def annotate(gene_list, db_info):
#
[local_db, all_species, ensembl_db_name, species] = db_info
db = connect_to_mysql()
cfg = ConfigurationReader()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
if verbose: print "thread %s annotating %s " % (get_thread_name(), species)
if not species == 'oryctolagus_cuniculus':
print 'The preferred list of species is hardcoded for the rabbit. Consider modifying.'
exit(1)
preferred_species = [
species, 'mus_musculus', 'rattus_norvegicus', 'homo_sapiens'
]
nearest_species_list = species_sort(cursor, all_species, species)
species_list = preferred_species + filter(
lambda x: x not in preferred_species, nearest_species_list)
inf = erropen("temp_out.fasta", "w")
for gene_id in gene_list:
#for gene_id in [90020]:
switch_to_db(cursor, ensembl_db_name[species])
####################
# get stable id and description of this gene
stable_id = gene2stable(cursor, gene_id)
if not gene_list.index(gene_id) % 100:
print gene_list.index(gene_id), "out of", len(gene_list)
if verbose: print "============================================="
if verbose: print gene_id, stable_id
####################
# find the annotation from the preferred source organism
[annot_source, orthology_type, annotation,
ortho_stable_ids] = find_annotation(cursor, ensembl_db_name,
species_list, gene_id)
if verbose: print annot_source, "**", orthology_type, '**', annotation
###################
# find splices (for now find the canonical splice)
switch_to_db(cursor, ensembl_db_name[species])
canonical_splice = get_canonical_transl(acg, cursor, gene_id, species)
# output
if orthology_type == 'self' or annotation == 'none':
header = ">{0} {1}".format(stable_id, annotation)
else:
header = ">{0} {1} [by sim to {2}, {3}]".format(
stable_id, annotation, annot_source, ortho_stable_ids)
print >> inf, header
print >> inf, canonical_splice
cursor.close()
db.close()
def main():
db = connect_to_mysql()
acg = AlignmentCommandGenerator()
cfg = ConfigurationReader()
cursor = db.cursor()
[all_species, ensembl_db_name] = get_species (cursor)
# human and mouse are the only two species that have CCDs info
for species in [ 'homo_sapiens', 'mus_musculus']:
alt_splice_almt (cursor, cfg, acg, species, ensembl_db_name)
cursor.close()
db .close()
def make_alignments (species_list, db_info):
[local_db, ensembl_db_name] = db_info
verbose = False
flank_length = 10
db = connect_to_mysql()
cfg = ConfigurationReader()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
# find db ids adn common names for each species db
[all_species, ensembl_db_name] = get_species (cursor)
max_days = 60
for species in species_list:
species_shorthand = get_species_shorthand(cursor, species)
print(species, species_shorthand)
directory = check_directory (cfg, species, species_shorthand, "pep")
if not directory: continue
removed = 0
remaining = 0
for dirname, dirnames, filenames in os.walk(directory):
for filename in filenames:
full_name = os.path.join(dirname, filename)
time_modified = os.path.getmtime(full_name)
number_of_days_since_modified = (time.time() - time_modified)/(60*60*24)
if number_of_days_since_modified > max_days:
#print "removing", filename, "made", number_of_days_since_modified, "ago"
os.remove(full_name)
else:
remaining += 1
print(species, "done, removed", removed, "files, remaining", remaining)
def main():
db = connect_to_mysql()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
[all_species, ensembl_db_name] = get_species(cursor)
species = 'homo_sapiens'
switch_to_db(cursor, ensembl_db_name[species])
gene_list = get_gene_ids(cursor, biotype='protein_coding')
for gene_id in gene_list:
# find stable
stable_id = gene2stable(cursor, gene_id=gene_id)
canonical = get_canonical_transl(acg,
cursor,
gene_id,
species,
strip_X=False)
if canonical:
print stable_id, canonical
cursor.close()
db.close()
def find_missing_exons(human_gene_list, db_info):
#
[local_db, ensembl_db_name, method] = db_info
db = connect_to_mysql()
cfg = ConfigurationReader()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
# find db ids and common names for each species db
all_species, ensembl_db_name = get_species(cursor)
# minimal acceptable similarity between exons
min_similarity = cfg.get_value('min_accptbl_exon_sim')
switch_to_db(cursor, ensembl_db_name['homo_sapiens'])
##################################################################################
# loop over human genes
gene_ct = 0
found = 0
sought = 0
unsequenced = 0
#human_gene_list.reverse()
for human_gene_id in human_gene_list:
switch_to_db(cursor, ensembl_db_name['homo_sapiens'])
# Get stable id and description of this gene -- DEBUG
human_stable = gene2stable(cursor, human_gene_id)
human_description = get_description(cursor, human_gene_id)
if verbose: print(human_gene_id, human_stable, human_description)
# progress counter
gene_ct += 1
if (not gene_ct % 10):
print("processed ", gene_ct, " out of ", len(human_gene_list),
"genes")
print("exons found: ", found, " out of ", sought, "sought")
# find all human exons for this gene that we are tracking in the database
human_exons = [
e for e in gene2exon_list(cursor, human_gene_id)
if e.covering_exon < 0 and e.is_canonical and e.is_known
]
if not human_exons:
print("\t\t no exons found")
continue
human_exons.sort(key=lambda exon: exon.start_in_gene)
for he in human_exons:
he.stable_id = exon2stable(cursor, he.exon_id)
##################################################################################
##################################################################################
# make 'table' of maps, which is either pointer to the map if it exists, or None
map_table = {}
for species in all_species:
map_table[species] = {}
for he in human_exons:
map_table[species][he] = None
#################
maps_for_exon = {}
for he in human_exons:
maps_for_exon[he] = get_maps(cursor, ensembl_db_name, he.exon_id,
he.is_known) # exon data
for m in maps_for_exon[he]:
#if m.source == 'usearch': continue
#if m.source == 'sw_sharp': continue
#if m.source == 'sw_sharp':
# print 'sw_sharp'
#if m.source == 'usearch':
# print 'usearch', m.similarity, m.species_2, m.exon_id_1, m.exon_id_2
if m.similarity < min_similarity: continue
m_previous = map_table[m.species_2][he]
if m_previous and m_previous.similarity > m.similarity:
continue
map_table[m.species_2][he] = m
# get rid of species that do not have the gene at all
for species in all_species:
one_exon_found = False
for he in human_exons:
if map_table[species][he]:
one_exon_found = True
break
if not one_exon_found:
del map_table[species]
