immuneML.simulation.motif_instantiation_strategy package¶
Submodules¶
immuneML.simulation.motif_instantiation_strategy.GappedKmerInstantiation module¶

class
immuneML.simulation.motif_instantiation_strategy.GappedKmerInstantiation.
GappedKmerInstantiation
(hamming_distance_probabilities: Optional[dict] = None, min_gap: int = 0, max_gap: int = 0, alphabet_weights: Optional[dict] = None, position_weights: Optional[dict] = None)[source]¶ 
Creates a motif instance from a given seed and additional optional parameters. Currently, at most a single gap can be specified in the sequence.
 Parameters
min_gap (int) – The minimum gap length, in case the original seed contains a gap.
max_gap (int) – The maximum gap length, in case the original seed contains a gap.
hamming_distance_probabilities (dict) – The probability of modifying the given seed with each
of modifications. The keys represent the number of modifications (number) –
the original seed and the implanted motif (between) –
the values represent the probabilities for (and) –
respective number of modifications. For example {0 (the) – 0.7, 1: 0.3} means that 30% of the time one position
be modified (will) –
the remaining 70% of the time the motif will remain unmodified with respect (and) –
the seed. The values of hamming_distance_probabilities must sum to 1. (to) –
position_weights (dict) – A dictionary containing the relative probabilities of choosing
position for hamming distance modification. The keys represent the position in the seed (each) –
where –
starts at 0. If the index of a gap is specified in position_weights (counting) –
will be removed. The values (it) –
the relative probabilities for modifying each position when it gets selected for modification. (represent) –
example {0 (For) – 0.6, 1: 0, 2: 0.4} means that when a sequence is selected for a modification (as
in hamming_distance_probabilities) (specified) –
60% of the time the amino acid at index 0 is modified (then) –
:param : :param and the remaining 40% of the time the amino acid at index 2. If the values of position_weights do not sum: :param to 1: :param the remainder will be redistributed over all positions: :param including those not specified.: :param alphabet_weights: A dictionary describing the relative probabilities of choosing each amino acid :type alphabet_weights: dict :param for hamming distance modification. The keys represent the amino acids and the values the relative: :param probabilities for choosing this amino acid. If the values of alphabet_weights do not sum to 1: :param the remainder: :param will be redistributed over all possible amino acids: :param including those not specified.:
YAML specification:
GappedKmer: min_gap: 1 max_gap: 2 hamming_distance_probabilities: 0: 0.7 1: 0.3 position_weights: # note that index 2, the position of the gap, is excluded from position_weights 0: 1 1: 0 3: 0 alphabet_weights: A: 0.2 C: 0.2 D: 0.4 E: 0.2

instantiate_motif
(base) → immuneML.simulation.implants.MotifInstance.MotifInstance[source]¶