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annotation.py
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annotation.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import itertools
import gzip
import sqlite3
from collections import OrderedDict
from urllib.parse import urlparse
import requests
import difflib
import pandas as pd
import numpy as np
import networkx as nx
from pyteomics import mass as pyteomics_mass
from beamspy.in_out import read_molecular_formulae
from beamspy.in_out import read_compounds
from beamspy.auxiliary import nist_database_to_pyteomics
from beamspy.auxiliary import composition_to_string
_sql_create_table_isotopes_ = """
CREATE TABLE isotopes (
peak_id_a TEXT DEFAULT NULL,
peak_id_b TEXT DEFAULT NULL,
label_a TEXT DEFAULT NULL,
label_b TEXT DEFAULT NULL,
atoms REAL DEFAULT NULL,
exact_mass_diff REAL DEFAULT NULL,
ppm_error REAL DEFAULT NULL,
charge INT DEFAULT 1,
PRIMARY KEY (peak_id_a, peak_id_b, label_a, label_b));
"""
_sql_create_table_neutral_losses_ = """
CREATE TABLE neutral_losses (
peak_id_a TEXT DEFAULT NULL,
peak_id_b TEXT DEFAULT NULL,
label TEXT DEFAULT NULL,
exact_mass_diff REAL DEFAULT NULL,
ppm_error REAL DEFAULT NULL,
PRIMARY KEY (peak_id_a, peak_id_b, label));
"""
def calculate_mz_tolerance(mass, ppm):
min_tol = mass - (mass * 0.000001 * ppm)
max_tol = mass + (mass * 0.000001 * ppm)
return min_tol, max_tol
def calculate_rt_tolerance(rt, rt_tol):
return rt - rt_tol, rt + rt_tol
def calculate_ppm_error(mass, theo_mass):
return float(mass - theo_mass) / (theo_mass * 0.000001)
def _remove_elements_from_compositions(records, keep):
path_nist_database = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data', 'nist_database.txt')
nist_database = nist_database_to_pyteomics(path_nist_database)
elements = [e for e in nist_database if e not in keep]
for record in records:
for e in elements:
if "composition" in record:
record["composition"].pop(e, None)
else:
record.pop(e, None)
return records
def _flatten_composition(records):
for record in records:
record.update(record["composition"])
del record["composition"]
return records
def _prep_lib(lib):
lib_pairs = []
if isinstance(lib, OrderedDict):
combs = list(itertools.combinations(lib, 2))
for pair in combs:
if lib[pair[0]]["charge"] == lib[pair[1]]["charge"]:
if lib[pair[0]]["mass"] < lib[pair[1]]["mass"]:
# print("yes", lib[pair[0]]["mass"], lib[pair[1]]["mass"], lib[pair[0]]["mass"] < lib[pair[1]]["mass"])
lib_pairs.append(OrderedDict([(pair[0], {"mass": lib[pair[0]]["mass"], "charge": lib[pair[0]]["charge"]}),
(pair[1], {"mass": lib[pair[1]]["mass"], "charge": lib[pair[1]]["charge"]})]))
else:
lib_pairs.append(OrderedDict([(pair[1], {"mass": lib[pair[1]]["mass"], "charge": lib[pair[1]]["charge"]}),
(pair[0], {"mass": lib[pair[0]]["mass"], "charge": lib[pair[0]]["charge"]})]))
elif lib[pair[0]]["charge"] > lib[pair[1]]["charge"]:
lib_pairs.append(OrderedDict([(pair[0], {"mass": lib[pair[0]]["mass"], "charge": lib[pair[0]]["charge"]}),
(pair[1], {"mass": lib[pair[1]]["mass"], "charge": lib[pair[1]]["charge"]})]))
else:
lib_pairs.append(OrderedDict([(pair[1], {"mass": lib[pair[1]]["mass"], "charge": lib[pair[1]]["charge"]}),
(pair[0], {"mass": lib[pair[0]]["mass"], "charge": lib[pair[0]]["charge"]})]))
#lib_pairs = sorted(lib_pairs, key=lambda pair: (list(pair.items())[0][1]["mass"] - list(pair.items())[1][1]["mass"]), reverse=True)
return lib_pairs
elif isinstance(lib, list) and isinstance(lib[0], OrderedDict):
if "mass_difference" in lib[0]:
return sorted(lib, key=lambda d: d["mass_difference"], reverse=True)
else:
raise ValueError("Format library incorrect")
#else:
# return sorted(lib_pairs, key=lambda pair: (list(pair.items())[0][1]["mass"] - list(pair.items())[1][1]["mass"]), reverse=True)
else:
raise ValueError("Incorrect format for library: {}".format(type(lib)))
def _annotate_artifacts(peaklist, diff=0.02):
n = peaklist.iloc[:, 1]
for i in range(n):
for j in range(i + 1, n):
mz_diff = peaklist.iloc[i,1] - peaklist.iloc[j,1]
ppm_error = calculate_ppm_error(peaklist.iloc[i,1], peaklist.iloc[j,1])
