Reorganize source files and generalize presets

proximity.R

@@ -1,29 +0,0 @@
-library(data.table)
-
-#' Score the mean distance of genes to the telomeres across species.
-#'
-#' A score will be given to each gene such that 0.0 corresponds to the maximal
-#' mean distance across all genes and 1.0 corresponds to a distance of 0.
-#'
-#' The result will be a data.table with the following columns:
-#'
-#'  - `gene` Gene ID of the processed gene.
-#'  - `score` Score for the proximity.
-#'
-#' @param distances Distance data to use.
-#' @param species_ids Species, whose data should be included.
-#' @param gene_ids Genes to process.
-process_proximity <- function(distances, species_ids, gene_ids, ...) {
-    species_count <- length(species_ids)
-
-    # Prefilter distances by species.
-    distances <- distances[species %chin% species_ids]
-
-    # Compute the score as described above.
-
-    distances <- distances[, .(mean_distance = mean(distance)), by = "gene"]
-    max_distance <- distances[, max(mean_distance)]
-    distances[, score := 1 - mean_distance / max_distance]
-
-    distances[, .(gene, score)]
-}