Пример #1
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def test_find_constrained_pure_metabolic_reactions(model):
    """
    Expect zero or more purely metabolic reactions to have fixed constraints.

    If a reaction is neither a transport reaction, a biomass reaction nor a
    boundary reaction, it is counted as a purely metabolic reaction. This test
    requires the presence of metabolite formula to be able to identify
    transport reactions. This test simply reports the number of purely
    metabolic reactions that have fixed constraints and does not have any
    mandatory 'pass' criteria.

    Implementation: From the pool of pure metabolic reactions identify
    reactions which are constrained to values other than the model's minimal or
    maximal possible bounds.

    """
    ann = test_find_constrained_pure_metabolic_reactions.annotation
    pmr = basic.find_pure_metabolic_reactions(model)
    ann["data"] = get_ids_and_bounds(
        [rxn for rxn in pmr if basic.is_constrained_reaction(
            model, rxn)])
    ann["metric"] = len(ann["data"]) / len(pmr)
    ann["message"] = wrapper.fill(
        """A total of {:d} ({:.2%}) purely metabolic reactions have fixed
        constraints in the model, this excludes transporters, exchanges, or
        pseudo-reactions: {}""".format(len(ann["data"]), ann["metric"],
                                       truncate(ann["data"])))
Пример #2
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def test_metabolic_reaction_specific_sbo_presence(read_only_model):
    """Expect all metabolic reactions to be annotated with SBO:0000176.

    SBO:0000176 represents the term 'biochemical reaction'. Every metabolic
    reaction that is not a transport or boundary reaction should be annotated
    with this. The results shown are relative to the total amount of pure
    metabolic reactions.

    """
    ann = test_metabolic_reaction_specific_sbo_presence.annotation
    pure = basic.find_pure_metabolic_reactions(read_only_model)
    ann["data"] = get_ids(sbo.check_component_for_specific_sbo_term(
        pure, "SBO:0000176"))
    try:
        ann["metric"] = len(ann["data"]) / len(pure)
        ann["message"] = wrapper.fill(
            """A total of {} metabolic reactions ({:.2%} of all purely
            metabolic reactions) lack annotation with the SBO term
            "SBO:0000176" for 'biochemical reaction': {}""".format(
                len(ann["data"]), ann["metric"], truncate(ann["data"])))
    except ZeroDivisionError:
        ann["metric"] = 1.0
        ann["message"] = "The model has no metabolic reactions."
        pytest.skip(ann["message"])
    assert len(ann["data"]) == len(pure), ann["message"]
Пример #3
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def test_find_constrained_pure_metabolic_reactions(model):
    """
    Expect zero or more purely metabolic reactions to have fixed constraints.

    If a reaction is neither a transport reaction, a biomass reaction nor a
    boundary reaction, it is counted as a purely metabolic reaction. This test
    requires the presence of metabolite formula to be able to identify
    transport reactions. This test simply reports the number of purely
    metabolic reactions that have fixed constraints and does not have any
    mandatory 'pass' criteria.

    Implementation: From the pool of pure metabolic reactions identify
    reactions which are constrained to values other than the model's minimal or
    maximal possible bounds.

    """
    ann = test_find_constrained_pure_metabolic_reactions.annotation
    pmr = basic.find_pure_metabolic_reactions(model)
    ann["data"] = get_ids_and_bounds(
        [rxn for rxn in pmr if basic.is_constrained_reaction(model, rxn)])
    ann["metric"] = len(ann["data"]) / len(pmr)
    ann["message"] = wrapper.fill(
        """A total of {:d} ({:.2%}) purely metabolic reactions have fixed
        constraints in the model, this excludes transporters, exchanges, or
        pseudo-reactions: {}""".format(len(ann["data"]), ann["metric"],
                                       truncate(ann["data"])))
Пример #4
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def test_find_pure_metabolic_reactions(model):
    """
    Expect at least one pure metabolic reaction to be defined in the model.

    If a reaction is neither a transport reaction, a biomass reaction nor a
    boundary reaction, it is counted as a purely metabolic reaction. This test
    requires the presence of metabolite formula to be able to identify
    transport reactions. This test is passed when the model contains at least
    one purely metabolic reaction i.e. a conversion of one metabolite into
    another.