if abs(mz_diff) < diff:
yield i, j, mz_diff, ppm_error
def _check_tolerance(mz_x, mz_y, lib_pair, ppm, charge):
min_tol_a, max_tol_a = calculate_mz_tolerance(mz_x, ppm)
min_tol_b, max_tol_b = calculate_mz_tolerance(mz_y, ppm)
if "mass_difference" in lib_pair.keys():
min_tol_b = min_tol_b - (lib_pair["mass_difference"])
max_tol_b = max_tol_b - (lib_pair["mass_difference"])
elif "mass" in list(lib_pair.items())[0][1]:
charge_a = list(lib_pair.items())[0][1]["charge"]
charge_b = list(lib_pair.items())[1][1]["charge"]
mass_a = list(lib_pair.items())[0][1]["mass"]
mass_b = list(lib_pair.items())[1][1]["mass"]
min_tol_a -= mass_a
max_tol_a -= mass_a
min_tol_b -= mass_b
max_tol_b -= mass_b
if charge_a > 1:
min_tol_a += (charge_a - 1) * (mz_x - mass_a)
max_tol_a += (charge_a - 1) * (mz_x - mass_a)
if charge_b > 1:
min_tol_b += (charge_b - 1) * (mz_y - mass_b)
max_tol_b += (charge_b - 1) * (mz_y - mass_b)
else:
raise ValueError("Incorrect format: {}".format(lib_pair))
#if min_tol_b > min_tol_a and min_tol_b > max_tol_a:
# return -1
# x1 <= mass <= x2
# y1 <= mass <= y2
# x1 <= y2 AND y1 <= x2
if min_tol_a < max_tol_b and min_tol_b < max_tol_a:
return 1
return 0
def _annotate_pairs_from_graph(G, ppm, lib_pairs, charge):
for e in G.edges(data=True):
mz_x = G.nodes[e[0]]["mz"]
mz_y = G.nodes[e[1]]["mz"]
for lib_pair in lib_pairs:
ct = _check_tolerance(mz_x, mz_y, lib_pair, ppm, charge)
if ct:
if "charge" in list(lib_pair.items())[0][1]:
charge_a = list(lib_pair.items())[0][1]["charge"]
charge_b = list(lib_pair.items())[1][1]["charge"]
elif charge:
charge_a = charge
charge_b = charge
else:
charge_a = 1
charge_b = 1
if "mass_difference" in lib_pair:
charge = lib_pair["charge"]
ppm_error = calculate_ppm_error(
mz_x,
mz_y - (lib_pair["mass_difference"]))
exact_mass_diff = lib_pair["mass_difference"]
else:
ppm_error = calculate_ppm_error(
(mz_x - list(lib_pair.items())[0][1]["mass"]) * charge_a,
(mz_y - list(lib_pair.items())[1][1]["mass"]) * charge_b)
exact_mass_diff = list(lib_pair.items())[1][1]["mass"] - list(lib_pair.items())[0][1]["mass"]
yield OrderedDict([("peak_id_a", e[0]), ("peak_id_b", e[1]),
("label_a", list(lib_pair.keys())[0]),
("label_b", list(lib_pair.keys())[1]),
('charge_a', charge_a),
('charge_b', charge_b),
('exact_mass_diff', exact_mass_diff),
('ppm_error', round(ppm_error, 2))])
def _annotate_pairs_from_peaklist(peaklist, ppm, lib_pairs, charge):
n = len(peaklist.iloc[:, 1])
for i in range(n):
for j in range(i + 1, n):
for lib_pair in lib_pairs:
ct = _check_tolerance(peaklist.iloc[i, 1], peaklist.iloc[j, 1], lib_pair, ppm, charge)
if ct:
if "charge" in list(lib_pair.items())[0][1]:
charge_a = list(lib_pair.items())[0][1]["charge"]
charge_b = list(lib_pair.items())[1][1]["charge"]
elif charge:
charge_a = charge
charge_b = charge
else:
charge_a = 1
charge_b = 1
if "mass_difference" in lib_pair:
ppm_error = calculate_ppm_error(
peaklist.iloc[i, 1],
peaklist.iloc[j, 1] - lib_pair["mass_difference"])
exact_mass_diff = lib_pair["mass_difference"]
charge_a = lib_pair["charge"]
charge_b = lib_pair["charge"]
else:
ppm_error = calculate_ppm_error(
(peaklist.iloc[i, 1] - list(lib_pair.items())[0][1]["mass"]) * charge_a,
(peaklist.iloc[j, 1] - list(lib_pair.items())[1][1]["mass"]) * charge_b)
exact_mass_diff = list(lib_pair.items())[1][1]["mass"] - list(lib_pair.items())[0][1]["mass"]
yield OrderedDict([("peak_id_a", peaklist.iloc[i,0]), ("peak_id_b", peaklist.iloc[j,0]),
("label_a", list(lib_pair.keys())[0]),
("label_b", list(lib_pair.keys())[1]),
('charge_a', charge_a),
('charge_b', charge_b),
('exact_mass_diff', exact_mass_diff),
('ppm_error', round(ppm_error, 2))])
class DbCompoundsMemory:
def __init__(self, filename, lib_adducts=[]):
self.filename = filename
self.lib_adducts = lib_adducts
records = read_compounds(self.filename, lib_adducts=self.lib_adducts)
if "retention_time" in list(records[0].keys()):
rt_column = "retention_time REAL DEFAULT NULL,"
else:
rt_column = ""
self.conn = sqlite3.connect(":memory:")
self.cursor = self.conn.cursor()
