def read_modification_dict(modifications_tsv):
result = {}
for entry in parse.read_tsv(modifications_tsv):
# pprint(entry)
key = entry['description']
if 'residue' in entry:
aa = entry['residue']
elif 'amino acid residue' in entry:
aa = entry['amino acid residue']
delta_mass = entry['monoisotopic mass shift (da)']
if aa == 'n/a':
continue
mass = peptidemass.aa_monoisotopic_mass[aa] + float(delta_mass)
result[key] = mass
return result
def read_modification_dict(modifications_tsv):
result = {}
for entry in parse.read_tsv(modifications_tsv):
key = entry['description']
mass = float(entry['monoisotopic mass shift (da)'])
if 'residue' in entry:
aa = entry['residue']
elif 'amino acid residue' in entry:
aa = entry['amino acid residue']
else:
aa = 'n/a'
if aa != 'n/a':
mass += peptidemass.aa_monoisotopic_mass[aa]
result[key] = mass
return result
def get_proteins(protein_groups_fname, psm_fname, modifications_fname=None):
dump_dir = os.path.dirname(protein_groups_fname)
if modifications_fname is not None:
modification_table = read_modification_dict(modifications_fname)
else:
modification_table = {}
peptides = parse.read_tsv(psm_fname)
protein_groups = parse.read_tsv(protein_groups_fname)
if logger.root.level <= logging.DEBUG:
dump = os.path.join(dump_dir, 'peptides.dump')
logger.debug('Dumping peptides data structure to ' + dump)
parse.save_data_dict(peptides, dump)
dump = os.path.join(dump_dir, 'protein_groups.dump')
logger.debug('Dumping protein_groups data structure to ' + dump)
parse.save_data_dict(protein_groups, dump)
proteins = {}
for i_group, protein_group in enumerate(protein_groups):
descriptions = protein_group['protein description'].split(' / ')
seqids = [desc.split()[0] for desc in descriptions]
for seqid in seqids:
if seqid in proteins:
logger.warning(
"Different protein groups claim same first seqid", seqid)
protein = {
'description': descriptions[0],
'sequence': protein_group['protein sequence'],
'attr': {
'coverage':
protein_group['protein sequence coverage (%)'],
'morpheus-score':
parse.round_decimal(protein_group['summed morpheus score'], 4),
'i_group':
i_group,
'other_seqids':
seqids[1:],
'seqid':
seqids[0],
},
'sources': [{
'peptides': []
}]
}
proteins[seqids[0]] = protein
protein_by_seqid = {}
for seqid in proteins:
protein = proteins[seqid]
protein_by_seqid[seqid] = protein
for alt_seqid in protein['attr']['other_seqids']:
protein_by_seqid[alt_seqid] = protein
unmatched_peptides = []
n_peptide_matched = 0
for src_peptide in peptides:
descriptions = src_peptide['protein description'].split(' / ')
peptide_seqids = [d.split()[0] for d in descriptions]
protein = None
for peptide_seqid in peptide_seqids:
if peptide_seqid in protein_by_seqid:
protein = protein_by_seqid[peptide_seqid]
break
if protein is None:
unmatched_peptides.append(src_peptide)
continue
n_peptide_matched += 1
sequence = protein['sequence']
peptide_sequence, modifications = parse_peptide(
src_peptide['peptide sequence'], modification_table)
peptide_sequence = src_peptide['base peptide sequence']
i = sequence.index(peptide_sequence)
peptide = {
'sequence': peptide_sequence,
'attr': {
'scan_id':
src_peptide['scan number'],
'retention_time':
parse.round_decimal(src_peptide['retention time (min)'], 4),
'morpheus_score':
parse.round_decimal(src_peptide['morpheus score'], 4),
'mass':
parse.round_decimal(src_peptide['precursor mass (da)'], 4),
'mass_diff':
parse.round_decimal(src_peptide['precursor mass error (da)'],
4),
'm/z':
parse.round_decimal(src_peptide['precursor m/z'], 4),
'source':
parse.basename(src_peptide['filename']),
},
'intensity': src_peptide['morpheus score'] / len(peptide_sequence),
'i': i,
}
if modifications:
for modification in modifications:
modification['mass'] = parse.round_decimal(
modification['mass'], 4)
peptide['attr']['modifications'] = modifications
protein['sources'][0]['peptides'].append(peptide)
