join(top_level_directory, 'postprocessing')
self.protein_identity = protein_identity
self.alignment_length = alignment_length
self.min_gene_coverage = min_gene_coverage
self.trim = not do_not_trim
self.testmode = testmode
self.scaffold_dir = join(self.output_dir, 'scaffolds')
self.genefamily_msa_dir = join(self.output_dir, 'genefamily_msa')
self.gene_msa_dir = join(self.output_dir, 'gene_msa')
check_dir(self.output_dir, create=True)
check_dir(self.scaffold_dir, create=True)
check_dir(self.genefamily_msa_dir, create=True)
check_dir(self.gene_msa_dir, create=True)
self.log = get_log()
self.param = GluttonParameters(top_level_directory)
self.db = GluttonDB(reference_fname)
self.info = GluttonInformation(self.alignments_dir, self.param, self.db)
# check reference was the same
if not self.param.same_reference(self.db) :
self.log.error("current reference is %s, alignments were performed using %s" % (reference_fname, self.db.filename))
exit(1);
# perhaps slightly overambitious to exit, just stick to a warning
pending,failures = self.info.num_alignments_not_done()
if pending != 0 :
self.log.warn("%d alignments were not run!" % pending)
self.assembler = AssemblerOutput(assembler_name)
# e.g. query39806_orf1
self.orfname_regex = re.compile("^(query\d+)\_orf(\d)$")
def stop(self) :
pass
def _orf_to_query_name(self, name) :
m = self.orfname_regex.match(name)
if not m :
raise ScaffolderError("unexpected query name (%s)" % name)
return m.group(1)
def _assembler_gene_name(self, name) :
m = self.assembler.match(name)
if not m :
raise ScaffolderError("unexpected gene name (%s)" % name)
if m.group(1) :
return m.group(1)
else :
return m.group(2)
# read the alignment file and return a dictionary keyed on the gene name
# - there might be multiple orfs for a single query sequence, so keep a track of the best one
#@profile
def read_alignment(self, fname) :
tmp = defaultdict(dict)
genes = []
for s in SeqIO.parse(fname, 'fasta') :
if not s.description.startswith('query') :
gene_id = s.description
gene_name = self.db.get_genename_from_geneid(gene_id)
gene_seq = str(s.seq)
gene_prot = translate(gene_seq)
gene_start,gene_end = sequence_limits(gene_prot)
genes.append((gene_name, gene_seq))
continue
query_id = self._orf_to_query_name(s.description)
contig_id,label = self.info.get_contig_from_query(query_id)
species = self.param.get_species(label)
assembler_geneid = self._assembler_gene_name(contig_id)
seq = str(s.seq).replace('N', '-')
contig_start,contig_end = sequence_limits(seq)
# pagan bug?
if (contig_end - contig_start) == 0 :
continue
overlap_start = max(contig_start / 3, gene_start)
overlap_end = min(contig_end / 3, gene_end)
# require all alignments to firmly overlap gene
if ((overlap_end - overlap_start) * 3) < 100 :
continue
ref_identity = self.protein_similarity(gene_prot,
translate(seq),
overlap_start,
overlap_end)
# user defined identity in protein space
if ref_identity < self.protein_identity :
continue
# if we have seen this before
if (contig_id in tmp[gene_name]) and (ref_identity < tmp[gene_name][contig_id][-1]) :
continue
# first three need to be seq, contig_start, contig_end
tmp[gene_name][contig_id] = (seq, contig_start, contig_end, label, species, assembler_geneid, s.description, ref_identity)
# convert from a dict of dicts to a dict of lists
tmp2 = defaultdict(list)
self.log.debug("read %s" % fname)
for gene in tmp :
self.log.debug("\tgene = %s" % gene)
for contig in tmp[gene] :
seq,start,end,label,species,assembler_geneid,queryid,ref_identity = tmp[gene][contig]
self.log.debug("\t\tquery id = %s (%d,%d)" % (queryid,start,end))
