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Sample epitopes

Source: R/sample_epitopes.R
sample_epitopes.Rd

Sample epitopes based on epitope probabilities. Note that the positions returned assume that the start of the amino acid sequence is also the start of the founder sequence in the simulation. We also assume that there are no frameshift mutations in the founder sequence.

Usage

sample_epitopes(
  epitope_probabilities,
  start_aa_pos = 0,
  end_aa_pos = NULL,
  num_epitopes = 10,
  aa_epitope_length = 10,
  max_fit_cost = 0.3,
  max_resamples = 100,
  ref_founder_map = NULL
)

Arguments

epitope_probabilities

Epitope probability tibble as output by get_epitope_frequencies(), including columns aa_position and epitope_probability. aa_position should be indexed at 0

start_aa_pos

Starting amino acid position to consider for epitopes, indexed at 0 (default: 0, i.e. the first position)

end_aa_pos

Ending amino acid position to consider for epitopes, indexed at 0 (default: NULL, i.e. through the final position in epitope_probabilities$aa_position)

num_epitopes

Number of epitopes to sample

aa_epitope_length

Amino acid epitope length

max_fit_cost

Maximum fitness cost of an epitope, must be in the range [0,1) where 0 indicates no cost. 1, which indicates no ability to survive, is not allowed (default: 0.3) note that the model output is very sensitive to this parameter

max_resamples

Maximum number of resampling events to attempt; this is to prevent an infinite loop (default: 100)

ref_founder_map

Output from map_ref_founder(), including nucleotide reference and founder positions (ref_pos and founder_pos). NOTE: The reference positions here, if they were converted to amino acid positions, are expected to match with the reference positions in epitope_probabilities. Further, we assume that the founder indices align with the founder sequence positions to be used in the simulation (default: NULL)

Value

tibble with the num_epitopes rows and the following columns:

  • epi_start_nt: nucleotide epitope start position

  • epi_end_nt: nucleotide epitope end position

  • max_fitness_cost: maximum fitness cost for that epitope

Examples

sample_epitopes(get_epitope_frequencies(env_features$Position - 1))
#> 5 resamples required
#> # A tibble: 10 × 3
#>    epi_start_nt epi_end_nt max_fitness_cost
#>           <dbl>      <dbl>            <dbl>
#>  1          882        912             0.03
#>  2          819        849             0.06
#>  3          489        519             0.09
#>  4          576        606             0.12
#>  5          522        552             0.15
#>  6          459        489             0.18
#>  7          357        387             0.21
#>  8          951        981             0.24
#>  9         1080       1110             0.27
#> 10         1272       1302             0.3