# fill in the peptide sequence field for each human exon
# get rid of exons that appear in no other species but human (?)
bad_he = []
for he in human_exons:
one_species_found = False
he.pepseq = get_exon_pepseq(cursor, he,
ensembl_db_name['homo_sapiens'])
if len(
he.pepseq
) < 3: # can I ever get rid of all the nonsense I find in Ensembl?
bad_he.append(he)
continue
for species in list(map_table.keys()):
if species == 'homo_sapiens': continue
if map_table[species][he]:
one_species_found = True
break
if not one_species_found:
bad_he.append(he)
human_exons = [he for he in human_exons if not he in bad_he]
# keep track of nearest neighbors for each human exon
previous = {}
next = {}
prev = None
for he in human_exons:
previous[he] = prev
if prev: next[prev] = he
prev = he
next[he] = None
# fill, starting from the species that are nearest to the human
if not list(map_table.keys()):
continue # whatever
species_sorted_from_human = species_sort(cursor,
list(map_table.keys()),
species)[1:]
for species in species_sorted_from_human:
print(species)
# see which exons have which neighbors
#if verbose: print he.exon_id, species
no_left = []
no_right = []
has_both_neighbors = []
one_existing_map = None
for he in human_exons:
m = map_table[species][he]
if m and not m.warning: # the one existing map should not be a problematic one
one_existing_map = m
continue
prev = previous[he]
nxt = next[he]
if prev and nxt and map_table[species][prev] and map_table[
species][nxt]:
has_both_neighbors.append(he)
elif not prev or not map_table[species][prev]:
no_left.append(he)
elif not nxt or not map_table[species][nxt]:
no_right.append(he)
if not one_existing_map: continue # this shouldn't happen
if not has_both_neighbors and not no_left and not no_right:
continue
# what is the gene that we are talking about?
exon_id = one_existing_map.exon_id_2
is_known = one_existing_map.exon_known_2
gene_id = exon_id2gene_id(cursor, ensembl_db_name[species],
exon_id, is_known)
# is it mitochondrial?
mitochondrial = is_mitochondrial(cursor, gene_id,
ensembl_db_name[species])
# where is the gene origin (position on the sequence)
gene_coords = get_gene_coordinates(cursor, gene_id,
ensembl_db_name[species])
if not gene_coords: continue
[gene_seq_region_id, gene_start, gene_end,
gene_strand] = gene_coords
# fill in exons that have both neighbors:
# human exon functions as a coordinate here
for he in has_both_neighbors:
# get template (known exon from the nearest species)
template_info = get_template(cursor, ensembl_db_name,
map_table, species, he)
if not template_info: continue
# previous_ and next_seq_region are of the type Seq_Region defined on the top of the file
# get previous region
prev_seq_region = get_neighboring_region(
cursor, ensembl_db_name, map_table, species, gene_coords,
he, previous[he])
if not prev_seq_region: continue
# get following region
next_seq_region = get_neighboring_region(
cursor, ensembl_db_name, map_table, species, gene_coords,
he, next[he])
if not next_seq_region: continue
sought += 1
reply = find_NNN(cursor, ensembl_db_name, cfg, acg, he,
maps_for_exon[he], species, gene_id,
gene_coords, prev_seq_region, next_seq_region,
template_info, mitochondrial, method)
if reply == 'NNN':
unsequenced += 1
# work backwards
# use the last known region on the left as the bound
no_left.reverse()
next_seq_region = None
for he in no_left:
m = map_table[species][he]
# check first if we haave already looked into this, and found incomplete region
#if m and m.warning: continue
# get template (known exon from the nearest species)
template_info = get_template(cursor, ensembl_db_name,
map_table, species, he)
if not template_info: continue
# get following region
if not next_seq_region:
next_seq_region = get_neighboring_region(
cursor, ensembl_db_name, map_table, species,
gene_coords, he, next[he])
if not next_seq_region: continue
# otherwise it is the last thing we found
# the previous region is eyeballed from the next on
# the previous and the next region frame the search region
prev_seq_region = left_region(next_seq_region,
MAX_SEARCH_LENGTH)
sought += 1
reply = find_NNN(cursor, ensembl_db_name, cfg, acg, he,
maps_for_exon[he], species, gene_id,
gene_coords, prev_seq_region, next_seq_region,
template_info, mitochondrial, method)
if reply == 'NNN':
unsequenced += 1
# repeat the whole procedure on the right
prev_seq_region = None
for he in no_right:
m = map_table[species][he]
# check first if we haave already looked into this, and found incomplete region
#if m and m.warning: continue
# get template (known exon from the nearest species)
template_info = get_template(cursor, ensembl_db_name,
map_table, species, he)
if not template_info: continue
# get following region
if not prev_seq_region:
prev_seq_region = get_neighboring_region(
cursor, ensembl_db_name, map_table, species,
gene_coords, he, previous[he])
if not prev_seq_region: continue
# otherwise it is the last thing we found
# the following region is eyeballed from the previous
next_seq_region = right_region(prev_seq_region,
MAX_SEARCH_LENGTH)
sought += 1
reply = find_NNN(cursor, ensembl_db_name, cfg, acg, he,
maps_for_exon[he], species, gene_id,
gene_coords, prev_seq_region, next_seq_region,
template_info, mitochondrial, method)
if reply == 'NNN':
unsequenced += 1
print(species, "sought", sought, " unseq", unsequenced)
def main():
verbose = True
