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import abc |
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import math |
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import time |
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import urllib |
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from dataclasses import dataclass |
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from datetime import datetime |
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from functools import cached_property |
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from pathlib import Path |
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from typing import Mapping, NamedTuple, Optional, Sequence |
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from urllib import request |
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import decorateme |
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import regex |
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from pocketutils.core.chars import Chars |
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from pocketutils.core.dot_dict import NestedDotDict |
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from pocketutils.core.enums import FlagEnum |
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from pocketutils.core.query_utils import QueryExecutor |
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from pocketutils.tools.common_tools import CommonTools |
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from mandos.model import Api, CompoundNotFoundError |
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from mandos.model.settings import QUERY_EXECUTORS, SETTINGS |
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from mandos.model.utils.setup import logger |
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class _Prop(NamedTuple): |
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kind: str |
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source: str |
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_prefixes = dict(M=1e6, mM=1e3, µM=1, uM=1, nM=1e-3, pM=1e-6, fM=1e-9) |
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_PREDICTED_PROPERTIES = [ |
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_Prop("average_mass", "ChemAxon"), |
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_Prop("logp", "ALOGPS"), |
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_Prop("logs", "ALOGPS"), |
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_Prop("solubility", "ALOGPS"), |
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_Prop("pka_strongest_acidic", "ChemAxon"), |
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_Prop("polar_surface_area", "ChemAxon"), |
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_Prop("polarizability", "ChemAxon"), |
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_Prop("physiological_charge", "ChemAxon"), |
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] |
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_RULES = [ |
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_Prop("rule_of_five", "ChemAxon"), |
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_Prop("ghose_filter", "ChemAxon"), |
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_Prop("veber_rule", "ChemAxon"), |
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_Prop("mddr_like_rule", "ChemAxon"), |
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] |
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_p1 = regex.compile(r"^([0-9.]+ +\(([0-9.]+) *\- *([0-9.]+)\)$", flags=regex.V1) |
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_p2 = regex.compile(r"^([0-9.]+) +\+\/\- +([0-9.]+)$", flags=regex.V1) |
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class HmdbCompoundLookupError(CompoundNotFoundError): |
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""" """ |
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class ConcentrationBound(NamedTuple): |
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mean: float |
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lower: float |
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upper: float |
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@property |
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def std(self) -> float: |
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return self.upper / 2 - self.lower / 2 |
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@property |
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def is_symmetric(self) -> bool: |
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return math.isclose(self.upper - self.mean, self.mean - self.lower) |
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@dataclass(frozen=True, repr=True, order=True) |
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class HmdbProperty: |
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kind: str |
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source: str |
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value: str |
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@dataclass(frozen=True, repr=True, order=True) |
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class HmdbDisease: |
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name: str |
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omim_id: str |
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n_refs: int |
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class PersonAge(FlagEnum): |
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unknown = () |
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adults = () |
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children = () |
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class PersonSex(FlagEnum): |
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unknown = () |
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male = () |
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female = () |
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@dataclass(frozen=True, repr=True, order=True) |
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class HmdbConcentration: |
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specimen: str |
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ages: PersonAge |
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sexes: PersonSex |
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condition: Optional[str] |
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micromolar: Optional[ConcentrationBound] |
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mg_per_kg: Optional[ConcentrationBound] |
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def __post_init__(self): |
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if (self.mg_per_kg is None) + (self.micromolar is None) != 1: |
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raise AssertionError( |
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f"Provided both micromolar ({self.micromolar})" |
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+ f" and mg/kg ({self.mg_per_kg}), or neither" |
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) |
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@cached_property |
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def format_value(self) -> str: |
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return f"{self._value}{Chars.narrownbsp}{self._unit}" |
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@cached_property |
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def format_value_pm(self) -> str: |
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v, u, s = self._value, self._unit, Chars.narrownbsp |
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return f"{v.mean}{Chars.plusminus}{v.std}{s}{u}" |
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@cached_property |
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def format_value_range(self) -> str: |
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v, u, s = self._value, self._unit, Chars.narrownbsp |
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return f"{v.mean}{s}({v.lower}{Chars.en}{v.upper}){s}{u}" |
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@property |
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def _value(self) -> ConcentrationBound: |
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if self.mg_per_kg is not None: |
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return self.mg_per_kg |
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return self.micromolar |
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@property |
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def _unit(self) -> str: |
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if self.mg_per_kg is not None: |
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return " mg/kg" |
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return " µmol/L" |
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class HmdbData: |
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def __init__(self, data: NestedDotDict): |
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self._data = data |
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@property |
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def cid(self) -> str: |
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return self._data.req_as("metabolite.accession", str) |
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@property |
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def inchi(self) -> str: |
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return self._data.req_as("metabolite.inchi", str) |
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@property |
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def inchikey(self) -> str: |
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return self._data.req_as("metabolite.inchikey", str) |
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@property |
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def smiles(self) -> str: |
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return self._data.req_as("metabolite.smiles", str) |