    Implementation:
    From the list of all reactions, those that are boundary, transport and
    biomass reactions are removed and the remainder assumed to be pure
    metabolic reactions. Boundary reactions are identified using the attribute
    cobra.Model.boundary. Please read the description of "Transport Reactions"
    and "Biomass Reaction Identified" to learn how they are identified.

    """
    ann = test_find_pure_metabolic_reactions.annotation
    ann["data"] = get_ids(
        basic.find_pure_metabolic_reactions(model))
    ann["metric"] = len(ann["data"]) / len(model.reactions)
    ann["message"] = wrapper.fill(
        """A total of {:d} ({:.2%}) purely metabolic reactions are defined in
        the model, this excludes transporters, exchanges, or pseudo-reactions:
        {}""".format(len(ann["data"]), ann["metric"], truncate(ann["data"])))
    assert len(ann["data"]) >= 1, ann["message"]
Пример #5
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def test_find_pure_metabolic_reactions(model):
    """
    Expect at least one pure metabolic reaction to be defined in the model.

    If a reaction is neither a transport reaction, a biomass reaction nor a
    boundary reaction, it is counted as a purely metabolic reaction. This test
    requires the presence of metabolite formula to be able to identify
    transport reactions. This test is passed when the model contains at least
    one purely metabolic reaction i.e. a conversion of one metabolite into
    another.

    Implementation:
    From the list of all reactions, those that are boundary, transport and
    biomass reactions are removed and the remainder assumed to be pure
    metabolic reactions. Boundary reactions are identified using the attribute
    cobra.Model.boundary. Please read the description of "Transport Reactions"
    and "Biomass Reaction Identified" to learn how they are identified.

    """
    ann = test_find_pure_metabolic_reactions.annotation
    ann["data"] = get_ids(basic.find_pure_metabolic_reactions(model))
    ann["metric"] = len(ann["data"]) / len(model.reactions)
    ann["message"] = wrapper.fill(
        """A total of {:d} ({:.2%}) purely metabolic reactions are defined in
        the model, this excludes transporters, exchanges, or pseudo-reactions:
        {}""".format(len(ann["data"]), ann["metric"], truncate(ann["data"])))
    assert len(ann["data"]) >= 1, ann["message"]
Пример #6
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def test_metabolic_reaction_specific_sbo_presence(model):
    """Expect all metabolic reactions to be annotated with SBO:0000176.

    SBO:0000176 represents the term 'biochemical reaction'. Every metabolic
    reaction that is not a transport or boundary reaction should be annotated
    with this. The results shown are relative to the total amount of pure
    metabolic reactions.

    Implementation:
    Check if each pure metabolic reaction has a non-zero "annotation"
    attribute that contains the key "sbo" with the associated
    value being the SBO term above.

    """
    ann = test_metabolic_reaction_specific_sbo_presence.annotation
    pure = basic.find_pure_metabolic_reactions(model)
    ann["data"] = get_ids(sbo.check_component_for_specific_sbo_term(
        pure, "SBO:0000176"))
    try:
        ann["metric"] = len(ann["data"]) / len(pure)
        ann["message"] = wrapper.fill(
            """A total of {} metabolic reactions ({:.2%} of all purely
            metabolic reactions) lack annotation with the SBO term
            "SBO:0000176" for 'biochemical reaction': {}""".format(
                len(ann["data"]), ann["metric"], truncate(ann["data"])))
    except ZeroDivisionError:
        ann["metric"] = 1.0
        ann["message"] = "The model has no metabolic reactions."
        pytest.skip(ann["message"])
    assert len(ann["data"]) == len(pure), ann["message"]
Пример #7
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def test_find_pure_metabolic_reactions(read_only_model, store):
    """Expect >= 1 pure metabolic reactions are present in the model."""
    store["metabolic_reactions"] = [
        rxn.id for rxn in basic.find_pure_metabolic_reactions(read_only_model)
    ]
    store["num_metabolic_reactions"] = len(store["metabolic_reactions"])
    assert store["num_metabolic_reactions"] >= 1
Пример #8
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def test_find_pure_metabolic_reactions(read_only_model):
    """
    Expect at least one pure metabolic reaction to be defined in the model.