db = connect_to_mysql()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
# find db ids adn common names for each species db
[all_species, ensembl_db_name] = get_species(cursor)
logf = erropen("error.log", "w")
if not logf: exit(1)
outf = erropen("mut_significance_bg_data.txt", "w")
if not outf: exit(1)
switch_to_db(cursor, ensembl_db_name['homo_sapiens'])
gene_ids = get_gene_ids(cursor,
biotype='protein_coding',
is_known=1,
ref_only=True)
# the categories of mutations for which we will be collecting statistics
fill_category()
# for each human gene
#gene_ids = [10093176 ]
for gene_id in gene_ids:
switch_to_db(cursor, ensembl_db_name['homo_sapiens'])
stable_id = gene2stable(cursor, gene_id)
# find all canonical coding human exons
# get_canonical_coding_exons also sorts exons by the start in the gene
canonical_human_exons = get_canonical_coding_exons(
cursor, gene_id, ensembl_db_name['homo_sapiens'])
# bail out if there is a problem
if not canonical_human_exons: continue
full_reconstituted_cDNA = ""
prev_codon_piece_plus_right_flank = ""
for human_exon in canonical_human_exons:
[exon_seq_id, pepseq, pepseq_transl_start, pepseq_transl_end, left_flank, right_flank, nucseq] = \
get_exon_seqs(cursor, human_exon.exon_id, human_exon.is_known)
# add the split codon
phase = get_exon_phase(cursor, human_exon.exon_id,
human_exon.is_known)
left_flank_plus_codon_piece = left_flank + nucseq[:
pepseq_transl_start]
split_codon = ""
if phase > 0 and prev_codon_piece_plus_right_flank and left_flank:
offset = (3 - phase) % 3
# hedge against the possibility that the translation starts
# right at the start of the exon, but there is supposed to be a phase
split_codon = prev_codon_piece_plus_right_flank[:
phase] + left_flank_plus_codon_piece[
-offset:]
full_reconstituted_cDNA += split_codon + nucseq[
pepseq_transl_start:pepseq_transl_end]
prev_codon_piece_plus_right_flank = nucseq[
pepseq_transl_end:] + right_flank
mitochondrial = is_mitochondrial(cursor, gene_id)
if (mitochondrial):
full_reconstituted_seq = Seq(full_reconstituted_cDNA).translate(
table="Vertebrate Mitochondrial").tostring()
else:
full_reconstituted_seq = Seq(
full_reconstituted_cDNA).translate().tostring()
canonical = get_canonical_transl(acg,
cursor,
gene_id,
'homo_sapiens',
strip_X=False)
if canonical[
0] == 'X': #that's some crap apparently wrong transcript is annotated as canonical
print >> logf, "warning", gene_id, stable_id, get_description(
cursor, gene_id)
print >> logf, "the deposited canonical sequence starts with X - is there an alternative (?)"
canonical = canonical[1:]
if full_reconstituted_seq[-1] == '*' and canonical[-1] != '*':
canonical += '*'
if (len(full_reconstituted_seq) != len(canonical)
or full_reconstituted_seq != canonical):
if (len(canonical) - len(full_reconstituted_seq) < 3
and full_reconstituted_seq in canonical):
# go with it - I do not have that much of that crap anyway
print >> logf, "warning", gene_id, stable_id, get_description(
cursor, gene_id)
print >> logf, "missing a couple of amino acids in beginning or in the end"
else:
print >> logf, "error", gene_id, stable_id, get_description(
cursor, gene_id)
print >> logf, "error reassembling, len(full_reconstituted_seq) != len(canonical) ", len(
full_reconstituted_seq), len(canonical)
print >> logf, "canonical:"
print >> logf, canonical
print >> logf, "reconstituted:"
print >> logf, full_reconstituted_seq
continue
# nucleotide stats
count = {'A': 0, 'C': 0, 'C-CpG': 0, 'T': 0, 'G': 0, 'G-CpG': 0}
is_CpG = {}
for i in range(len(full_reconstituted_cDNA)):
is_CpG[i] = False
if full_reconstituted_cDNA[i] == 'A':
count['A'] += 1
elif full_reconstituted_cDNA[i] == 'T':
count['T'] += 1
elif full_reconstituted_cDNA[i] == 'C':
if i + 1 < len(full_reconstituted_cDNA
) and full_reconstituted_cDNA[i + 1] == 'G':
count['C-CpG'] += 1
is_CpG[i] = True
else:
count['C'] += 1
elif full_reconstituted_cDNA[i] == 'G':
if i > 0 and full_reconstituted_cDNA[i - 1] == 'C':
count['G-CpG'] += 1
is_CpG[i] = True
else:
count['G'] += 1
# in each category_dict (AT transt, AT transv, CG trans, CG transv, Cpg trans, cpGtransv, how many missense,
# how many nonsense, how many silent possible
codons = map(''.join, zip(*[iter(full_reconstituted_cDNA)] * 3))
silent = {}
missense = {}
nonsense = {}
for cg in categories:
silent[cg] = 0
missense[cg] = 0
nonsense[cg] = 0
for i in range(len(codons)):
codon = codons[i]
aa = full_reconstituted_seq[i]
for j in range(3):
nt_position = i * 3 + j
nt = full_reconstituted_cDNA[nt_position]
for new_nt in ['A', 'C', 'T', 'G']:
if new_nt == nt: continue
mutated_codon = mutate(codon, j, new_nt)
if (mitochondrial):
mutated_aa = Seq(mutated_codon).translate(
table="Vertebrate Mitochondrial").tostring()
else:
mutated_aa = Seq(mutated_codon).translate().tostring()
cg = category_dict[codon[j]][new_nt][is_CpG[nt_position]]
if not cg or not cg in categories:
print >> logf, "category problem in ", gene_id, stable_id, get_description(
cursor, gene_id)
print >> logf, codon, mutated_codon, j, codon[
j], new_nt, is_CpG[nt_position], cg
print >> logf, i, j, nt_position, nt
print >> logf, aa, mutated_aa
continue
if (mutated_aa == aa):
silent[cg] += 1
elif (mutated_aa == "*"):
nonsense[cg] += 1
else:
missense[cg] += 1
print >> outf, stable_id, get_description(cursor, gene_id)
print >> outf, "# CpG nucleotides (format: cdna_position|nucleotide|codon|context; )"