self.cursor.execute("""CREATE TABLE COMPOUNDS(
compound_id TEXT PRIMARY KEY NOT NULL,
compound_name TEXT,
exact_mass REAL,
{}
C INTEGER DEFAULT 0,
H INTEGER DEFAULT 0,
N INTEGER DEFAULT 0,
O INTEGER DEFAULT 0,
P INTEGER DEFAULT 0,
S INTEGER DEFAULT 0,
CHNOPS INTEGER DEFAULT NULL,
molecular_formula TEXT DEFAULT NULL,
adduct TEXT DEFAULT NULL
);""".format(rt_column))
records = _remove_elements_from_compositions(records, keep=["C", "H", "N", "O", "P", "S"])
records = _flatten_composition(records)
for record in records:
columns = ",".join(map(str, list(record.keys())))
qms = ', '.join(['?'] * len(record.values()))
query = """insert into COMPOUNDS ({}) values ({})""".format(columns, qms)
self.cursor.execute(query, list(record.values()))
self.cursor.execute("""CREATE INDEX IDX_EXACT_MASS ON COMPOUNDS (exact_mass);""")
self.conn.commit()
self.cursor.execute("select * from COMPOUNDS")
def select_compounds(self, min_tol, max_tol, min_rt=None, max_rt=None):
col_names = ["compound_id", "compound_name", "exact_mass", "C", "H", "N", "O", "P", "S", "CHNOPS", "molecular_formula", "adduct"]
if min_rt:
col_names.insert(3, "retention_time")
sql_rt = " and retention_time >= {} and retention_time <= {}".format(min_rt, max_rt)
else:
sql_rt = ""
sql_str = """SELECT {} FROM COMPOUNDS WHERE exact_mass >= {} and exact_mass <= {}{}""".format(",".join(map(str, col_names)), min_tol, max_tol, sql_rt)
self.cursor.execute(sql_str)
return [OrderedDict(zip(col_names, list(record))) for record in self.cursor.fetchall()]
def close(self):
self.conn.close()
class DbMolecularFormulaeMemory:
def __init__(self, filename):
self.filename = filename
self.conn = sqlite3.connect(":memory:")
self.cursor = self.conn.cursor()
self.cursor.execute("""CREATE TABLE MF(
exact_mass REAL,
C INTEGER DEFAULT 0,
H INTEGER DEFAULT 0,
N INTEGER DEFAULT 0,
O INTEGER DEFAULT 0,
P INTEGER DEFAULT 0,
S INTEGER DEFAULT 0,
CHNOPS INTEGER DEFAULT NULL,
HC INTEGER DEFAULT NULL,
NOPSC INTEGER DEFAULT NULL,
lewis INTEGER DEFAULT NULL,
senior INTEGER DEFAULT NULL,
double_bond_equivalents REAL,
primary key (C,H,N,O,P,S,exact_mass)
);""")
records = read_molecular_formulae(self.filename)
records = _remove_elements_from_compositions(records, keep=["C", "H", "N", "O", "P", "S"])
records = _flatten_composition(records)
for record in records:
columns = ",".join(map(str, list(record.keys())))
qms = ', '.join(['?'] * len(record.values()))
query = """insert into mf ({}) values ({})""".format(columns, qms)
self.cursor.execute(query, list(record.values()))
self.cursor.execute("""CREATE INDEX IDX_EXACT_MASS ON MF (exact_mass);""")
self.cursor.execute("""CREATE INDEX IDX_EXACT_MASS_RULES ON MF (exact_mass, HC, NOPSC, LEWIS, SENIOR);""")
self.conn.commit()
def select_mf(self, min_tol, max_tol, rules):
if rules:
sql_filters = " and lewis = 1 and senior = 1 and HC = 1 and NOPSC = 1"
else:
sql_filters = ""
col_names = ["exact_mass", "C", "H", "N", "O", "P", "S",
"double_bond_equivalents", "LEWIS", "SENIOR", "HC", "NOPSC"]
self.cursor.execute("""SELECT exact_mass, C, H, N, O, P, S,
double_bond_equivalents, LEWIS, SENIOR, HC, NOPSC
from mf where exact_mass >= {} and exact_mass <= {}{}
""".format(min_tol, max_tol, sql_filters))
return [OrderedDict(zip(col_names, list(record))) for record in self.cursor.fetchall()]
def close(self):
self.conn.close()
def annotate_adducts(source, db_out, ppm, lib, add=False):
conn = sqlite3.connect(db_out)
cursor = conn.cursor()
if not add:
cursor.execute("DROP TABLE IF EXISTS adduct_pairs")
cursor.execute("""CREATE TABLE adduct_pairs (
peak_id_a TEXT DEFAULT NULL,
peak_id_b TEXT DEFAULT NULL,
label_a TEXT DEFAULT NULL,
label_b TEXT DEFAULT NULL,
charge_a INTEGER DEFAULT NULL,
charge_b INTEGER DEFAULT NULL,
exact_mass_diff REAL DEFAULT NULL,
ppm_error REAL DEFAULT NULL,
PRIMARY KEY (peak_id_a, peak_id_b, label_a, label_b));""")
lib_pairs = _prep_lib(lib.lib)
if isinstance(source, nx.classes.digraph.DiGraph):
source = list(source.subgraph(c) for c in nx.weakly_connected_components(source))