    If a reaction is neither a transport reaction, a biomass reaction nor a
    boundary reaction, it is counted as a purely metabolic reaction. This test
    requires the presence of metabolite formula to be able to identify
    transport reactions. This test is passed when the model contains at least
    one purely metabolic reaction i.e. a conversion of one metabolite into
    another.
    """
    ann = test_find_pure_metabolic_reactions.annotation
    ann["data"] = get_ids(basic.find_pure_metabolic_reactions(read_only_model))
    ann["metric"] = len(ann["data"]) / len(read_only_model.reactions)
    ann["message"] = wrapper.fill(
        """A total of {:d} ({:.2%}) purely metabolic reactions are defined in
        the model, this excludes transporters, exchanges, or pseudo-reactions:
        {}""".format(len(ann["data"]), ann["metric"], truncate(ann["data"])))
    assert len(ann["data"]) >= 1, ann["message"]
Пример #9
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def test_find_constrained_pure_metabolic_reactions(model, num):
    """Expect num of contrained metabolic rxns to be identified correctly."""
    pmr = basic.find_pure_metabolic_reactions(model)
    contrained_pmr = set(
        [rxn for rxn in pmr if basic.is_constrained_reaction(model, rxn)])
    assert len(contrained_pmr) == num
Пример #10
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def test_find_pure_metabolic_reactions(model, num):
    """Expect amount of metabolic reactions to be identified correctly."""
    assert len(basic.find_pure_metabolic_reactions(model)) == num
Пример #11
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def test_find_candidate_irreversible_reactions(model):
    u"""
    Identify reversible reactions that could be irreversible.

    If a reaction is neither a transport reaction, a biomass reaction nor a
    boundary reaction, it is counted as a purely metabolic reaction.
    This test checks if the reversibility attribute of each reaction
    agrees with a thermodynamics-based
    calculation of reversibility.

    Implementation:
    To determine reversibility we calculate
    the reversibility index ln_gamma (natural logarithm of gamma) of each
    reaction
    using the eQuilibrator API. We consider reactions, whose reactants'
    concentrations would need to change by more than three orders of
    magnitude for the reaction flux to reverse direction, to be likely
    candidates of irreversible reactions. This assume default concentrations
    around 100 μM (~3 μM—3 mM) at pH = 7, I = 0.1 M and T = 298 K. The
    corresponding reversibility index is approximately 7. For
    further information on the thermodynamic and implementation details
    please refer to
    https://doi.org/10.1093/bioinformatics/bts317 and
    https://pypi.org/project/equilibrator-api/.

    Please note that currently eQuilibrator can only determine the
    reversibility index for chemically and redox balanced reactions whose
    metabolites can be mapped to KEGG compound identifiers (e.g. C00001). In
    addition
    to not being mappable to KEGG or the reaction not being balanced,
    there is a possibility that the metabolite cannot be broken down into
    chemical groups which is essential for the calculation of Gibbs energy
    using group contributions. This test collects each erroneous reaction
    and returns them as a tuple containing each list in the following order:
        1. Reactions with reversibility index
        2. Reactions with incomplete mapping to KEGG
        3. Reactions with metabolites that are problematic during calculation
        4. Chemically or redox unbalanced Reactions (after mapping to KEGG)

    This test simply reports the number of reversible reactions that, according
    to the reversibility index, are likely to be irreversible.

    """
    # With gamma = 1000, ln_gamma ~ 6.9. We use 7 as the cut-off.
    threshold = 7.0
    ann = test_find_candidate_irreversible_reactions.annotation
    met_rxns = basic.find_pure_metabolic_reactions(model)
    rev_index, incomplete, problematic, unbalanced = \
        thermo.find_thermodynamic_reversibility_index(met_rxns)
    ann["data"] = (
        # The reversibility index can be infinite so we convert it to a JSON
        # compatible string.
        [(r.id, str(i)) for r, i in rev_index],
        get_ids(incomplete),
        get_ids(problematic),
        get_ids(unbalanced)
    )
    num_irrev = sum(1 for r, i in rev_index if abs(i) >= threshold)
    ann["message"] = wrapper.fill(
        """Out of {} purely metabolic reactions, {} have an absolute
        reversibility index greater or equal to 7 and are therefore likely
        candidates for being irreversible.
        {} reactions could not be mapped to KEGG completely, {} contained
        'problematic' metabolites, and {} are chemically or redox imbalanced.
        """.format(len(met_rxns), num_irrev, len(incomplete), len(problematic),
                   len(unbalanced))
    )
    ann["metric"] = num_irrev / len(rev_index)