Summarize emerging lineages — summarize

Tests whether each lineage's frequency is significantly increasing over time using a binomial GLM. Useful for early warning of lineages that may warrant enhanced surveillance.

Usage

summarize_emerging(data, threshold = 0.01, min_obs = 3L, p_adjust = "holm")

Arguments

data: An lfq_data object.
threshold: Minimum current frequency to test. Default 0.01.
min_obs: Minimum time points observed. Default 3.
p_adjust: P-value adjustment method. Default "holm".

Value

A tibble with columns: lineage, first_seen, last_seen, n_timepoints, current_freq, growth_rate, p_value, p_adjusted, significant, direction.

Examples

sim <- simulate_dynamics(
  n_lineages = 4,
  advantages = c(emerging = 1.5, stable = 1.0, declining = 0.7),
  n_timepoints = 12, seed = 42)
summarize_emerging(sim)
#> # A tibble: 2 × 10
#>   lineage  first_seen last_seen  n_timepoints current_freq growth_rate   p_value
#>   <chr>    <date>     <date>            <int>        <dbl>       <dbl>     <dbl>
#> 1 emerging 2026-04-13 2026-06-29           12        0.976      0.0645 0        
#> 2 stable   2026-04-13 2026-06-29           12        0.016     -0.0394 9.90e-101
#> # ℹ 3 more variables: p_adjusted <dbl>, significant <lgl>, direction <chr>