#' Score genes based on their proximity to the reference genes. #' #' @param estimate A function that will be used to summarize the distance #' values for each gene. By default, [median()] is used. #' @param combination A function that will be used to combine the different #' distances to the reference genes. By default [min()] is used. That means #' the distance to the nearest reference gene will be scored. #' #' @return An object of class `geposan_method`. #' #' @export adjacency <- function(estimate = stats::median, combination = min) { method( id = "adjacency", name = "Adjacency", description = "Adjacency to reference genes", function(preset, progress) { species_ids <- preset$species_ids gene_ids <- preset$gene_ids reference_gene_ids <- preset$reference_gene_ids cached( "adjacency", c( species_ids, gene_ids, reference_gene_ids, estimate, combination ), { # nolint # Filter distances by species and gene and summarize each # gene's distance values using the estimation function. data <- geposan::distances[ species %chin% species_ids & gene %chin% gene_ids, .(distance = as.numeric(estimate(distance))), by = gene ] # Compute the absolute value of the difference between the # estimated distances of each gene to the reference genes. compute_difference <- function(distance_value, comparison_ids) { differences <- data[ gene %chin% comparison_ids, .(difference = abs(distance_value - distance)) ] combination(differences$difference) } # Compute the differences to the reference genes. data[ !gene %chin% reference_gene_ids, difference := compute_difference( distance, reference_gene_ids ), by = gene ] progress(0.5) # Exclude the reference gene itself when computing its # difference. data[ gene %chin% reference_gene_ids, difference := compute_difference( distance, reference_gene_ids[reference_gene_ids != gene] ), by = gene ] # Compute the final score by normalizing the difference. data[, score := 1 - difference / max(difference)] progress(1.0) result( method = "adjacency", scores = data[, .(gene, score)], details = list(data = data) ) } ) } ) }