try :
tmp2[gene].append(Alignment(contig, assembler_geneid, gene, start, end, seq, label, species))
except ScaffolderError :
self.log.debug("empty sequence %s in %s" % (queryid, fname))
continue
return tmp2, genes
def group_alignments(self, alignments) :
groups = []
# for each alignment
for align in alignments :
# for each group
add_to_group = False
for group in groups :
# if 'align' overlaps with a member of that group
# are they were from the same input file (i.e. label)
for member in group :
if member.overlaps(align) and member.from_same_file(align) :
add_to_group = True
break
# add to the group
if add_to_group :
group.append(align)
break
if not add_to_group :
groups.append([ align ])
return groups
def group_alignments_by_file(self, alignments) :
groups = defaultdict(list)
for a in alignments :
groups[a.label].append(a)
return groups
def group_cannot_be_merged_isoforms(self, group) :
return self.group_cannot_be_merged(group, consider_isoforms=True)
def group_cannot_be_merged(self, group, consider_isoforms=False) :
for i in range(0, len(group)) :
a = group[i]
for j in range(i+1, len(group)) :
b = group[j]
if a.overlaps(b) :
if consider_isoforms :
if a.isoforms(b) :
return True
else :
if not a.mergeable(b) :
return True
return False
def merge_alignments(self, alignments) :
global DEBUG
#if self.testmode != 'none' :
# return alignments
# perform merges of overlaps first
unmerged_labels = set()
merged_groups = []
def label_all(group, label) :
for i in group :
i.desc = label
for group in self.group_alignments(alignments) :
no_print = False
# if the assembler thinks these two contigs are isoforms of the
# same gene then we should not attempt to merge them
if self.group_cannot_be_merged_isoforms(group) :
unmerged_labels.add(group[0].label)
if len(set([ g.gene_id for g in group ])) == 1 :
label_all(group, 'single_gene_multiple_isoform')
else :
label_all(group, 'multiple_gene_multiple_isoform')
merged_groups += group
no_print = True
# some contigs mapping to the same region of the gene cannot be
# merged because the differences between them is too large
# (defined in Alignment class)
elif self.group_cannot_be_merged(group) :
unmerged_labels.add(group[0].label)
label_all(group, 'conflict')
merged_groups += group
# these can be merged trivially
else :
merged_groups.append( reduce(operator.add, sorted(group, key=lambda x : x.start)) )
#if DEBUG and (not no_print) and (len(group) > 1) :
# self.print_alignments(group)
# if there were any conflicts for a given gene in an alignment, then
# just output what has been merged, if there were no conflicts for
# a gene then concatenate the islands of alignments with N's
tmp = []
grouped_by_file = self.group_alignments_by_file(merged_groups)
for label in grouped_by_file :
if label in unmerged_labels :
tmp += grouped_by_file[label]
else :
tmp.append( reduce(operator.add, sorted(grouped_by_file[label], key=lambda x : x.start)) )
return tmp
def print_alignments(self, alignments) :
f = open('glutton_debug_scaffolds.txt', 'a')
for a in alignments :
print >> f, "%s\t%s" % (a.id, a.seq)
alignment_diff = ""
for column in range(len(alignments[0].seq)) :
chars = set([ a[column] for a in alignments if a[column] ])
if ('-' in chars) and (len(chars) > 1) :
alignment_diff += 'X'
elif len(chars) < 2 :
alignment_diff += ' '
else :
alignment_diff += 'M'
print >> f, "difference \t%s" % alignment_diff
print >> f, ""
f.close()
# XXX now in Alignment class
def trim_at_ATG(self, seq, pos) :
trim_pos = pos
for ind in range(0, pos+3, 3)[::-1] :
codon = seq[ind : ind+3]
if codon == start_codon :