dump = os.path.join(dump_dir, 'proteins.dump')
logger.debug('Dumping proteins data structure to ' + dump)
if logger.root.level <= logging.DEBUG:
parse.save_data_dict(proteins, dump)
logger.info("Assigned {}/{} of PSMs.tsv to protein_groups.tsv".format(
n_peptide_matched, len(unmatched_peptides)))
return proteins
def get_proteins_and_sources(in_dir, great_expect=1E-8, cutoff_expect=1E-2):
evidence_fname = os.path.join(in_dir, 'evidence.txt')
logger.info('Loading evidence file: ' + evidence_fname)
evidence_iter = parse.read_tsv(evidence_fname)
evidence_dict = {int(e['id']): e for e in evidence_iter}
sources_set = set(e['raw file'] for e in evidence_dict.values())
sources = [str(s) for s in sorted(sources_set)]
i_sources = {source: k for k, source in enumerate(sources)}
protein_group_fname = os.path.join(in_dir, 'proteinGroups.txt')
logger.info('Loading protein groups: ' + protein_group_fname)
proteins = {}
protein_by_group_id = {}
for protein_group in parse.read_tsv(protein_group_fname):
group_id = protein_group['id']
protein = {
'description': '',
'attr': {
'group_id': group_id,
'other_seqids': [],
},
'sources': [{
'matches': []
} for k in range(len(i_sources))],
}
transfer_attrs(protein_group, protein['attr'], protein_parse_list)
seqids = parse.splitter(protein_group['protein ids'])
proteins[seqids[0]] = protein
protein['attr']['seqid'] = seqids[0]
protein['attr']['other_seqids'] = seqids[1:]
protein_by_group_id[group_id] = protein
peptides_fname = os.path.join(in_dir, 'peptides.txt')
logger.info('Loading peptides file: ' + peptides_fname)
peptides_iter = parse.read_tsv(peptides_fname)
peptides = {int(p['id']): p for p in peptides_iter}
scans_fname = os.path.join(in_dir, 'msms.txt')
logger.info('Loading scans and matching: ' + scans_fname)
i_scan = 0
for scan in parse.read_tsv(scans_fname):
scan_id = int(scan['id'])
i_scan += 1
if i_scan % 5000 == 0:
logger.info("{} scans processed".format(i_scan))
evidence_id = int(scan['evidence id'])
evidence = evidence_dict[evidence_id]
mod_seq = evidence['modified sequence']
mod_peptide_id = evidence['mod. peptide id']
peptide_id = int(scan['peptide id'])
peptide = peptides[peptide_id]
for group_id in parse.splitter(str(scan['protein group ids'])):
match = {
'sequence': scan['sequence'],
'spectrum': get_labeled_spectrum(scan),
'modifications': get_modifications(scan),
'attr': {
'modified_sequence': mod_seq,
'mq_scan_id': scan_id,
'evidence_id': evidence_id,
'is_unique': peptide['unique (groups)'] == 'yes',
}
}
if scan['pep'] > cutoff_expect:
continue
match['intensity'] = parse_proteins.calc_minus_log_intensity(
scan['pep'], great_expect, cutoff_expect)
transfer_attrs(scan, match['attr'], scan_parse_list)
transfer_attrs(evidence, match['attr'], evidence_parse_list)
transfer_attrs(peptide, match['attr'], peptide_parse_list)
change_key(match['attr'], 'scan number', 'scan_id')
change_key(match['attr'], 'retention time', 'retention_time')
protein = protein_by_group_id[int(group_id)]
i_source = i_sources[evidence['raw file']]
protein['sources'][i_source]['matches'].append(match)
parse_proteins.count_matches(proteins)
parse_proteins.delete_empty_proteins(proteins)
return proteins, sources
def read(in_dir):
peptides = parse.read_tsv(os.path.join(in_dir, 'peptides.txt'))
scans = parse.read_tsv(os.path.join(in_dir, 'msms.txt'))
protein_groups = parse.read_tsv(os.path.join(in_dir, 'proteinGroups.txt'))
evidence = parse.read_tsv(os.path.join(in_dir, 'evidence.txt'))
return peptides, scans, protein_groups, evidence
def get_proteins_and_sources(
in_dir,
great_expect=1E-8,
cutoff_expect=1E-2):
evidence_fname = os.path.join(in_dir, 'evidence.txt')
logger.info('Loading evidence file: ' + evidence_fname)
evidence_iter = parse.read_tsv(evidence_fname)
evidence_dict = { int(e['id']):e for e in evidence_iter }