if isinstance(source, list) and len(source) > 0 and isinstance(source[0], nx.classes.digraph.DiGraph):
for i, graph in enumerate(source):
for assignment in _annotate_pairs_from_graph(graph, lib_pairs=lib_pairs, ppm=ppm, charge=None):
cursor.execute("""INSERT OR REPLACE into adduct_pairs (peak_id_a, peak_id_b,
label_a, label_b,
charge_a, charge_b,
exact_mass_diff, ppm_error)
values (?,?,?,?,?,?,?,?)""", (str(assignment["peak_id_a"]), str(assignment["peak_id_b"]),
assignment["label_a"], assignment["label_b"],
assignment["charge_a"], assignment["charge_b"],
float(assignment["exact_mass_diff"]),
float(assignment["ppm_error"])))
elif isinstance(source, pd.core.frame.DataFrame):
for assignment in _annotate_pairs_from_peaklist(source, lib_pairs=lib_pairs, ppm=ppm, charge=None):
cursor.execute("""INSERT OR REPLACE into adduct_pairs (peak_id_a, peak_id_b,
label_a, label_b,
charge_a, charge_b,
exact_mass_diff, ppm_error)
values (?,?,?,?,?,?,?,?)""", (assignment["peak_id_a"], assignment["peak_id_b"],
assignment["label_a"], assignment["label_b"],
assignment["charge_a"], assignment["charge_b"],
float(assignment["exact_mass_diff"]),
float(assignment["ppm_error"])))
cursor.execute("""CREATE INDEX IDX_peak_id_a ON adduct_pairs (peak_id_a);""")
cursor.execute("""CREATE INDEX IDX_peak_id_b ON adduct_pairs (peak_id_b);""")
conn.commit()
conn.close()
return
def annotate_isotopes(source, db_out, ppm, lib):
conn = sqlite3.connect(db_out)
cursor = conn.cursor()
cursor.execute("DROP TABLE IF EXISTS isotopes")
cursor.execute(_sql_create_table_isotopes_)
lib_pairs = _prep_lib(lib.lib)
abundances = {}
for pair in lib.lib:
abundances[list(pair.items())[0][0]] = list(pair.items())[0][1]
abundances[list(pair.items())[1][0]] = list(pair.items())[1][1]
if isinstance(source, nx.classes.digraph.DiGraph):
source = list(source.subgraph(c) for c in nx.weakly_connected_components(source))
if isinstance(source, list) and len(source) > 0 and isinstance(source[0], nx.classes.digraph.DiGraph):
for graph in source:
peaklist = graph.nodes(data=True)
for assignment in _annotate_pairs_from_graph(G=graph, lib_pairs=lib_pairs, ppm=ppm, charge=None):
if abundances[assignment["label_a"]]["abundance"] < abundances[assignment["label_b"]]["abundance"]:
# Lithium
y = abundances[assignment["label_a"]]['abundance'] * peaklist[assignment["peak_id_b"]]["intensity"]
x = 100.0 * peaklist[assignment["peak_id_a"]]["intensity"]
else:
y = 100.0 * peaklist[assignment["peak_id_b"]]["intensity"]
x = abundances[assignment["label_b"]]['abundance'] * peaklist[assignment["peak_id_a"]]["intensity"]
if x == 0.0 or y == 0.0:
atoms = None
elif abundances[assignment["label_a"]]["abundance"] < abundances[assignment["label_b"]]["abundance"]:
atoms = x/y
else:
atoms = y/x
cursor.execute("""insert into isotopes (peak_id_a, peak_id_b, label_a, label_b,
atoms, exact_mass_diff, ppm_error, charge)
values (?,?,?,?,?,?,?,?)""", (str(assignment["peak_id_a"]), str(assignment["peak_id_b"]),
assignment["label_a"], assignment["label_b"], float(atoms),
float(assignment["exact_mass_diff"]), float(assignment["ppm_error"]), assignment["charge_a"]))
elif isinstance(source, pd.core.frame.DataFrame):
for assignment in _annotate_pairs_from_peaklist(peaklist=source, lib_pairs=lib_pairs, ppm=ppm, charge=None):
if abundances[assignment["label_a"]]["abundance"] < abundances[assignment["label_b"]]["abundance"]:
# Lithium
y = abundances[assignment["label_a"]]["abundance"] * source.loc[source['name'] == assignment["peak_id_b"]]["intensity"].iloc[0]
x = 100.0 * source.loc[source['name'] == assignment["peak_id_a"]]["intensity"].iloc[0]
else:
y = 100.0 * source.loc[source['name'] == assignment["peak_id_b"]]["intensity"].iloc[0]
x = abundances[assignment["label_b"]]["abundance"] * source.loc[source['name'] == assignment["peak_id_a"]]["intensity"].iloc[0]
if x == 0.0 or y == 0.0:
atoms = None
elif abundances[assignment["label_a"]]["abundance"] < abundances[assignment["label_b"]]["abundance"]:
atoms = x/y
else:
atoms = y/x
cursor.execute("""insert into isotopes (peak_id_a, peak_id_b, label_a, label_b,
atoms, exact_mass_diff, ppm_error, charge)
