diff --git a/NAMESPACE b/NAMESPACE
index 685d468..49d5bdf 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -12,7 +12,6 @@ export(analyze)
 export(clustering)
 export(compare)
 export(correlation)
-export(densest)
 export(method)
 export(neural)
 export(optimal_weights)
diff --git a/R/adjacency.R b/R/adjacency.R
index 6d2a1e6..06c47fd 100644
--- a/R/adjacency.R
+++ b/R/adjacency.R
@@ -1,31 +1,7 @@
-#' Find the densest value in the data.
-#'
-#' This function assumes that data represents a continuous variable and finds
-#' a single value with the highest estimated density. This can be used to
-#' estimate the mode of the data. If there is only one value that value is
-#' returned. If multiple density maxima with the same density exist, their mean
-#' is returned.
-#'
-#' @param data The input data.
-#'
-#' @return The densest value of data.
-#'
-#' @export
-densest <- function(data) {
-    as.numeric(if (length(data) <= 0) {
-        NULL
-    } else if (length(data) == 1) {
-        data
-    } else {
-        density <- stats::density(data)
-        mean(density$x[density$y == max(density$y)])
-    })
-}
-
 #' 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. See [densest()] for the default implementation.
+#'   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.
@@ -33,7 +9,7 @@ densest <- function(data) {
 #' @return An object of class `geposan_method`.
 #'
 #' @export
-adjacency <- function(estimate = densest, combination = min) {
+adjacency <- function(estimate = stats::median, combination = min) {
     method(
         id = "adjacency",
         name = "Adjacency",
diff --git a/man/adjacency.Rd b/man/adjacency.Rd
index f68d759..bc0a724 100644
--- a/man/adjacency.Rd
+++ b/man/adjacency.Rd
@@ -4,11 +4,11 @@
 \alias{adjacency}
 \title{Score genes based on their proximity to the reference genes.}
 \usage{
-adjacency(estimate = densest, combination = min)
+adjacency(estimate = stats::median, combination = min)
 }
 \arguments{
 \item{estimate}{A function that will be used to summarize the distance
-values for each gene. See \code{\link[=densest]{densest()}} for the default implementation.}
+values for each gene. By default, \code{\link[=median]{median()}} is used.}
 
 \item{combination}{A function that will be used to combine the different
 distances to the reference genes. By default \code{\link[=min]{min()}} is used. That means
diff --git a/man/densest.Rd b/man/densest.Rd
deleted file mode 100644
index 252c6f1..0000000
--- a/man/densest.Rd
+++ /dev/null
@@ -1,21 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/adjacency.R
-\name{densest}
-\alias{densest}
-\title{Find the densest value in the data.}
-\usage{
-densest(data)
-}
-\arguments{
-\item{data}{The input data.}
-}
-\value{
-The densest value of data.
-}
-\description{
-This function assumes that data represents a continuous variable and finds
-a single value with the highest estimated density. This can be used to
-estimate the mode of the data. If there is only one value that value is
-returned. If multiple density maxima with the same density exist, their mean
-is returned.
-}