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: dict = None, min_gap: int = 0, max_gap: int = 0, alphabet_weights: dict = None, position_weights: dict = None)[source]
Bases:
MotifInstantiationStrategy
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
modifications (number of modifications. The keys represent the number of) –
motif (between the original seed and the implanted) –
for (and the values represent the probabilities) –
{0 (For example) – 0.7, 1: 0.3} means that 30% of the time one position
modified (then 60% of the time the amino acid at index 0 is) –
respect (and the remaining 70% of the time the motif will remain unmodified with) –
1. (to the seed. The values of hamming_distance_probabilities must sum to) –
position_weights (counting starts at 0. If the index of a gap is specified in) – A dictionary containing the relative probabilities of choosing
seed (each position for hamming distance modification. The keys represent the position in the) –
where –
position_weights –
values (it will be removed. The) –
modification. (represent the relative probabilities for modifying each position when it gets selected for) –
{0 – 0.6, 1: 0, 2: 0.4} means that when a sequence is selected for a modification (as
hamming_distance_probabilities) (specified in) –
modified –
: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) MotifInstance [source]