trim_pos = ind
break
#if codon in stop_codons :
# break
return ('-' * trim_pos) + seq[trim_pos:]
def consensus_for_msa(self, reference, alignments, bamfiles) :
if len(alignments) == 1 :
a = alignments[0]
a.trim_at_ATG(reference.start)
if self.trim :
a.truncate_at_stop_codon()
return Alignment2(a.species, a.gene_name, a.seq, [a.contig_id])
if self.testmode == 'none' :
return self.consensus_for_msa_glutton(reference, alignments, bamfiles)
else :
lengths = [ len(a.seq.replace('-','')) for a in alignments ]
identities = []
coverages = []
gene_prot = translate(reference.seq)
for a in alignments :
# identity
overlap_start = max(a.start, reference.start)
overlap_end = min(a.end , reference.end )
ident = self.protein_similarity(gene_prot, translate(a.seq), overlap_start/3, overlap_end/3)
identities.append(ident)
# coverage (depth)
if a.label in bamfiles :
try :
id = str(a.id).split()[0]
coverages.append(bamfiles[a.label].count(id))
except :
coverages.append(1)
coverages = [ c / float(l) for c,l in zip(coverages, lengths) ]
if self.testmode == 'length' :
top_hit = sorted(zip(lengths, identities, coverages, range(len(lengths))))[-1][-1]
elif self.testmode == 'identity' :
top_hit = sorted(zip(identities, lengths, coverages, range(len(lengths))))[-1][-1]
else :
top_hit = sorted(zip(coverages, identities, lengths, range(len(lengths))))[-1][-1]
a = alignments[top_hit]
a.trim_at_ATG(reference.start)
if self.trim :
a.truncate_at_stop_codon()
#seq = self.trim_at_ATG(a.seq, reference.start)
return Alignment2(a.species, a.gene_name, a.seq, [a.contig_id])
#@profile
def consensus_for_msa_glutton(self, reference, alignments, bamfiles) :
if len(alignments) == 1 :
a = alignments[0]
a.trim_at_ATG(reference.start)
if self.trim :
a.truncate_at_stop_codon()
return Alignment2(a.species, a.gene_name, a.seq, [a.contig_id])
# this is buggy if within a species there are FAKE and real bam files
coverage = []
for a in alignments :
numerator = 1
denominator = len(a.seq.replace('-', ''))
if a.label in bamfiles :
try :
# BWA only uses the fasta id, but we need to store the complete
# description line as an id because soapdenovotrans does not provide
# the locus information in the first token, but the second
#id = str(a.id).split()[0] # moved to a property in Alignment
numerator = bamfiles[a.label].count(a.contig_id)
except ValueError :
pass
coverage.append(numerator / float(denominator))
s = "-" * len(alignments[0].seq)
for cov,a in sorted(zip(coverage, alignments)) :
#tmp = ""
#for c1,c2 in zip(a.seq[a.start:a.end], s[a.start:a.end]) :
# tmp += (c1 if c1 not in ('-','N') else c2)
a.trim_at_ATG(reference.start)
if self.trim :
a.truncate_at_stop_codon()
subseq = a.seq[a.start:a.end]
if 'N' not in subseq :
s = s[:a.start] + subseq + s[a.end:]
else :
tmp = ""
for ind,c in enumerate(subseq) :
tmp += (c if c != 'N' else s[a.start + ind])
s = s[:a.start] + tmp + s[a.end:]
#s = self.trim_at_ATG(s, reference.start)
return Alignment2(alignments[0].species, alignments[0].gene_name, s, [ a.contig_id for a in alignments ])
def remove_common_gaps(self, alignment) :
indices = [-1, len(alignment[0].seq)]
num_rows = len(alignment)
for index,chars in enumerate(zip(*[ a.seq for a in alignment ])) :
if (chars.count('-') + chars.count('N')) == num_rows :
#if chars.count('-') == num_rows :
indices.append(index)
indices.sort()
for a in alignment :
a.remove_chars(indices)
return alignment
def nucleotide_overlap(self, ref, query, start, end) :
if end <= start :
return 0
r = ref[start:end]
q = query[start:end]
covered = 0
for cq,cr in zip(q,r) :
if (cq,cr) == ('-','-') :
