Update gene data based on the suggested ranking

This also exports the ranking function itself for external use.

man/genes.Rd

@@ -5,7 +5,7 @@
 \alias{genes}
 \title{A \code{data.table} containig data on genes and their expression behavior.}
 \format{
-An object of class \code{data.table} (inherits from \code{data.frame}) with 56156 rows and 13 columns.
+An object of class \code{data.table} (inherits from \code{data.frame}) with 56156 rows and 14 columns.
 }
 \usage{
 genes

man/rank_genes.Rd

@@ -0,0 +1,35 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/ranking.R
+\name{rank_genes}
+\alias{rank_genes}
+\title{Rank genes based on how ubiquitous they are.}
+\usage{
+rank_genes(
+  cross_sample_metric = "above_95",
+  cross_sample_weight = 0.5,
+  mean_expression_weight = 0.25,
+  sd_expression_weight = -0.25
+)
+}
+\arguments{
+\item{cross_sample_metric}{Metric to use for calculating the number of
+samples a gene is expressed in. One of \code{above_95}, \code{above_median} or
+\code{above_zero}.}
+
+\item{cross_sample_weight}{Weighting of the cross sample metric within the
+final score.}
+
+\item{mean_expression_weight}{Weighting of the gene's mean expression within
+the final score.}
+
+\item{sd_expression_weight}{Weighting of the standard deviation of the
+gene's expression within the final score.}
+}
+\value{
+A \code{data.table} with gene data as well as the scores, ranks and
+percentiles for each gene.
+}
+\description{
+This function will compute a weighted average across multiple metrics that
+define how ubiquitous a gene is based on its expression across samples.
+}