sources_set = set(e['raw file'] for e in evidence_dict.values())
sources = [str(s) for s in sorted(sources_set)]
i_sources = {source:k for k, source in enumerate(sources)}
protein_group_fname = os.path.join(in_dir, 'proteinGroups.txt')
logger.info('Loading protein groups: ' + protein_group_fname)
proteins = {}
protein_by_group_id = {}
for protein_group in parse.read_tsv(protein_group_fname):
group_id = protein_group['id']
protein = {
'description': '',
'attr': {
'group_id': group_id,
'other_seqids': [],
},
'sources': [{ 'matches': [] } for k in range(len(i_sources))],
}
transfer_attrs(protein_group, protein['attr'], protein_parse_list)
seqids = parse.splitter(protein_group['protein ids'])
proteins[seqids[0]] = protein
protein['attr']['seqid'] = seqids[0]
protein['attr']['other_seqids'] = seqids[1:]
protein_by_group_id[group_id] = protein
peptides_fname = os.path.join(in_dir, 'peptides.txt')
logger.info('Loading peptides file: ' + peptides_fname)
peptides_iter = parse.read_tsv(peptides_fname)
peptides = { int(p['id']):p for p in peptides_iter }
scans_fname = os.path.join(in_dir, 'msms.txt')
logger.info('Loading scans and matching: ' + scans_fname)
i_scan = 0
for scan in parse.read_tsv(scans_fname):
scan_id = int(scan['id'])
i_scan += 1
if i_scan % 5000 == 0:
logger.info("{} scans processed".format(i_scan))
evidence_id = int(scan['evidence id'])
evidence = evidence_dict[evidence_id]
mod_seq = evidence['modified sequence']
mod_peptide_id = evidence['mod. peptide id']
peptide_id = int(scan['peptide id'])
peptide = peptides[peptide_id]
for group_id in parse.splitter(str(scan['protein group ids'])):
match = {
'sequence': scan['sequence'],
'spectrum': get_labeled_spectrum(scan),
'modifications': get_modifications(scan),
'attr' : {
'modified_sequence': mod_seq,
'mq_scan_id': scan_id,
'evidence_id': evidence_id,
'is_unique': peptide['unique (groups)'] == 'yes',
}
}
if scan['pep'] > cutoff_expect:
continue
match['intensity'] = parse_proteins.calc_minus_log_intensity(
scan['pep'], great_expect, cutoff_expect)
transfer_attrs(scan, match['attr'], scan_parse_list)
transfer_attrs(evidence, match['attr'], evidence_parse_list)
transfer_attrs(peptide, match['attr'], peptide_parse_list)
change_key(match['attr'], 'scan number', 'scan_id')
change_key(match['attr'], 'retention time', 'retention_time')
protein = protein_by_group_id[int(group_id)]
i_source = i_sources[evidence['raw file']]
protein['sources'][i_source]['matches'].append(match)
parse_proteins.count_matches(proteins)
parse_proteins.delete_empty_proteins(proteins)
return proteins, sources
def get_proteins_and_sources(
protein_groups_fname,
psm_fname,
modifications_fname=None,
q_good=0.0,
q_cutoff=10):
is_debug = logger.root.level <= logging.DEBUG
dump_dir = os.path.dirname(protein_groups_fname)
modification_table = {}
if modifications_fname:
modification_table = read_modification_dict(modifications_fname)
proteins = {}
dict_dump_writer = parse.DictListWriter(is_debug, os.path.join(dump_dir, 'protein_groups.dump'))
for i_group, protein_group in enumerate(parse.read_tsv(protein_groups_fname)):
protein = make_protein(i_group, protein_group)
proteins[protein['attr']['seqid']] = protein
dict_dump_writer.dump_dict(protein_group)
dict_dump_writer.close()
protein_by_seqid = {}
for seqid in proteins:
protein = proteins[seqid]
protein_by_seqid[seqid] = protein
for alt_seqid in protein['attr']['other_seqids']:
protein_by_seqid[alt_seqid] = protein
dict_dump_writer = parse.DictListWriter(is_debug, os.path.join(dump_dir, 'peptides.dump'))
n_match = 0
n_match_assigned = 0
i_source_from_source = {}
sources = []
for psm in parse.read_tsv(psm_fname):
dict_dump_writer.dump_dict(psm)
match = make_match(psm, modification_table)
match['intensity'] = parse_proteins.calc_intensity(
match['attr']['q_value'], q_good, q_cutoff)
if match['attr']['q_value'] > q_cutoff:
continue
