immuneML.simulation.implants package

Submodules

immuneML.simulation.implants.ImplantAnnotation module

class immuneML.simulation.implants.ImplantAnnotation.ImplantAnnotation(signal_id: str = None, motif_id: str = None, motif_instance: immuneML.simulation.implants.MotifInstance.MotifInstance = None, position: int = None)

Bases: object

motif_id: str = None

motif_instance: immuneML.simulation.implants.MotifInstance.MotifInstance = None

position: int = None

signal_id: str = None

immuneML.simulation.implants.Motif module

class immuneML.simulation.implants.Motif.Motif(identifier: str, instantiation: immuneML.simulation.motif_instantiation_strategy.MotifInstantiationStrategy.MotifInstantiationStrategy, seed: Optional[str] = None, seed_chain1: Optional[str] = None, name_chain1: Optional[immuneML.data_model.receptor.receptor_sequence.Chain.Chain] = None, seed_chain2: Optional[str] = None, name_chain2: Optional[immuneML.data_model.receptor.receptor_sequence.Chain.Chain] = None)

Bases: object

Class describing motifs where each motif is defined by a seed and a way of creating specific instances of the motif (instantiation_strategy);

When instantiation_strategy is set, specific motif instances will be produced by calling instantiate_motif(seed) method of instantiation_strategy

Parameters

• seed (str) – An amino acid sequence that represents the basic motif seed. All implanted motifs correspond to the seed, or a modified

• thereof (version) –

• set (is) –

• used. (In the YAML specification this can either be one of these values as a string in which case the default parameters will be) –

• instantiation (MotifInstantiationStrategy) –

• MotifInstantiationStrategy. (Which strategy to use for implanting the seed. It should be one of the classes inheriting) –

• used. –

• Alternatively –

• of (instantiation can be specified with parameters as in the example YAML specification below. For the detailed list) –

• parameters –

• below. (see the specific instantiation strategies) –

• seed_chain1 (str) – in case when representing motifs for paired chain data, it is possible to define a motif seed per chain; if this parameter

• set –

• argument (the generated motif instances will include a motif instance for both chains; for more details on how it works see seed) –

• set. (argument is used only if the seed argument is not) –

• seed_chain2 (str) – used for paired chain data, for the other receptor chain; for more details on how it works see seed argument. This

• set. –

• name_chain1 – name of the first chain if paired receptor data are simulated. The value should be an instance of

:param Chain. This argument is used only if the seed argument is not set.: :param name_chain2: name of the second chain 2 if paired receptor data are simulated. The value should be an instance of :param Chain. This argument is used only if the seed argument is not set.:

YAML specification:

motifs:
    # examples for single chain receptor data
    my_simple_motif: # this will be the identifier of the motif
        seed: AAA
        instantiation: GappedKmer
    my_gapped_motif:
        seed: AA/A
        instantiation:
            GappedKmer:
                min_gap: 1
                max_gap: 2
    # examples for paired chain receptor data
    my_paired_motif:
        seed_chain1: AAA # seed for chain1 or chain2 can optionally include gap, same as for single chain receptor data
        name_chain1: ALPHA # alpha chain of TCR
        seed_chain2: CCC
        name_chain2: BETA # beta chain of TCR
        instantiation: GappedKmer # same as for single chain receptor data

static get_documentation()

get_max_length()

identifier: str

instantiate_motif(chain_name: Optional[immuneML.data_model.receptor.receptor_sequence.Chain.Chain] = None)

Creates a motif instance based on the seed; if seed parameter is defined for the motif, it is assumed that single chain data are used for the analysis. If seed is None, then it is assumed that paired chain receptor data are required in which case this function will return a motif instance per chain along with the names of the chains

Returns

a motif instance if single chain immune receptor data are simulated or a dict where keys are chain names and values are motif instances for the corresponding chains

instantiation: immuneML.simulation.motif_instantiation_strategy.MotifInstantiationStrategy.MotifInstantiationStrategy

name_chain1: immuneML.data_model.receptor.receptor_sequence.Chain.Chain = None

name_chain2: immuneML.data_model.receptor.receptor_sequence.Chain.Chain = None

seed: str = None

seed_chain1: str = None

seed_chain2: str = None

immuneML.simulation.implants.MotifInstance module

class immuneML.simulation.implants.MotifInstance.MotifInstance(instance: str, gap: int)

Bases: object

immuneML.simulation.implants.Signal module

class immuneML.simulation.implants.Signal.Signal(identifier: str, motifs: List[immuneML.simulation.implants.Motif.Motif], implanting_strategy: immuneML.simulation.signal_implanting_strategy.SignalImplantingStrategy.SignalImplantingStrategy)

Bases: object

This class represents the signal that will be implanted during a Simulation. A signal is represented by a list of motifs, and an implanting strategy.

A signal is associated with a metadata label, which is assigned to a receptor or repertoire. For example antigen-specific/disease-associated (receptor) or diseased (repertoire).

Parameters

• motifs (list) – A list of the motifs associated with this signal.

• implanting (SignalImplantingStrategy) –

• implanted (The strategy that is used to decide in which sequences the motifs should be) –

• how. (and) –

• strategies. (Valid values for this argument are class names of different signal implanting) –

YAML specification:

signals:
    my_signal:
        motifs:
            - my_simple_motif
            - my_gapped_motif
        implanting: HealthySequence
        sequence_position_weights:
            109: 0.5
            110: 0.5

static get_documentation()

implant_in_receptor(receptor: immuneML.data_model.receptor.Receptor.Receptor, is_noise: bool) → immuneML.data_model.receptor.Receptor.Receptor

implant_to_repertoire(repertoire: immuneML.data_model.repertoire.Repertoire.Repertoire, repertoire_implanting_rate: float, path: pathlib.Path) → immuneML.data_model.repertoire.Repertoire.Repertoire

Module contents