print >> outf, "# ('context' contains one nucleotide before and one after the CpG nucleotide)"
outstr = ""
for i in range(len(full_reconstituted_cDNA)):
if (is_CpG[i]):
context = ""
if i > 0: context += full_reconstituted_cDNA[i - 1]
context += full_reconstituted_cDNA[i]
if i < len(full_reconstituted_cDNA) - 1:
context += full_reconstituted_cDNA[i + 1]
outstr += "%d|%s|%s|%s;" % (i + 1, full_reconstituted_cDNA[i],
codons[i / 3], context)
print >> outf, outstr
print >> outf, "# mutations possible (in principle)"
print >> outf, "# %10s %5s %5s %5s" % ("category", "silent",
"nonsense", "missense")
for cg in categories:
print >> outf, "%10s %5d %5d %5d" % (cg, silent[cg],
nonsense[cg], missense[cg])
print >> outf, "# canonical sequence (format: <amino_acid><position_on_peptide_chain><codon>;):"
outstr = ""
for i in range(len(codons)):
if (mitochondrial):
codon_transl = Seq(codons[i]).translate(
table="Vertebrate Mitochondrial").tostring()
else:
codon_transl = Seq(codons[i]).translate().tostring()
outstr += "%s%d%s;" % (full_reconstituted_seq[i], i + 1, codons[i])
print >> outf, outstr
print >> outf, stable_id, "done"
logf.close()
def multiple_exon_alnmt(gene_list, db_info):
print "process pid: %d, length of gene list: %d" % ( get_process_id(), len(gene_list))
[local_db, ensembl_db_name] = db_info
db = connect_to_mysql()
cfg = ConfigurationReader()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
# find db ids adn common names for each species db
[all_species, ensembl_db_name] = get_species (cursor)
species = 'homo_sapiens'
switch_to_db (cursor, ensembl_db_name[species])
gene_ids = get_gene_ids (cursor, biotype='protein_coding', is_known=1)
# for each human gene
gene_ct = 0
tot = 0
ok = 0
no_maps = 0
no_pepseq = 0
no_orthologues = 0
min_similarity = cfg.get_value('min_accptbl_exon_sim')
#gene_list.reverse()
for gene_id in gene_list:
start = time()
gene_ct += 1
if not gene_ct%10: print gene_ct, "genes out of", len(gene_list)
switch_to_db (cursor, ensembl_db_name['homo_sapiens'])
print gene_ct, len(gene_ids), gene_id, gene2stable(cursor, gene_id), get_description (cursor, gene_id)
human_exons = filter (lambda e: e.is_known==1 and e.is_coding and e.covering_exon<0, gene2exon_list(cursor, gene_id))
human_exons.sort(key=lambda exon: exon.start_in_gene)
##################################################################
for human_exon in human_exons:
tot += 1
# find all orthologous exons the human exon maps to
maps = get_maps(cursor, ensembl_db_name, human_exon.exon_id, human_exon.is_known)
if verbose:
print "\texon no.", tot, " id", human_exon.exon_id,
if not maps:
print " no maps"
print human_exon
print
if not maps:
no_maps += 1
continue
# human sequence to fasta:
seqname = "{0}:{1}:{2}".format('homo_sapiens', human_exon.exon_id, human_exon.is_known)
switch_to_db (cursor, ensembl_db_name['homo_sapiens'])
[exon_seq_id, pepseq, pepseq_transl_start, pepseq_transl_end,
left_flank, right_flank, dna_seq] = get_exon_seqs (cursor, human_exon.exon_id, human_exon.is_known)
if (not pepseq):
if verbose and human_exon.is_coding and human_exon.covering_exon <0: # this should be a master exon
print "no pep seq for", human_exon.exon_id, "coding ", human_exon.is_coding,
print "canonical: ", human_exon.is_canonical
print "length of dna ", len(dna_seq)
no_pepseq += 1
continue
# collect seq from all maps, and output them in fasta format
hassw = False
headers = []
sequences = {}
exons_per_species = {}
for map in maps:
switch_to_db (cursor, ensembl_db_name[map.species_2])
if map.similarity < min_similarity: continue
exon = map2exon(cursor, ensembl_db_name, map)
pepseq = get_exon_pepseq (cursor,exon)
if (not pepseq):
continue
if map.source == 'sw_sharp':
exon_known_code = 2
hassw = True
elif map.source == 'usearch':
exon_known_code = 3
hassw = True
else:
exon_known_code = map.exon_known_2
seqname = "{0}:{1}:{2}".format(map.species_2, map.exon_id_2, exon_known_code)
headers.append(seqname)
sequences[seqname] = pepseq
# for split exon concatenation (see below)
if not map.species_2 in exons_per_species.keys():
exons_per_species[map.species_2] = []
exons_per_species[map.species_2].append ([ map.exon_id_2, exon_known_code]);
if (len(headers) <=1 ):
if verbose: print "single species in the alignment"
no_orthologues += 1
continue
# concatenate exons from the same gene - the alignment program might go wrong otherwise
concatenated = concatenate_exons (cursor, ensembl_db_name, sequences, exons_per_species)
fasta_fnm = "{0}/{1}.fa".format( cfg.dir_path['scratch'], human_exon.exon_id)
output_fasta (fasta_fnm, sequences.keys(), sequences)
# align
afa_fnm = "{0}/{1}.afa".format( cfg.dir_path['scratch'], human_exon.exon_id)
mafftcmd = acg.generate_mafft_command (fasta_fnm, afa_fnm)
ret = commands.getoutput(mafftcmd)
if (verbose): print 'almt to', afa_fnm
# read in the alignment
inf = erropen(afa_fnm, "r")
aligned_seqs = {}
for record in SeqIO.parse(inf, "fasta"):
aligned_seqs[record.id] = str(record.seq)
inf.close()
# split back the concatenated exons
if concatenated: split_concatenated_exons (aligned_seqs, concatenated)
human_seq_seen = False
for seq_name, sequence in aligned_seqs.iteritems():
# if this is one of the concatenated seqs, split them back to two
### store the alignment as bitstring
# Generate the bitmap
bs = Bits(bin='0b' + re.sub("[^0]","1", sequence.replace('-','0')))
