#' hypergeom feature class
#'
#' class to hold features undergoing hypergeometric enrichment
#'
#' @slot significant the significant features
#' @slot universe all of the features measured
#' @slot annotation annotation object
#'
#' @export
setClass("hypergeom_features",
slots = list(significant = "ANY",
universe = "ANY",
annotation = "annotation"))
#' do hypergeometric enrichment
#'
#' @param hypergeom_features a hypergeometric_features object
#' @param direction which direction to do the enrichment (over or under)
#' @param p_adjust how to correct the p-values (default is "BH")
#' @param min_features how many features should be annotated before testing it?
#'
#' @details The \code{min_features} argument here applies to the minumum number of features an annotation has
#' from the universe of features supplied, \bold{not} the minumum number of features from the differential
#' list.
#' For more about the p-value adjustment, see \code{stats::p.adjust}
#' @export
#' @return enriched_result
#'
hypergeometric_feature_enrichment <- function(hypergeom_features, direction = "over", p_adjust = "BH", min_features = 1){
# cleanup the features and annotations (should be in separate function)
hypergeom_features@universe <- unique(hypergeom_features@universe)
tmp_annot_feature <- hypergeom_features@annotation@annotation_features
annotation_universe <- unique(unlist(tmp_annot_feature))
hypergeom_features@universe <- intersect(hypergeom_features@universe, annotation_universe)
tmp_annot_feature <- lapply(tmp_annot_feature, intersect, hypergeom_features@universe)
n_feature <- sapply(tmp_annot_feature, length)
keep_annot <- n_feature >= min_features
tmp_annot_feature <- tmp_annot_feature[keep_annot]
hypergeom_features@significant <- intersect(hypergeom_features@significant, hypergeom_features@universe)
hypergeom_features@annotation@annotation_features <- tmp_annot_feature
# this probably needs its own function eventually
if (length(hypergeom_features@annotation@description) != 0){
hypergeom_features@annotation@description <- hypergeom_features@annotation@description[names(tmp_annot_feature)]
}
if (length(hypergeom_features@annotation@links) != 0){
hypergeom_features@annotation@links <- hypergeom_features@annotation@links[names(tmp_annot_feature)]
}
# now get the counts annotated
num_white_drawn <- sapply(hypergeom_features@annotation@annotation_features, function(x) sum(hypergeom_features@significant %in% x))
if (length(num_white_drawn) == 0){
num_white_drawn <- 0
}
num_white <- Biobase::listLen(hypergeom_features@annotation@annotation_features)
if (length(num_white) == 0){
num_white <- 0
}
num_black <- length(hypergeom_features@universe) - num_white
num_drawn <- length(hypergeom_features@significant)
hyper_stats <- hypergeometric_basic(num_white, num_black, num_drawn, num_white_drawn, direction)
hyper_stats$counts <- num_white_drawn[names(hyper_stats$p)]
hyper_stats$padjust <- p.adjust(hyper_stats$p, p_adjust)
out_stats <- new("statistical_results",
statistic_data = hyper_stats,
annotation_id = names(hypergeom_features@annotation@annotation_features),
method = "hypergeometric")
out_enrich <- new("enriched_result",
features = hypergeom_features@significant,
universe = hypergeom_features@universe,
statistics = out_stats,
annotation = hypergeom_features@annotation)
out_enrich
}
#' generate link text
#'
#' given a named vector of links, generate an actual html link formatted for output in html documents
#'
#' @param links the vector of links
#'
#' @export
#' @return character
generate_link <- function(links){
link_names <- names(links)
if (max(nchar(link_names)) == 0){
link_names <- "link"
}
paste('<a href="', links, '">', link_names, '</a>', sep = "")
}
#' do hypergeometric test
#'
#' does a hypergeometric enrichment test
#'
#' @param num_white number of white balls in urn
#' @param num_black number of black balls in urn
#' @param num_drawn number of balls taken from urn
#' @param num_white_drawn number of white balls taken from urn
#' @param direction which direction is the test
#'
#' @export
#' @return list
hypergeometric_basic <- function(num_white, num_black, num_drawn, num_white_drawn, direction = "over"){
n_2_1 <- num_white - num_white_drawn
n_1_2 <- num_drawn - num_white_drawn
n_2_2 <- num_black - n_1_2
odds_ratio <- (num_white_drawn * n_2_2) / (n_1_2 * n_2_1)
expected <- ((num_white_drawn + n_1_2) * (num_white_drawn + n_2_1)) / (num_white_drawn + n_1_2 + n_2_1 + n_2_2)
p_values <- switch(direction,
over = phyper(num_white_drawn - 1L, num_white, num_black, num_drawn, lower.tail = FALSE),
under = phyper(num_white_drawn, num_white, num_black, num_drawn, lower.tail = TRUE)
)
list(p = p_values, odds = odds_ratio, expected = expected)
}
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