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@property |
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def cas(self) -> str: |
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return self._data.req_as("metabolite.cas_registry_number", str) |
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@property |
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def drugbank_id(self) -> Optional[str]: |
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return self._data.get_as("metabolite.inchikey", str) |
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@property |
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def pubchem_id(self) -> Optional[str]: |
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return self._data.get_as("metabolite.pubchem_compound_id", str) |
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@property |
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def create_date(self) -> datetime: |
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return datetime.fromisoformat(self._data.req_as("metabolite.creation_date", str)) |
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@property |
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def mod_date(self) -> datetime: |
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return datetime.fromisoformat(self._data.req_as("metabolite.update_date", str)) |
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@cached_property |
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def predicted_properties(self) -> Sequence[HmdbProperty]: |
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data = self._data.get("metabolite.predicted_properties", []) |
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return [ |
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HmdbProperty(kind=x["kind"], source=x["source"], value=x["value"]) |
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for x in data |
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if _Prop(x["kind"], x["source"]) in _PREDICTED_PROPERTIES |
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] |
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@cached_property |
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def rules(self) -> Mapping[str, bool]: |
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data = self._data.get("metabolite.predicted_properties", []) |
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return { |
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r["kind"]: CommonTools.parse_bool_flex(r["value"]) |
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for r in data |
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if (r["kind"], r["source"]) in _RULES |
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} |
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@cached_property |
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def diseases(self) -> Sequence[HmdbDisease]: |
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data = self._data.get_list_as("metabolite.diseases", NestedDotDict) |
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return [HmdbDisease(d["name"], d["omim_id"], len(d.get("references", []))) for d in data] |
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@cached_property |
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def specimens(self) -> Sequence[str]: |
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return self._data.get_list_as("metabolite.biological_properties.biospecimen_locations", str) |
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@cached_property |
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def tissue_locations(self) -> Sequence[str]: |
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210
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return self._data.get_list_as("metabolite.biological_properties.tissue_locations", str) |
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@cached_property |
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def normal_concentrations(self) -> Sequence[HmdbConcentration]: |
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data = self._data.get_list_as("metabolite.normal_concentrations", NestedDotDict, []) |
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results = [] |
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for d in data: |
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x = self._new_conc(d) |
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if x is not None: |
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results.append(x) |
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return results |
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def _new_conc(self, x: NestedDotDict) -> Optional[HmdbConcentration]: |
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specimen = x["biospecimen"] |
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# both can be "Not Specified" |
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ages = { |
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"Adult": PersonAge.adults, |
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"Children": PersonAge.children, |
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"Both": PersonAge.adults | PersonAge.children, |
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}.get(x.get_as("subject_age", str, "").split(" ")[0], PersonAge.unknown) |
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sexes = { |
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"Male": PersonSex.male, |
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"Female": PersonSex.female, |
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"Both": PersonSex.female | PersonSex.male, |
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}.get(x.get_as("subject_sex", str, ""), PersonSex.unknown) |
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condition = ( |
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None |
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if x.get("subject_condition") == "Normal" |
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else x.get_as("patient_information", str, "") |
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) |
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value, units = x.get_as("concentration_value", str), x.get_as("concentration_units", str) |
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if value is None or len(value) == 0: |
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logger.trace(f"Discarding {x} with empty value") |
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return None |
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if units not in ["uM", "mg/kg"]: |
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logger.trace(f"Discarding {x} with units '{units}'") |
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return None |
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247
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bound = self._parse_conc(value) |
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if bound is None: |
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logger.warning(f"Could not parse concentration {value} (units: {units})") |
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logger.trace(f"Full data: {x}") |
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return None |
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return HmdbConcentration( |
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specimen=specimen, |
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ages=ages, |
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255
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sexes=sexes, |
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256
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condition=condition, |
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257
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micromolar=bound if units == "uM" else None, |
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258
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mg_per_kg=bound if units == "mg/kg" else None, |
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259
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) |
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260
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261
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def _parse_conc(self, value: str) -> Optional[ConcentrationBound]: |
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262
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m: regex.Match = _p1.fullmatch(value) |
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263
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if m is not None: |
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return ConcentrationBound(*m.groups()) |
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m: regex.Match = _p2.fullmatch(value) |
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if m is not None: |
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v, std = m.groups() |
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268
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return ConcentrationBound(v, v - std, v + std) |
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return None |
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270
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271
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@cached_property |
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272
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def abnormal_concentrations(self) -> Sequence[HmdbConcentration]: |
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273
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return self._data.get("metabolite.normal_concentrations", []) |
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274
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275
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276
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@decorateme.auto_repr_str() |
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277