values (?,?,?,?,?,?,?,?)""", (assignment["peak_id_a"], assignment["peak_id_b"],
assignment["label_a"], assignment["label_b"], atoms,
float(assignment["exact_mass_diff"]), assignment["ppm_error"], assignment["charge_a"]))
cursor.execute("""CREATE INDEX IDX_isotopes_peak_id_a ON isotopes (peak_id_a);""")
cursor.execute("""CREATE INDEX IDX_isotopes_peak_id_b ON isotopes (peak_id_b);""")
conn.commit()
conn.close()
return
def annotate_oligomers(source, db_out, ppm, lib, maximum=3):
conn = sqlite3.connect(db_out)
cursor = conn.cursor()
cursor.execute("DROP TABLE IF EXISTS oligomers")
cursor.execute("""CREATE TABLE oligomers (
peak_id_a TEXT DEFAULT NULL,
peak_id_b TEXT DEFAULT NULL,
mz_a REAL DEFAULT NULL,
mz_b REAL DEFAULT NULL,
label_a TEXT DEFAULT NULL,
label_b TEXT DEFAULT NULL,
charge_a INTEGER DEFAULT NULL,
charge_b INTEGER DEFAULT NULL,
mz_ratio REAL DEFAULT NULL,
ppm_error REAL DEFAULT NULL,
PRIMARY KEY (peak_id_a, peak_id_b, label_a, label_b));""")
if isinstance(source, nx.classes.digraph.DiGraph):
source = list(source.subgraph(c) for c in nx.weakly_connected_components(source))
if isinstance(source, list) and len(source) > 0 and isinstance(source[0], nx.classes.digraph.DiGraph):
for graph in source:
for n in graph.nodes():
neighbors = list(graph.neighbors(n))
for d in range(1, maximum):
for nn in neighbors:
mz_x = graph.nodes[n]["mz"]
mz_y = graph.nodes[nn]["mz"]
if mz_x < mz_y:
for adduct in lib.lib.keys():
if lib.lib[adduct]["charge"] > 1:
continue
min_tol_a, max_tol_a = calculate_mz_tolerance(mz_x + ((mz_x - lib.lib[adduct]["mass"]) * d), ppm)
min_tol_b, max_tol_b = calculate_mz_tolerance(mz_y, ppm)
if (min_tol_b > max_tol_a and max_tol_b > max_tol_a):# or (min_tol_a < min_tol_b and max_tol_a < min_tol_b):
#print(source.iloc[i][1], source.iloc[j][1], adduct)
break
min_tol_a -= lib.lib[adduct]["mass"]
max_tol_a -= lib.lib[adduct]["mass"]
min_tol_b -= lib.lib[adduct]["mass"]
max_tol_b -= lib.lib[adduct]["mass"]
if min_tol_a < max_tol_b and min_tol_b < max_tol_a:
a = (mz_x - lib.lib[adduct]["mass"]) + (mz_x - lib.lib[adduct]["mass"]) * d
b = mz_y - lib.lib[adduct]["mass"]
ratio = (mz_y - lib.lib[adduct]["mass"]) / (mz_x - lib.lib[adduct]["mass"])
ppm_error = calculate_ppm_error(a, b)
if "M" in adduct:
adduct_oligo = adduct.replace("M", "{}M".format(int(round(ratio))))
else:
adduct_oligo = "{}{}".format(int(round(ratio)), adduct)
cursor.execute("""insert into oligomers (peak_id_a, peak_id_b, mz_a, mz_b, label_a, label_b, charge_a, charge_b, mz_ratio, ppm_error)
values (?,?,?,?,?,?,?,?,?,?)""", (n, nn, mz_x, mz_y, adduct, adduct_oligo,
lib.lib[adduct]["charge"], lib.lib[adduct]["charge"], round(ratio, 2), round(ppm_error, 2)))
elif isinstance(source, pd.core.frame.DataFrame):
n = len(source.iloc[:,0])
for adduct in lib.lib.keys():
if lib.lib[adduct]["charge"] > 1:
continue
for i in range(n):
for d in range(1, maximum):
for j in range(i + 1, n):
min_tol_a, max_tol_a = calculate_mz_tolerance(source.iloc[i][1] + ((source.iloc[i][1] - lib.lib[adduct]["mass"]) * d), ppm)
min_tol_b, max_tol_b = calculate_mz_tolerance(source.iloc[j][1], ppm)
if (min_tol_b > max_tol_a and max_tol_b > max_tol_a):# or (min_tol_a < min_tol_b and max_tol_a < min_tol_b):
#print(source.iloc[i][1], source.iloc[j][1], adduct)
break
min_tol_a -= lib.lib[adduct]["mass"]
max_tol_a -= lib.lib[adduct]["mass"]
min_tol_b -= lib.lib[adduct]["mass"]
max_tol_b -= lib.lib[adduct]["mass"]
if min_tol_a < max_tol_b and min_tol_b < max_tol_a:
a = (source.iloc[i][1] - lib.lib[adduct]["mass"]) + (source.iloc[i][1] - lib.lib[adduct]["mass"]) * d
b = source.iloc[j][1] - lib.lib[adduct]["mass"]
ratio = (source.iloc[j][1] - lib.lib[adduct]["mass"]) / (source.iloc[i][1] - lib.lib[adduct]["mass"])
ppm_error = calculate_ppm_error(a, b)
if "M" in adduct:
adduct_oligo = adduct.replace("M", "{}M".format(int(round(ratio))))
else:
adduct_oligo = "{}{}".format(int(round(ratio)), adduct)
cursor.execute("""insert into oligomers (peak_id_a, peak_id_b, mz_a, mz_b, label_a, label_b, charge_a, charge_b, mz_ratio, ppm_error)