# The returned value of tobytes() will be padded at the end
# with between zero and seven 0 bits to make it byte aligned.
# I will end up with something that looks like extra alignment gaps, that I'll have to return
msa_bitmap = bs.tobytes()
# Retrieve information on the cognate
cognate_species, cognate_exon_id, cognate_exon_known = seq_name.split(':')
if cognate_exon_known == '2':
source = 'sw_sharp'
elif cognate_exon_known == '3':
source = 'usearch'
else:
source = 'ensembl'
if (cognate_species == 'homo_sapiens'):
human_seq_seen = True
cognate_genome_db_id = species2genome_db_id(cursor, cognate_species) # moves the cursor
switch_to_db(cursor, ensembl_db_name['homo_sapiens']) # so move it back to h**o sapiens
# Write the bitmap to the database
#if (cognate_species == 'homo_sapiens'):
if verbose: # and (source=='sw_sharp' or source=='usearch'):
print "storing"
print human_exon.exon_id, human_exon.is_known
print cognate_species, cognate_genome_db_id, cognate_exon_id, cognate_exon_known, source
print sequence
if not msa_bitmap:
print "no msa_bitmap"
continue
store_or_update(cursor, "exon_map", {"cognate_genome_db_id":cognate_genome_db_id,
"cognate_exon_id":cognate_exon_id ,"cognate_exon_known" :cognate_exon_known,
"source": source, "exon_id" :human_exon.exon_id, "exon_known":human_exon.is_known},
{"msa_bitstring":MySQLdb.escape_string(msa_bitmap)})
ok += 1
commands.getoutput("rm "+afa_fnm+" "+fasta_fnm)
if verbose: print " time: %8.3f\n" % (time()-start);
print "tot: ", tot, "ok: ", ok
print "no maps ", no_pepseq
print "no pepseq ", no_pepseq
print "no orthologues ", no_orthologues
print
def multiple_exon_alnmt(species_list, db_info):
[local_db, ensembl_db_name] = db_info
verbose = False
db = connect_to_mysql()
cfg = ConfigurationReader()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
for species in species_list:
print
print "############################"
print species
switch_to_db (cursor, ensembl_db_name[species])
gene_ids = get_gene_ids (cursor, biotype='protein_coding')
#gene_ids = get_theme_ids(cursor, cfg, 'wnt_pathway')
if not gene_ids:
print "no gene_ids"
continue
gene_ct = 0
tot = 0
ok = 0
no_maps = 0
no_pepseq = 0
no_paralogues = 0
for gene_id in gene_ids:
if verbose: start = time()
gene_ct += 1
if not gene_ct%100: print species, gene_ct, "genes out of", len(gene_ids)
if verbose:
print
print gene_id, gene2stable(cursor, gene_id), get_description (cursor, gene_id)
# get the paralogues - only the representative for the family will have this
paralogues = get_paras (cursor, gene_id)
if not paralogues:
if verbose: print "\t not a template or no paralogues"
continue
if verbose: print "paralogues: ", paralogues
# get _all_ exons
template_exons = gene2exon_list(cursor, gene_id)
if (not template_exons):
if verbose: print 'no exons for ', gene_id
continue
# find all template exons we are tracking in the database
for template_exon in template_exons:
if verbose: print template_exon.exon_id
maps = get_maps(cursor, ensembl_db_name, template_exon.exon_id,
template_exon.is_known, species=species, table='para_exon_map')
if not maps:
no_maps += 1
continue
# output to fasta:
seqname = "{0}:{1}:{2}".format('template', template_exon.exon_id, template_exon.is_known)
exon_seqs_info = get_exon_seqs (cursor, template_exon.exon_id, template_exon.is_known)
if not exon_seqs_info: continue
[exon_seq_id, pepseq, pepseq_transl_start, pepseq_transl_end,
left_flank, right_flank, dna_seq] = exon_seqs_info
if (not pepseq):
if ( template_exon.is_coding and template_exon.covering_exon <0): # this should be a master exon
print "no pep seq for", template_exon.exon_id, "coding ", template_exon.is_coding,
print "canonical: ", template_exon.is_canonical
print "length of dna ", len(dna_seq)
no_pepseq += 1
continue
tot += 1
sequences = {seqname:pepseq}
headers = [seqname]
for map in maps:
exon = map2exon(cursor, ensembl_db_name, map, paralogue=True)
pepseq = get_exon_pepseq (cursor,exon)
if (not pepseq):
continue
seqname = "{0}:{1}:{2}".format('para', map.exon_id_2, map.exon_known_2)
headers.append(seqname)
sequences[seqname] = pepseq
fasta_fnm = "{0}/{1}_{2}_{3}.fa".format( cfg.dir_path['scratch'], species, template_exon.exon_id, template_exon.is_known)
output_fasta (fasta_fnm, headers, sequences)
if (len(headers) <=1 ):
print "single species in the alignment (?)"