peptide_sequence = match['sequence']
n_match += 1
protein = None
descriptions = psm['protein description'].split(' / ')
peptide_seqids = [d.split()[0] for d in descriptions]
for peptide_seqid in peptide_seqids:
if peptide_seqid in protein_by_seqid:
test_protein = protein_by_seqid[peptide_seqid]
sequence = protein_by_seqid[peptide_seqid]['sequence']
if peptide_sequence in sequence:
protein = test_protein
break
else:
logger.debug("Couldn't find protein for %s" % (peptide_sequence))
continue
match['i'] = sequence.find(peptide_sequence)
n_match_assigned += 1
i_source = get_i_source(proteins, sources, psm['filename'])
protein['sources'][i_source]['matches'].append(match)
dict_dump_writer.close()
dump = os.path.join(dump_dir, 'proteins.dump')
if logger.root.level <= logging.DEBUG:
logger.debug('Dumping proteins data structure to ' + dump)
parse.save_data_dict(proteins, dump)
logger.info("Assigned {}/{} of PSMs.tsv to protein_groups.tsv".format(n_match_assigned, n_match))
return proteins, sources
def read(in_dir): peptides = parse.read_tsv(os.path.join(in_dir, 'peptides.txt')) scans = parse.read_tsv(os.path.join(in_dir, 'msms.txt')) protein_groups = parse.read_tsv(os.path.join(in_dir, 'proteinGroups.txt')) evidence = parse.read_tsv(os.path.join(in_dir, 'evidence.txt')) return peptides, scans, protein_groups, evidence
def get_proteins_and_sources(in_dir, is_leu_ile_isomeric=False):
evidence_fname = os.path.join(in_dir, "evidence.txt")
logger.info("Loading evidence file: " + evidence_fname)
evidence_iter = parse.read_tsv(evidence_fname)
evidence_dict = {int(e["id"]): e for e in evidence_iter}
sources_set = set(e["raw file"] for e in evidence_dict.values())
sources = [str(s) for s in sorted(sources_set)]
i_sources = {source: k for k, source in enumerate(sources)}
protein_group_fname = os.path.join(in_dir, "proteinGroups.txt")
logger.info("Loading protein groups: " + protein_group_fname)
proteins = {}
protein_by_group_id = {}
for protein_group in parse.read_tsv(protein_group_fname):
group_id = protein_group["id"]
protein = {
"description": "",
"attr": {"group_id": group_id, "other_seqids": []},
"sources": [{"peptides": []} for k in range(len(i_sources))],
}
transfer_attrs(protein_group, protein["attr"], protein_parse_list)
seqids = parse.splitter(protein_group["protein ids"])
proteins[seqids[0]] = protein
protein["attr"]["seqid"] = seqids[0]
protein["attr"]["other_seqids"] = seqids[1:]
protein_by_group_id[group_id] = protein
peptides_fname = os.path.join(in_dir, "peptides.txt")
logger.info("Loading peptides file: " + peptides_fname)
peptides_iter = parse.read_tsv(peptides_fname)
peptides = {int(p["id"]): p for p in peptides_iter}
scans_fname = os.path.join(in_dir, "msms.txt")
logger.info("Loading scans and matching: " + scans_fname)
i_scan = 0
for scan in parse.read_tsv(scans_fname):
scan_id = int(scan["id"])
i_scan += 1
if i_scan % 5000 == 0:
logger.info("{} scans processed".format(i_scan))
evidence_id = int(scan["evidence id"])
evidence = evidence_dict[evidence_id]
peptide_id = int(scan["peptide id"])
peptide = peptides[peptide_id]
for group_id in parse.splitter(str(scan["protein group ids"])):
new_peptide = {
"sequence": scan["sequence"],
"spectrum": get_labeled_spectrum(scan),
"attr": {"modifications": [], "mq_scan_id": scan_id, "is_unique": peptide["unique (groups)"] == "yes"},
}
transfer_attrs(scan, new_peptide["attr"], scan_parse_list)
transfer_attrs(evidence, new_peptide["attr"], evidence_parse_list)
transfer_attrs(peptide, new_peptide["attr"], peptide_parse_list)
change_key(new_peptide["attr"], "scan number", "scan_id")
change_key(new_peptide["attr"], "retention time", "retention_time")
protein = protein_by_group_id[int(group_id)]
i_source = i_sources[evidence["raw file"]]
protein["sources"][i_source]["peptides"].append(new_peptide)
parse_proteins.count_peptides(proteins)
return proteins, sources