values (?,?,?,?,?,?,?,?,?,?)""", (source.iloc[i][0], source.iloc[j][0], source.iloc[i][1], source.iloc[j][1], adduct, adduct_oligo,
lib.lib[adduct]["charge"], lib.lib[adduct]["charge"], round(ratio, 2), round(ppm_error, 2)))
cursor.execute("""CREATE INDEX IDX_oligomers_peak_id_a ON oligomers (peak_id_a);""")
cursor.execute("""CREATE INDEX IDX_oligomers_peak_id_b ON oligomers (peak_id_b);""")
conn.commit()
conn.close()
return
def annotate_neutral_losses(source, db_out, ppm, lib):
conn = sqlite3.connect(db_out)
cursor = conn.cursor()
cursor.execute("DROP TABLE IF EXISTS neutral_losses")
cursor.execute(_sql_create_table_neutral_losses_)
if isinstance(source, nx.classes.digraph.DiGraph):
source = list(source.subgraph(c) for c in nx.weakly_connected_components(source))
if isinstance(source, list) and len(source) > 0 and isinstance(source[0], nx.classes.digraph.DiGraph):
for graph in source:
for e in graph.edges(data=True):
mz_x = graph.nodes[e[0]]["mz"]
mz_y = graph.nodes[e[1]]["mz"]
for nl in lib.lib:
ct = _check_tolerance(mz_x, mz_y, nl, ppm, charge=1)
if ct:
ppm_error = calculate_ppm_error(
mz_x, mz_y - nl["mass_difference"])
cursor.execute("""insert into neutral_losses (peak_id_a, peak_id_b, label,
exact_mass_diff, ppm_error)
values (?,?,?,?,?)""", (e[0], e[1],
nl["label"], nl["mass_difference"], ppm_error))
elif isinstance(source, pd.core.frame.DataFrame):
n = len(source.iloc[:, 1])
for i in range(n):
for j in range(i + 1, n):
for nl in lib.lib:
ct = _check_tolerance(source.iloc[i, 1], source.iloc[j, 1], nl, ppm, charge=1)
if ct:
ppm_error = calculate_ppm_error(
source.iloc[i, 1],
source.iloc[j, 1] - nl["mass_difference"])
cursor.execute("""insert into neutral_losses (peak_id_a, peak_id_b, label,
exact_mass_diff, ppm_error)
values (?,?,?,?,?)""", (source.iloc[i, 0], source.iloc[j, 0],
nl["label"], nl["mass_difference"], ppm_error))
cursor.execute("""CREATE INDEX IDX_nls_peak_id_a ON neutral_losses (peak_id_a);""")
cursor.execute("""CREATE INDEX IDX_nls_peak_id_b ON neutral_losses (peak_id_b);""")
conn.commit()
conn.close()
return
def annotate_artifacts(source, db_out, diff):
conn = sqlite3.connect(db_out)
cursor = conn.cursor()
cursor.execute("DROP TABLE IF EXISTS artifacts")
cursor.execute("""CREATE TABLE artifacts (
peak_id_a TEXT DEFAULT NULL,
peak_id_b TEXT DEFAULT NULL,
mz_diff REAL DEFAULT NULL,
ppm_error REAL DEFAULT NULL,
PRIMARY KEY (peak_id_a, peak_id_b));""")
if isinstance(source, nx.classes.digraph.DiGraph):
source = list(source.subgraph(c) for c in nx.weakly_connected_components(source))
if (isinstance(source, list) or isinstance(source, np.ndarray)) and isinstance(source[0], nx.classes.graph.Graph):
for graph in source:
peaklist = graph.nodes(data=True)
for assignment in _annotate_artifacts(peaklist, diff=diff):
cursor.execute("""insert into artifacts (peak_id_a, peak_id_b, mz_diff, ppm_error)
values (?,?,?,?)""", (assignment["peak_id_a"], assignment["peak_id_b"], assignment["label_a"], assignment["label_b"]))
elif isinstance(source, pd.core.frame.DataFrame):
for assignment in _annotate_artifacts(source, diff=diff):
cursor.execute("""insert into artifacts (peak_id_a, peak_id_b, mz_diff, ppm_error)
values (?,?,?,?)""", (assignment["peak_id_a"], assignment["peak_id_b"], assignment["label_a"], assignment["label_b"]))
conn.commit()
return
def _select_unions_peak_patterns(cursor):
cursor.execute("SELECT name FROM sqlite_master WHERE type='table'")
tables = cursor.fetchall()
# Prepare (empty) sqlite tables if not exist to make union queries more consistent
if ("isotopes",) not in tables:
cursor.execute(_sql_create_table_isotopes_.replace("CREATE", "CREATE TEMP"))
if ("neutral_losses",) not in tables:
cursor.execute(_sql_create_table_neutral_losses_.replace("CREATE", "CREATE TEMP"))
records = []
sql_unions = []
excl_ids_pp = []
for t in ["adduct_pairs", "oligomers"]:
if (t,) in tables:
if t == "oligomers":
col_mz_ratio = "ap.mz_ratio AS mz_ratio"
else:
col_mz_ratio = "1 AS mz_ratio"
sql_str = """
SELECT ap.peak_id_a AS peak_id_a,
iso.peak_id_b AS peak_id_b,