no_paralogues += 1
continue
# align
afa_fnm = "{0}/{1}_{2}_{3}.afa".format( cfg.dir_path['scratch'], species, template_exon.exon_id, template_exon.is_known)
mafftcmd = acg.generate_mafft_command (fasta_fnm, afa_fnm)
ret = commands.getoutput(mafftcmd)
# read in the alignment
inf = erropen(afa_fnm, "r")
if not inf:
print gene_id
continue
template_seq_seen = False
for record in SeqIO.parse(inf, "fasta"):
### store the alignment as bitstring
# Generate the bitmap
bs = Bits(bin='0b' + re.sub("[^0]","1", str(record.seq).replace('-','0')))
msa_bitmap = bs.tobytes()
# Retrieve information on the cognate
label, cognate_exon_id, cognate_exon_known = record.id.split(':')
if (label == 'template'):
template_seq_seen = True
# Write the bitmap to the database
#print "updating: ", template_exon.exon_id
store_or_update(cursor, "para_exon_map", {"cognate_exon_id" :cognate_exon_id,
"cognate_exon_known" :cognate_exon_known,
"exon_id" :template_exon.exon_id,
"exon_known" :template_exon.is_known},
{"msa_bitstring":MySQLdb.escape_string(msa_bitmap)})
inf.close()
ok += 1
commands.getoutput("rm "+afa_fnm+" "+fasta_fnm)
if verbose: print " time: %8.3f\n" % (time()-start);
outstr = species + " done \n"
outstr += "tot: %d ok: %d \n" % (tot, ok)
outstr += "no maps %d \n" % no_pepseq
outstr += "no pepseq %d \n" % no_pepseq
outstr += "no paralogues %d \n" % no_paralogues
outstr += "\n"
print outstr
def exon_cleanup(gene_list, db_info):
[local_db, ensembl_db_name] = db_info
db = connect_to_mysql()
cfg = ConfigurationReader()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
# find db ids and common names for each species db
all_species, ensembl_db_name = get_species(cursor)
mammals = [
'ailuropoda_melanoleuca', 'bos_taurus', 'callithrix_jacchus',
'canis_familiaris', 'cavia_porcellus', 'choloepus_hoffmanni',
'dasypus_novemcinctus', 'dipodomys_ordii', 'echinops_telfairi',
'equus_caballus', 'erinaceus_europaeus', 'felis_catus',
'gorilla_gorilla', 'ictidomys_tridecemlineatus', 'loxodonta_africana',
'macaca_mulatta', 'macropus_eugenii', 'microcebus_murinus',
'monodelphis_domestica', 'mus_musculus', 'mustela_putorius_furo',
'myotis_lucifugus', 'nomascus_leucogenys', 'ochotona_princeps',
'ornithorhynchus_anatinus', 'oryctolagus_cuniculus',
'otolemur_garnettii', 'pan_troglodytes', 'papio_anubis',
'pongo_abelii', 'procavia_capensis', 'pteropus_vampyrus',
'rattus_norvegicus', 'sarcophilus_harrisii', 'sorex_araneus',
'sus_scrofa', 'tarsius_syrichta', 'tupaia_belangeri',
'tursiops_truncatus', 'vicugna_pacos'
]
tot = 0
tot_ok = 0
for human_gene_id in gene_list:
switch_to_db(cursor, ensembl_db_name['homo_sapiens'])
stable_id = gene2stable(cursor, human_gene_id)
description = get_description(cursor, human_gene_id)
mitochondrial = is_mitochondrial(cursor, human_gene_id)
#print "#############################################"
#print human_gene_id, stable_id, get_description (cursor, human_gene_id)
human_exons = get_ok_human_exons(cursor, ensembl_db_name,
human_gene_id)
for human_exon in human_exons:
[
exon_seq_id, human_protein_seq, pepseq_transl_start,
pepseq_transl_end, left_flank, right_flank, dna_seq
] = get_exon_seqs(cursor, human_exon.exon_id, 1,
ensembl_db_name['homo_sapiens'])
human_exon_phase = get_exon_phase(cursor, human_exon.exon_id, 1)
first_exon = (human_exons.index(human_exon) == 0)
for species in mammals: # maxentscan does not work for fish
for table in ['sw_exon', 'usearch_exon']:
switch_to_db(cursor, ensembl_db_name[species])
qry = "select * from %s where maps_to_human_exon_id = %d " % (
table, human_exon.exon_id)
novel_exons = search_db(cursor, qry)
if not novel_exons:
#print "human_exon: ", human_exon.exon_id, "no", table, "for", species
continue
ct = 0
ok = 0
for novel_exon in novel_exons:
print "%s: novel exon found in table %s, mapping to human exon %s" % \
(species, table, exon2stable (cursor, human_exon.exon_id, ensembl_db_name['homo_sapiens']) )
ct += 1
has_stop = False
has_NNN = False
[
novel_exon_id, gene_id, start_in_gene, end_in_gene,
maps_to_human_exon_id, exon_seq_id,
template_exon_seq_id, template_species, strand,
phase, end_phase, has_NNN, has_stop, has_3p_ss,
has_5p_ss
] = novel_exon
tot += 1
exon_seqs = get_exon_seq_by_db_id(
cursor, exon_seq_id, ensembl_db_name[species])
if not exon_seqs:
print "exon seqs not found"
continue
[
exon_seq_id, protein_seq, pepseq_transl_start,
pepseq_transl_end, left_flank, right_flank, dna_seq
] = exon_seqs
len_ok = (pepseq_transl_end -
pepseq_transl_start) == len(dna_seq)
if not len_ok:
# if it is not the case, then make it be so
left_flank += dna_seq[:pepseq_transl_start]
right_flank = dna_seq[
pepseq_transl_end:] + right_flank
dna_seq = dna_seq[
pepseq_transl_start:pepseq_transl_end]
pepseq_transl_start = 0
pepseq_transl_end = len(dna_seq)
phase_ok = (len(dna_seq) % 3 == 0)
if not phase_ok:
phase = len(dna_seq) % 3
cds = dna_seq[phase:]
pepseq_corrected = Seq(cds).translate().tostring()
if pepseq_corrected == protein_seq:
left_flank += dna_seq[:phase]
dna_seq = dna_seq[phase:]
else:
cds = dna_seq[:-phase]
pepseq_corrected = Seq(
cds).translate().tostring()
if pepseq_corrected == protein_seq:
right_flank += dna_seq[
-phase:] + right_flank
dna_seq = dna_seq[:-phase]
else:
print "no match ..."
