```
#' @title Calculate enriched terms in a target set
#'
#' @description Given a target set of articles under question, we wish to compare the frequencies of term occurance to a control set of articles. We set a threshold above which to investigate terms (setting this threshold higher reduces spurious associated but decreases power to identify true associations) and calculate the enrichment and the P value of association (see \code{\link{hgt}} for more details).
#'
#' @details This function mimics a truncated version of the output of \href{https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-10-48}{GOrilla} by identifying and quantifying the enrichment of terms in a target set of articles. Given N articles and B associations of the given term, the enrichment of b terms in the n articles in the target set is given by \eqn{\frac{\frac{b}{n}}{\frac{B}{N}}}.
#'
#' @param target Set of \code{\link{goldi}} output for a target set of articles.
#' @param control Set of \code{\link{goldi}} output for a control set of articles.
#' @param threshold Only investigate associations which have been founder greater than this number of times.
#' @param correction Correction to impliment on association P values. Users may choose any value which \code{\link[stats]{p.adjust}} may accept.
#'
#' @references Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z. (2009). GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics, 10(1), 1–7. http://doi.org/10.1186/1471-2105-10-48
#'
#' @return A formated data.frame with three columns: terms, enrichments, and P values.
#'
#' @export
enrichment <- function(target, control, threshold, correction = "fdr"){
# Summarise the target set
target %<>%
as.data.frame() %>%
group_by_("V1") %>%
summarise_(length = "length(V1)") %>%
filter(length > threshold) %>%
arrange(-length)
control %<>%
as.data.frame %>%
group_by_("V1") %>%
summarise_(length = "length(V1)") %>%
arrange(-length)
results <- data.frame(Term = character(), Enrichment = double(), P = double(), stringsAsFactors = F)
for(i in target$V1) {
row <- nrow(results)+1
i <- as.character(i)
N = nrow(control) + nrow(target)
.n = nrow(target)
B = nrow(control[control$V1 == i,]) + target$length[row]
.b = target$length[row]
p = hgt(.b, N, B, .n)
e = (.b / .n) / (B / N)
results[row, "Term"] <- as.character(i)
results[row, "Enrichment"] <- e
results[row, "P"] <- p
}
results$P <- p.adjust(results$P, method = correction)
return(results)
}
```

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