nl_ap.peak_id_a AS peak_id_a_nl,
nl_ap.peak_id_b AS peak_id_aa_nl,
nl_iso.peak_id_a AS peak_id_b_nl,
nl_iso.peak_id_b AS peak_id_bb_nl,
ap.label_a AS adduct_label,
IFNULL(ap.peak_id_b = iso.peak_id_b, 0) AS flag,
iso.label_a AS iso_label_a,
iso.label_b AS iso_label_b,
ap.charge_a AS ap_charge,
iso.charge AS iso_charge,
1 AS mz_ratio,
IFNULL(iso.exact_mass_diff, 0.0) AS iso_exact_mass_diff,
IFNULL(nl_ap.exact_mass_diff, 0.0) AS nl_exact_mass_diff,
nl_ap.label AS nl_label
FROM {} AS ap
LEFT JOIN isotopes AS iso
ON ap.peak_id_a = iso.peak_id_a AND ap.charge_a = iso.charge
LEFT JOIN neutral_losses AS nl_ap
ON (ap.peak_id_a = nl_ap.peak_id_a OR ap.peak_id_a = nl_ap.peak_id_b)
LEFT JOIN neutral_losses AS nl_iso
ON (iso.peak_id_b = nl_iso.peak_id_a OR iso.peak_id_b = nl_iso.peak_id_b)
UNION
SELECT ap.peak_id_b AS peak_id_a,
iso.peak_id_b AS peak_id_b,
nl_ap.peak_id_a AS peak_id_a_nl,
nl_ap.peak_id_b AS peak_id_aa_nl,
nl_iso.peak_id_a AS peak_id_b_nl,
nl_iso.peak_id_b AS peak_id_bb_nl,
ap.label_b AS adduct_label,
0 AS flag,
iso.label_a AS iso_label_a,
iso.label_b AS iso_label_b,
ap.charge_b AS ap_charge,
iso.charge AS iso_charge,
{},
IFNULL(iso.exact_mass_diff, 0) AS iso_exact_mass_diff,
IFNULL(nl_ap.exact_mass_diff, 0) AS nl_exact_mass_diff,
nl_ap.label AS nl_label
FROM {} AS ap
LEFT JOIN isotopes AS iso
ON ap.peak_id_b = iso.peak_id_a AND ap.charge_b = iso.charge
LEFT JOIN neutral_losses AS nl_ap
ON (ap.peak_id_b = nl_ap.peak_id_a OR ap.peak_id_b = nl_ap.peak_id_b)
LEFT JOIN neutral_losses AS nl_iso
ON (iso.peak_id_b = nl_iso.peak_id_a OR iso.peak_id_b = nl_iso.peak_id_b)
""".format(t, col_mz_ratio, t)
sql_unions.append(sql_str)
excl_ids_pp.append("""SELECT peak_id_a FROM {} UNION SELECT peak_id_b FROM {}""".format(t, t))
cursor.execute(" UNION ".join(map(str, sql_unions)))
records.extend([dict(zip([c[0] for c in cursor.description], record)) for record in cursor.fetchall()])
if len(excl_ids_pp) > 0:
excl_ids_adducts_oligomers = " union ".join(map(str, excl_ids_pp))
sql_excl = """AND iso.peak_id_a NOT IN ({})
AND iso.peak_id_b NOT IN ({})""".format(excl_ids_adducts_oligomers, excl_ids_adducts_oligomers)
else:
sql_excl = ""
# WHERE (nl_ap.label = nl_iso.label
# OR IFNULL(nl_ap.label, nl_iso.label) is NOT NULL
# OR IFNULL(nl_ap.label, nl_iso.label) is NULL)
sql_str = """
SELECT iso.peak_id_a AS peak_id_a,
iso.peak_id_b AS peak_id_b,
nl_ap.peak_id_a AS peak_id_a_nl,
nl_ap.peak_id_b AS peak_id_aa_nl,
nl_iso.peak_id_a AS peak_id_b_nl,
nl_iso.peak_id_b AS peak_id_bb_nl,
NULL AS adduct_label,
0 AS flag,
iso.label_a AS iso_label_a,
iso.label_b AS iso_label_b,
NULL AS ap_charge,
iso.charge AS iso_charge,
1 AS mz_ratio,
IFNULL(iso.exact_mass_diff, 0.0) AS iso_exact_mass_diff,
IFNULL(nl_ap.exact_mass_diff, 0.0) AS nl_exact_mass_diff,
nl_ap.label AS nl_label
FROM isotopes AS iso
LEFT JOIN neutral_losses AS nl_ap
ON (iso.peak_id_a = nl_ap.peak_id_a OR iso.peak_id_a = nl_ap.peak_id_b)
LEFT JOIN neutral_losses AS nl_iso
ON (iso.peak_id_b = nl_iso.peak_id_a OR iso.peak_id_b = nl_iso.peak_id_b)
{}""".format(sql_excl)
cursor.execute(sql_str)
records.extend([dict(zip([c[0] for c in cursor.description], record)) for record in cursor.fetchall()])
excl_ids_pp.append("""SELECT peak_id_a FROM isotopes UNION SELECT peak_id_b FROM isotopes""")
excl_ids = " UNION ".join(map(str, excl_ids_pp))
sql_excl = """WHERE peak_id_a NOT IN ({})
AND peak_id_a_nl NOT IN ({})""".format(excl_ids, excl_ids)
sql_str = """
SELECT peak_id_a,
NULL AS peak_id_b,
peak_id_b AS peak_id_a_nl,
NULL AS peak_id_b_nl,
NULL AS adduct_label,
0 AS flag,
NULL AS iso_label_a,
NULL AS iso_label_b,
1 AS ap_charge,
1 AS iso_charge,
1 AS mz_ratio,
0.0 AS iso_exact_mass_diff,
exact_mass_diff AS nl_exact_mass_diff,
label AS nl_label
FROM neutral_losses
{}
UNION
SELECT peak_id_b AS peak_id_a,
NULL AS peak_id_b,
peak_id_a AS peak_id_a_nl,
NULL AS peak_id_b_nl,
NULL AS adduct_label,
0 AS flag,
NULL AS iso_label_a,
NULL AS iso_label_b,
1 AS ap_charge,
1 AS iso_charge,
1 AS mz_ratio,
0.0 AS iso_exact_mass_diff,
exact_mass_diff AS nl_exact_mass_diff,
label AS nl_label