continue
if cq == 'N' :
continue
covered += 1
return covered
def gene_coverage(self, ref, query) :
total = 0
covered = 0
for i in range(ref.start, ref.end) :
cq = query.seq[i]
cr = ref.seq[i]
if (cq,cr) == ('-','-') :
continue
if (query.start <= i < query.end) and (cq != 'N') :
covered += 1
total += 1
return covered / float(total)
def protein_similarity(self, ref, query, start, end) :
if end <= start :
return 0.0
r = ref[start:end]
q = query[start:end]
identical = 0
length = 0
for cq,cr in zip(q,r) :
if (cq,cr) == ('-','-') :
continue
if cq == 'X' :
continue
if cq == cr :
identical += 1
length += 1
return identical / float(length)
def process_alignments(self, output_files, bam_files) :
global DEBUG
counter = -1
aligned_contigs = defaultdict(set)
alignment_files = glob(join(self.alignments_dir, 'glutton*.nucleotide'))
complete_files = 0
total_files = len(alignment_files)
stderr.write("\rINFO processed %d / %d alignments " % (complete_files, total_files))
stderr.flush()
for fname in alignment_files :
contigs, genes = self.read_alignment(fname)
merged_contigs = defaultdict(dict)
# for each gene, merge the contigs from the same input file
# and write to output
for gene_name in contigs :
for a in contigs[gene_name] :
aligned_contigs[a.label].add(a.id)
if a.species not in merged_contigs[gene_name] :
merged_contigs[gene_name][a.species] = []
merged_contigs[gene_name][a.species].append(a)
for a in self.merge_alignments(contigs[gene_name]) :
print >> output_files[a.label], a.format_contig()
# merge sequences from the same species
# find stop codon and truncate sequences
# delete columns with only gaps
# then write out to a file in self.output_dir
# in MSA have >species_name contents=gluttonX,gluttonY,gluttonZ
new_alignment = []
non_reference_seq = 0
for gene_name,gene_seq in genes :
ref = Alignment2(self.db.species, gene_name, gene_seq, [gene_name])
new_alignment.append(ref)
#gene_prot = translate(ref.seq)
ref.prot_id = 1.0
ref.coverage = 1.0
for species in merged_contigs[gene_name] :
try :
tmp = self.consensus_for_msa(ref, merged_contigs[gene_name][species], bam_files)
#tmp.truncate_at_stop_codon() # this only needs to be here for the testmodes, otherwise it is redundant
except ScaffolderError, se :
continue
# check length vs alignment_length
#if len(tmp) < self.alignment_length :
# continue
overlap_start = max(tmp.start, ref.start)
overlap_end = min(tmp.end , ref.end )
overlap_bases = self.nucleotide_overlap(ref.seq, tmp.seq, overlap_start, overlap_end)
if overlap_bases < self.alignment_length :
continue
coverage = self.gene_coverage(ref, tmp)
if coverage < self.min_gene_coverage :
continue
prot_identity = self.protein_similarity(translate(ref.seq),
translate(tmp.seq),
overlap_start / 3,
overlap_end / 3)
if prot_identity < self.protein_identity :
continue
tmp.prot_id = prot_identity
tmp.coverage = coverage
new_alignment.append(tmp)
non_reference_seq += 1
if non_reference_seq != 0 :
counter += 1
self.write_alignment(join(self.genefamily_msa_dir, "msa%d.fasta" % counter), new_alignment)
subalignments = defaultdict(list)
for a in new_alignment :
subalignments[a.gene_name].append(a)
for k,v in subalignments.iteritems() :
if len(v) > 1 :
self.write_alignment(join(self.gene_msa_dir, "%s.fasta" % k), v)
complete_files += 1
stderr.write("\rINFO processed %d / %d alignments " % (complete_files, total_files))
stderr.flush()
stderr.write("\rINFO processed %d / %d alignments \n" % (complete_files, total_files))
stderr.flush()
self.log.info("created %d multiple sequence alignments" % (counter + 1))
return aligned_contigs