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class HmdbApi(Api, metaclass=abc.ABCMeta): |
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278
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def fetch(self, hmdb_id: str) -> HmdbData: |
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279
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raise NotImplementedError() |
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280
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281
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282
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@decorateme.auto_repr_str() |
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class QueryingHmdbApi(HmdbApi): |
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def __init__(self, executor: QueryExecutor = QUERY_EXECUTORS.hmdb): |
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self._executor = executor |
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def fetch(self, inchikey_or_hmdb_id: str) -> HmdbData: |
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logger.debug(f"Downloading HMDB data for {inchikey_or_hmdb_id}") |
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# e.g. https://hmdb.ca/metabolites/HMDB0001925.xml |
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cid = None |
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if inchikey_or_hmdb_id.startswith("HMDB"): |
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cid = inchikey_or_hmdb_id |
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else: |
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time.sleep(SETTINGS.hmdb_query_delay_min) # TODO |
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url = f"https://hmdb.ca/unearth/q?query={inchikey_or_hmdb_id}&searcher=metabolites" |
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try: |
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res = urllib.request.urlopen(url) |
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url_ = res.geturl() |
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logger.trace(f"Got UR {url_} from {url}") |
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cid = url_.split("/")[-1] |
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if not cid.startswith("HMDB"): |
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raise ValueError(f"Invalid CID {cid} from URL {url_}") |
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except Exception: |
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raise HmdbCompoundLookupError(f"No HMDB match for {inchikey_or_hmdb_id}") |
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url = f"https://hmdb.ca/metabolites/{cid}.xml" |
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try: |
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data = self._executor(url) |
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except Exception: |
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raise HmdbCompoundLookupError(f"No HMDB match for {inchikey_or_hmdb_id} ({cid})") |
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return HmdbData(self._to_json(data)) |
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def _to_json(self, xml) -> NestedDotDict: |
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response = {} |
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for child in list(xml): |
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if len(list(child)) > 0: |
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response[child.tag] = self._to_json(child) |
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else: |
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response[child.tag] = child.text or "" |
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return NestedDotDict(response) |
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def _query(self, url: str) -> str: |
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data = self._executor(url) |
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tt = self._executor.last_time_taken |
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wt, qt = tt.wait.total_seconds(), tt.query.total_seconds() |
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bts = int(len(data) * 8 / 1024) |
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logger.trace(f"Queried {bts} kb from {url} in {qt:.1} s with {wt:.1} s of wait") |
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return data |
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@decorateme.auto_repr_str() |
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331
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class CachingHmdbApi(HmdbApi): |
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def __init__( |
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self, query: Optional[QueryingHmdbApi], cache_dir: Path = SETTINGS.hmdb_cache_path |
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): |
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self._query = query |
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self._cache_dir = cache_dir |
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def path(self, inchikey_or_hmdb_id: str) -> Path: |
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return self._cache_dir / f"{inchikey_or_hmdb_id}.json.gz" |
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341
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def fetch(self, inchikey_or_hmdb_id: str) -> HmdbData: |
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path = self.path(inchikey_or_hmdb_id) |
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if path.exists(): |
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return HmdbData(NestedDotDict.read_json(path)) |
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345
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else: |
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data = self._query.fetch(inchikey_or_hmdb_id) |
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path = self.path(data.cid) |
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348
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data._data.write_json(path, mkdirs=True) |
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349
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logger.info(f"Saved HMDB metabolite {data.cid}") |
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350
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self._write_links(data) |
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351
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return data |
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352
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353
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def _write_links(self, data: HmdbData) -> None: |
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354
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path = self.path(data.cid) |
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355
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# these all have different prefixes, so it's ok |
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356
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aliases = [ |
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357
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data.inchikey, |
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358
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*[ell for ell in [data.cas, data.pubchem_id, data.drugbank_id] if ell is not None], |
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359
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] |
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360
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for alias in aliases: |
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361
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link = self.path(alias) |
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362
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link.unlink(missing_ok=True) |
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363
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path.link_to(link) |
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364
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logger.debug(f"Added aliases {','.join([str(s) for s in aliases])} ⇌ {data.cid} ({path})") |
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365
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366
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|
367
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__all__ = [ |
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368
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"HmdbApi", |
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369
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"QueryingHmdbApi", |
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370
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"CachingHmdbApi", |
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371
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"HmdbProperty", |
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372
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"ConcentrationBound", |
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373
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"HmdbData", |
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374
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"PersonSex", |
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375
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"PersonAge", |
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376
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"HmdbConcentration", |
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377
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"HmdbDisease", |
|
378
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"HmdbCompoundLookupError", |
|
379
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] |
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380
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