Plots estimated k
plot_estimated_k.RdPlots the estimated k for residues. Estimated k for each are calculated from classification results, treating the n (population) as the probability of getting corresponding rate of exchange. The aggregation of results is described in the vignette.
Examples
kin_dat <- prepare_kin_dat(alpha_dat)
fit_k_params <- get_example_fit_k_params()
control <- get_example_control()
fit_values <- create_fit_dataset(kin_dat, fit_k_params, control)
hires_params <- calculate_hires(fit_values)
#> Error in if (method == "shortest") { hires_params_ <- lapply(seq(1:protein_length), function(pos) { if (fractional) { tmp_params <- fit_values %>% filter(start <= pos & pos <= end & n_1 + n_2 + n_3 < 1.25) } else { tmp_params <- fit_values %>% filter(start <= pos & pos <= end & n_1 + n_2 + n_3 - max_uptake <= 0) } tmp_params <- tmp_params %>% filter(!class_name %in% c("invalid", "invalid_uc")) %>% arrange(nchar(sequence), class_name) %>% .[1, ] if (nrow(tmp_params) == 0) { data.frame(Protein = Protein, State = State, position = pos, n_1 = NA, k_1 = NA, n_2 = NA, k_2 = NA, n_3 = NA, k_3 = NA, k_est = NA, class_name = NA, color = NA) } else { data.frame(Protein = Protein, State = State, position = pos, n_1 = tmp_params[["n_1"]], k_1 = tmp_params[["k_1"]], n_2 = tmp_params[["n_2"]], k_2 = tmp_params[["k_2"]], n_3 = tmp_params[["n_3"]], k_3 = tmp_params[["k_3"]], k_est = tmp_params[["k_est"]], class_name = tmp_params[["class_name"]], color = tmp_params[["color"]]) } }) %>% bind_rows()}: the condition has length > 1
plot_estimated_k(hires_params)
#> Error: object 'hires_params' not found