FROM neutral_losses
{}""".format(sql_excl, sql_excl)
cursor.execute(sql_str)
records.extend([dict(zip([c[0] for c in cursor.description], record)) for record in cursor.fetchall()])
return records
def annotate_molecular_formulae(peaklist, lib_adducts, ppm, db_out, db_in="https://mfdb.bham.ac.uk", patterns=True, rules=True, max_mz=None):
conn = sqlite3.connect(db_out)
cursor = conn.cursor()
cursor.execute("DROP TABLE IF EXISTS molecular_formulae")
cursor.execute("""CREATE TABLE molecular_formulae (
id TEXT DEFAULT NULL,
mz REAL DEFAULT NULL,
exact_mass REAL DEFAULT NULL,
ppm_error REAL DEFAULT NULL,
adduct TEXT DEFAULT NULL,
isotope TEXT DEFAULT '',
neutral_loss TEXT DEFAULT '',
C INTEGER DEFAULT 0,
H INTEGER DEFAULT 0,
N INTEGER DEFAULT 0,
O INTEGER DEFAULT 0,
P INTEGER DEFAULT 0,
S INTEGER DEFAULT 0,
CHNOPS INTEGER DEFAULT NULL,
molecular_formula TEXT DEFAULT NULL,
HC INTEGER DEFAULT NULL,
NOPSC INTEGER DEFAULT NULL,
lewis INTEGER DEFAULT NULL,
senior INTEGER DEFAULT NULL,
double_bond_equivalents REAL DEFAULT NULL,
primary key (id, mz, molecular_formula, adduct, isotope, neutral_loss)
);""")
if os.path.isfile(db_in):
conn_mem = DbMolecularFormulaeMemory(db_in)
source = "sqlite"
max_mz = None
else:
source = "api"
url = '{}/api/formula/mass_range'.format(db_in)
url_test = '{}/api/formula/mass?mass=180.06339&tol=0.0&tol_unit=ppm&rules=1'.format(db_in)
o = urlparse(url)
if o.scheme != "http" and o.netloc != "mfdb.bham.ac.uk":
raise ValueError("No database or local db available")
else:
r = requests.get(url_test)
r.raise_for_status()
path_nist_database = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data', 'nist_database.txt')
nist_database = nist_database_to_pyteomics(path_nist_database)
def _select_mfs(source, peak_id, mz, ppm, adducts, isotope, neutral_loss, n_oligo, exact_mass_diff=0.0, rules=True):
min_mz, max_mz = calculate_mz_tolerance(mz, ppm)
mf_records = []
for adduct in adducts:
if mz - lib_adducts.lib[adduct]["mass"] > 0.5:
if source == "api":
params = {"lower": (min_mz - lib_adducts.lib[adduct]["mass"] - exact_mass_diff) *
lib_adducts.lib[adduct]["charge"] / n_oligo,
"upper": (max_mz - lib_adducts.lib[adduct]["mass"] - exact_mass_diff) *
lib_adducts.lib[adduct]["charge"] / n_oligo,
"rules": int(rules)}
response = requests.get(url, params=params)
records = response.json()["records"]
else:
records = conn_mem.select_mf((min_mz - lib_adducts.lib[adduct]["mass"] - exact_mass_diff) *
lib_adducts.lib[adduct]["charge"] / n_oligo,
(max_mz - lib_adducts.lib[adduct]["mass"] - exact_mass_diff) *
lib_adducts.lib[adduct]["charge"] / n_oligo, rules=rules)
for record in records:
record["id"] = peak_id
if "CHNOPS" not in record: # MFdb API specific
record["CHNOPS"] = True # MFdb API specific
if "rules" in record:
record.update(record["rules"])
del record["rules"]
if "atoms" in record:
record.update(record["atoms"])
del record["atoms"]
record["exact_mass"] = (record["exact_mass"] / lib_adducts.lib[adduct]["charge"] * n_oligo) + \
(float(lib_adducts.lib[adduct]["mass"]) + exact_mass_diff)
record["adduct"] = adduct
record["mz"] = mz
record["ppm_error"] = calculate_ppm_error(mz, record["exact_mass"])
comp = OrderedDict([(item, record[item]) for item in record if item in nist_database.keys()])
record["molecular_formula"] = composition_to_string(comp)
record["adduct"] = adduct
if isotope:
record["isotope"] = isotope
else:
record["isotope"] = ""
if neutral_loss:
record["neutral_loss"] = neutral_loss
else:
record["neutral_loss"] = ""
records = _remove_elements_from_compositions(records, keep=["C", "H", "N", "O", "P", "S"])
mf_records.extend(records)
return mf_records
rows = _select_unions_peak_patterns(cursor)
names_to_skip = []
for row in rows:
if row["peak_id_a"] in names_to_skip and row["peak_id_b"] in names_to_skip and not row["adduct_label"]:
continue
records = []
match = None
if row["adduct_label"]:
if row["mz_ratio"] > 1: # oligomers
match = difflib.get_close_matches(row["adduct_label"], lib_adducts.lib.keys(), n=1)
adducts = [match[0]]
else:
adducts = [str(row["adduct_label"])]