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Move species count to analysis

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This commit is contained in:
Elias Projahn 2021-11-17 22:57:31 +01:00
parent f84d37dd30
commit 33056bfa40
6 changed files with 30 additions and 45 deletions
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30
R/ranking.R
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@ -6,33 +6,18 @@
#' @param analysis Analysis object resulting from [analyze()].
#' @param weights Named list pairing method names with weighting factors. Only
#' methods that are contained within this list will be included.
#' @param min_n_species Minimum number of required species per gene. Genes that
#' have fewer species will not be included in the ranking.
#'
#' @returns A ranking object. The object extends the analysis result with
#' additional columns containing the `score` and the `rank` of each gene. It
#' will be ordered by rank.
#'
#' @export
ranking <- function(analysis, weights, min_n_species = 10) {
ranking <- function(analysis, weights) {
if (!"geposan_analysis" %chin% class(analysis)) {
stop("Invalid analyis. Use geposan::analyze().")
}
# Count included species from the preset per gene.
genes_n_species <- geposan::distances[
species %chin% analysis$preset$species_ids,
.(n_species = .N),
by = "gene"
]
setkey(genes_n_species, gene)
# Exclude genes with too few species.
ranking <- analysis$results[
genes_n_species[gene, n_species] >= min_n_species
]
ranking <- copy(analysis$results)
ranking[, score := 0.0]
for (method in names(weights)) {
@ -65,16 +50,13 @@ ranking <- function(analysis, weights, min_n_species = 10) {
#' @param reference_gene_ids IDs of the reference genes.
#' @param target The optimization target. It may be one of "mean", "min" or
#' "max" and results in the respective rank being optimized.
#' @param min_n_species Minimum number of required species per gene. Genes that
#' have fewer species will not be included in the rankings used to find the
#' optimal weights.
#'
#' @returns Named list pairing method names with their optimal weights. This
#' can be used as an argument to [ranking()].
#'
#' @export
optimal_weights <- function(analysis, methods, reference_gene_ids,
target = "mean", min_n_species = 10) {
target = "mean") {
if (!"geposan_analysis" %chin% class(analysis)) {
stop("Invalid analyis. Use geposan::analyze().")
}
@ -92,11 +74,7 @@ optimal_weights <- function(analysis, methods, reference_gene_ids,
# Compute the target rank of the reference genes when applying the weights.
target_rank <- function(factors) {
data <- ranking(
analysis,
weights(factors),
min_n_species = min_n_species
)
data <- ranking(analysis, weights(factors))
result <- data[gene %chin% reference_gene_ids, if (target == "min") {
min(rank)