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99 lines
3.1 KiB
R
99 lines
3.1 KiB
R
#' Score genes based on their proximity to the reference genes.
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#'
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#' In this case, the distance data that is available for one gene is first
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#' combined. The resulting value is compared to the reference genes and
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#' determines the gene's score in relation to other genes.
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#'
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#' @param id Unique ID for the method and its results.
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#' @param name Human readable name for the method.
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#' @param description Method description.
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#' @param distance_estimate A function that will be used to summarize the
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#' distance values for each gene. See [densest()] for the default
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#' implementation.
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#'
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#' @return An object of class `geposan_method`.
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#'
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#' @export
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adjacency <- function(id = "adjacency",
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name = "Adjacency",
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description = "Adjacency to reference genes",
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distance_estimate = densest) {
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method(
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id = id,
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name = name,
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description = description,
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help = paste0(
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"Adjacency to the reference genes across species. This method penalizes ",
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"genes that do not occur in the region typical for the reference genes, ",
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"without artificially defining a fixed boundary."
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),
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function(preset, progress) {
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species_ids <- preset$species_ids
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gene_ids <- preset$gene_ids
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reference_gene_ids <- preset$reference_gene_ids
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cached(
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id,
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c(
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species_ids,
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gene_ids,
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reference_gene_ids,
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distance_estimate
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),
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{ # nolint
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# Filter distances by species and gene and summarize each
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# gene's distance values using the estimation function.
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data <- geposan::distances[
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species %chin% species_ids & gene %chin% gene_ids,
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.(distance = as.numeric(distance_estimate(distance))),
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by = gene
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]
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# Compute the absolute value of the difference between the
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# estimated distances of each gene to the reference genes.
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compute_difference <- function(distance_values,
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comparison_ids) {
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comparison_distance <- data[
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gene %chin% comparison_ids,
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distance_estimate(distance)
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]
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abs(distance_values - comparison_distance)
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}
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# Compute the differences to the reference genes.
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data[
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!gene %chin% reference_gene_ids,
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difference := compute_difference(
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distance,
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reference_gene_ids
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)
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]
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progress(0.5)
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# Exclude the reference gene itself when computing its
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# difference.
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data[
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gene %chin% reference_gene_ids,
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difference := compute_difference(
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distance,
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reference_gene_ids[reference_gene_ids != gene]
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)
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]
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# Compute the final score by normalizing the difference.
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data[, score := 1 - difference / max(difference)]
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progress(1.0)
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result(
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method = "adjacency",
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scores = data[, .(gene, score)],
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details = list(data = data)
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)
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}
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)
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}
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)
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}
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