continue # don't want to shut-off the pipeline here
pepseq_transl_start = 0
pepseq_transl_end = len(dna_seq)
# retrieve the template
template_db_id = species2genome_db_id(
cursor, template_species)
[templ_exon_seq_id, templ_protein_seq, templ_pepseq_transl_start,
templ_pepseq_transl_end, templ_left_flank, templ_right_flank, templ_dna_seq] \
= get_exon_seq_by_db_id (cursor, template_exon_seq_id, ensembl_db_name[template_species])
correction = 0
phase = 0
end_phase = 0
# if this is the first exon, check if we are starting from methionine
if first_exon:
[left_flank_ok, correction, phase] = \
check_translation_start (mitochondrial, left_flank, dna_seq, templ_dna_seq, templ_protein_seq)
# see if the left splice site is ok
else:
[left_flank_ok, correction, phase, max_score] = \
check_left_flank (acg, left_flank, dna_seq, templ_dna_seq)
########################
#
# see if the right splice site is ok
[right_flank_ok, end_correction, end_phase, end_max_score] = \
check_right_flank(acg, right_flank, dna_seq, templ_dna_seq)
pepseq_corrected = ""
new_left_flank = ""
new_right_flank = ""
new_dna_seq = ""
if left_flank_ok:
offset = (3 - phase) % 3
if correction:
if correction > 0:
new_dna_seq = dna_seq[correction:]
new_left_flank = left_flank + dna_seq[:
correction]
else:
# correction is negative, therefore left_flank[correction:] is the tail of left_flank
new_dna_seq = left_flank[
correction:] + dna_seq
new_left_flank = left_flank[:correction]
else:
new_left_flank = left_flank
pepseq_transl_start = offset
else:
new_left_flank = left_flank
if right_flank_ok:
if not new_dna_seq: new_dna_seq = dna_seq
if end_correction:
if end_correction < 0:
new_right_flank = new_dna_seq[
end_correction:] + right_flank
new_dna_seq = new_dna_seq[:end_correction]
else:
# correction is negative, therefore right_flank[correction:] is the tail of right_flank
new_right_flank = right_flank[
end_correction:]
new_dna_seq += right_flank[:end_correction]
else:
new_right_flank = right_flank
pepseq_transl_end = len(new_dna_seq)
pepseq_transl_end -= end_phase
else:
new_right_flank = right_flank
# if only one flank is ok, use that side to decide if there is a phase on the other
if left_flank_ok and not right_flank_ok:
end_phase = (pepseq_transl_end -
pepseq_transl_start) % 3
pepseq_transl_end -= end_phase
if right_flank_ok and not left_flank_ok:
phase = (pepseq_transl_end -
pepseq_transl_start) % 3
pepseq_transl_start += phase
# check that the lengths match
has_stop = None
if new_dna_seq:
len_old = len(left_flank + dna_seq + right_flank)
len_new = len(new_left_flank + new_dna_seq +
new_right_flank)
if not len_old == len_new:
print len_old, len_new
print correction, end_correction
print map(len,
[left_flank, dna_seq, right_flank])
print map(len, [
new_left_flank, new_dna_seq,
new_right_flank
])
continue
cds = new_dna_seq[
pepseq_transl_start:pepseq_transl_end]
if mitochondrial:
pepseq_corrected = Seq(cds).translate(
table="Vertebrate Mitochondrial").tostring(
)
else:
pepseq_corrected = Seq(
cds).translate().tostring()
if '*' in pepseq_corrected:
has_stop = 1
else:
has_stop = 0
if has_stop and not '*' in protein_seq:
continue # abort, abort
if True:
print "#############################################"
print human_gene_id, stable_id, "exo no:", human_exons.index(
human_exon), " ", description
print species, table
print "\t template", template_exon_seq_id, template_species, template_db_id
print "\t template left flank", templ_left_flank, templ_dna_seq[
0:3]
print "\t left flank", left_flank, dna_seq[
0:3]
print "\t ", left_flank_ok, correction, phase,
if not first_exon:
print max_score
else:
print
print "\t template right flank", templ_dna_seq[
-3:], templ_right_flank
print "\t right flank", dna_seq[
-3:], right_flank
print "\t ", right_flank_ok, end_correction, end_phase, end_max_score
print "\t human", human_protein_seq, human_exon.exon_id, human_exon_phase
print "\t template", templ_protein_seq
print "\t deposited", protein_seq
if pepseq_corrected:
print "\t corrected", pepseq_corrected
if new_dna_seq:
if (pepseq_transl_end - pepseq_transl_start) % 3:
print "length not divisible by 3 "
print pepseq_transl_start, pepseq_transl_end
print phase, end_phase
print len(new_dna_seq)
print "%%%%% "
continue
else:
new_dna_seq = dna_seq
#########################################################
# 18_find_exons is sometimes messing up the coordinates
# I do not know why
ret = check_coordinates_in_the_gene(
cursor, cfg, acg, ensembl_db_name, species,
novel_exon, new_dna_seq)
if not ret:
print "\t coordinate check failed"
continue
[start_in_gene_corrected, end_in_gene_corrected] = ret
#########################################################
# update the *_exon and exon_seq tables accordingly
switch_to_db(cursor, ensembl_db_name[species])
qry = "update %s set " % table
set_fields = ""
if not start_in_gene_corrected == start_in_gene:
