R/GeneratePRC.R

In OscarBrock/gCrisprTools: Suite of Functions for Pooled Crispr Screen QC and Analysis

##' @title Generate a Precision-Recall Curve from a CRISPR screen  
##' @description Given a set of targets of interest, this function generates a Precision Recall curve from the results of 
##' a CRISPR screen. Specifically, it orders the target elements in the screen in the specified direction, and then plots the recall 
##' rate (proportion of true targets identified) against the precision (proportion of identified targets that are true targets). 
##' 
##' Note that ranking statistics in CRISPR screens are (usually) permutation-based, and so some granularity in the rankings is expected. This 
##' function does a little extra work to ensure that hits are counted as soon as the requisite value of the ranking statistic is reached 
##' regardless of where the gene is located within the block of equally-significant genes. Functionally, this means that the drawn curve is
##' somewhat anticonservative in cases where the gene ranks are not well differentiated.  
##'
##' @param summaryDF A dataframe summarizing the results of the screen, returned by the function \code{\link{ct.generateResults}}. 
##' @param target.list A character vector containing the names of the targets to be tested; by default these are assumed to be `geneID`s, 
##' but specifying `collapse=geneSymbol` enables setting on `geneSymbol` by passing that value through to `ct.simpleResult`.
##' @param direction Direction by which to order target signals (`enrich` or `deplete`).  
##' @param plot.it Logical value indicating whether to plot the curves. 
##' @return A list containing the the x and y coordinates of the curve.
##' @author Russell Bainer
##' @examples data('resultsDF')
##' data('essential.genes') #Note that this is an artificial example.
##' pr <- ct.PRC(resultsDF, essential.genes, 'enrich')
##' str(pr)
##' @export
ct.PRC <- function(summaryDF, target.list, direction = c("enrich", "deplete"), plot.it = TRUE) {

    direction <- match.arg(direction)
    stopifnot(is(plot.it, "logical"))

    if (!is.character(target.list)) {
        warning("Supplied target.list is not a character vector. Coercing.")
        target.list <- as.character(target.list)
    }

    # Infer whether Gsdb is ID or feature centric
    gids <- sum(target.list %in% summaryDF$geneID)
    gsids <- sum(target.list %in% summaryDF$geneSymbol)

    if (all(c(gsids, gids) == 0)) {
        stop("None of the features in the GeneSetDb are present in either the geneID or geneSymbol slots of the first provided result.")
    }

    collapse <- ifelse(gids > gsids, "geneID", "geneSymbol")
    simpleDF <- ct.simpleResult(summaryDF, collapse)

    present <- intersect(target.list, row.names(simpleDF))

    if (length(present) != length(target.list)) {
        if (length(present) < 1) {
            stop(paste0("None of the genes in the input list are present in the ", collapse, " column of the input data.frame."))
        }
        warning(length(present), " of ", length(target.list), " genes are present in the supplied results data.frame. Ignoring the remainder of the target.list.")
    }

    # Subset signals
    values <- simpleDF[simpleDF$direction == direction, ]
    values <- c(values$best.p[order(values$best.p, decreasing = FALSE)], rep(1, times = sum(!(simpleDF$direction %in% direction))))

    targvals <- vapply(target.list, function(x) {
        ifelse(simpleDF[x, "direction"] %in% direction, simpleDF[x, "best.p"], 1)
    }, numeric(1))

    out <- list()
    out$precision <- c(1, unlist(lapply(unique(values), function(x) {
        sum(targvals <= x, na.rm = TRUE)/sum(values <= x, na.rm = TRUE)
    })), 0)
    out$recall <- c(0, unlist(lapply(unique(values), function(x) {
        sum(targvals <= x, na.rm = TRUE)/length(targvals)
    })), 1)

    enrich <- switch(direction, enrich = ct.targetSetEnrichment(simpleDF, target.list, enrich = TRUE, collapse = collapse), deplete = ct.targetSetEnrichment(simpleDF, 
        target.list, enrich = FALSE, collapse = collapse))
    out <- c(out, enrich)

    # Plot it?
    if (plot.it) {
        plot(out$recall, out$precision, xlim = c(0, 1), ylim = c(0, 1), type = "l", ylab = "Precision", xlab = "Recall", main = paste("Precision and Recall of", deparse(substitute(target.list))), 
            col = "blue", lwd = 3)
    }
    return(invisible(out))
}