if set_fields: set_fields += ", "
set_fields += " start_in_gene = %d " % start_in_gene_corrected
if not end_in_gene_corrected == end_in_gene:
if set_fields: set_fields += ", "
set_fields += " end_in_gene = %d " % end_in_gene_corrected
if not has_stop is None:
if set_fields: set_fields += ", "
set_fields += " has_stop = %d" % has_stop
if left_flank_ok:
if set_fields: set_fields += ", "
set_fields += " phase = %d, " % phase
if first_exon:
set_fields += " has_3p_ss = '%s' " % (
"first exon; starts with M")
else:
set_fields += " has_3p_ss = '%s' " % (
"me_score=" + str(max_score))
if right_flank_ok:
if set_fields: set_fields += ", "
set_fields += " end_phase = %d, " % end_phase
set_fields += " has_5p_ss = '%s' " % (
"me_score=" + str(end_max_score))
qry += set_fields + " where exon_id=%d" % novel_exon_id
if set_fields:
search_db(cursor, qry)
# update exon sequence
if pepseq_corrected:
# we might have changed our mind as to what is the cDNA seq, and what is flanking
qry = "update exon_seq set "
qry += " protein_seq = '%s', " % pepseq_corrected
qry += " dna_seq = '%s', " % new_dna_seq
qry += " left_flank = '%s', " % new_left_flank
qry += " right_flank = '%s', " % new_right_flank
qry += " pepseq_transl_start = %d, " % pepseq_transl_start
qry += " pepseq_transl_end = %d " % pepseq_transl_end
table_id = 2 if table == 'novel_exon' else 3
qry += " where exon_id=%d and is_known=%d" % (
novel_exon_id, table_id)
search_db(cursor, qry)
# gene2exon --> have to go back to 07_gene2exon for that
tot_ok += 1
print "gene list done"
cursor.close()
db.close()
def main():
db = connect_to_mysql()
acg = AlignmentCommandGenerator()
cursor = db.cursor()
[all_species, ensembl_db_name] = get_species(cursor)
if len(sys.argv) > 1:
species_list = sys.argv[1:]
else:
species_list = all_species
############################
for species in species_list:
print
print "############################"
print species
switch_to_db(cursor, ensembl_db_name[species])
if (species == 'homo_sapiens'):
gene_ids = get_gene_ids(cursor,
biotype='protein_coding',
is_known=1)
else:
gene_ids = get_gene_ids(cursor, biotype='protein_coding')
ct = 0
tot = 0
for tot in range(1000):
#for gene_id in gene_ids:
#tot += 1
gene_id = choice(gene_ids)
# find all canonical coding exons associated with the gene id
exons = get_canonical_coding_exons(cursor, gene_id)
if (not exons):
ct += 1
print gene_id, gene2stable(
cursor, gene_id=gene_id), " no exons found ", ct, tot
if not tot % 100:
print species, tot, ct
# add up the coding length of the canonical exons
exons.sort(key=lambda exon: exon.start_in_gene)
inside_the_coding_range = False
start_properly_marked = False
length = 0
for exon in exons:
if not exon.canon_transl_start is None:
start_properly_marked = True # if it is not propermy marked, we'll never start reading
inside_the_coding_range = True
length -= exon.canon_transl_start - 1
if not exon.canon_transl_end is None:
inside_the_coding_range = False
length += exon.canon_transl_end
if inside_the_coding_range:
length += exon.end_in_gene - exon.start_in_gene + 1
# take that all exons are coding full length if there is no start and end annotation
# (this I believe is the case for predicted transcripts)
if not start_properly_marked:
length = 0
for exon in exons:
length += exon.end_in_gene - exon.start_in_gene + 1
if (not length):
print gene2stable(
cursor, gene_id=gene_id), " no exons marked as canonical"
continue
# what is the length of the canonical transcript according to Ensembl
canonical_translation = get_canonical_transl(acg,
cursor,
gene_id,
species,
strip_X=False)
if (not canonical_translation):
print "no canonical transl found for ", gene_id
continue
if (abs(length / 3 - len(canonical_translation)) > 3):
ct += 1
print gene_id, gene2stable(cursor, gene_id), get_description(
cursor, gene_id)
print "(length of all exons)/3 ", length / 3,
print " does not match reported canonical transl len ", len(
canonical_translation)
if False:
# print out all exons
print "exons:"
inspect(exons)
print
print 'canonical sequence'
print re.sub(
"(.{50})", "\\1\n", canonical_translation
) # print canonical sequence with \n stuck in every 50 positions
print
# print out exons more carefully filtered to belong to the canonical version of the translation
print
get_translated_region_talkative(cursor, gene_id, species)
all_exons = gene2exon_list(cursor, gene_id)
print "all exons:"
inspect(all_exons)
print
compare_seqs(canonical_translation,
translated_seq,
verbose=False)
exit(1)
print species, "checked a sample of ", tot + 1, "genes; problematic:", ct
cursor.close()
db.close()
#
# print 'Note: some problems could not have be resolved up to this point,'
# print 'becasue we have not really looged at the exons seqs yet.'
# print 'For example, for MP furo the, start fo the cannonical translation'
# print 'is sometimes given in the middle of NNNNN region.'
#
return True
