Add in latest dev changes

.travis.yml

@@ -10,6 +10,7 @@ env:
     - R_BUILD_ARGS="--no-build-vignettes --no-manual"
     - R_CHECK_ARGS="--no-build-vignettes --no-manual --timings"
     - _R_CHECK_TIMINGS_="0"
+    - R_DEFAULT_INTERNET_TIMEOUT="300"
 
 r:
   - release

R/ggeplot.R

@@ -10,22 +10,26 @@
 #' @importFrom ggplot2 qplot aes geom_rug geom_hline geom_vline annotate theme element_text element_blank element_line element_rect
 #' 
 #' @export
-ggeplot <- function(n, positions, x_axis, y_axis, title="") {
-    score <- which.max(abs(y_axis))
-    qplot(x_axis, 
-          y_axis,
-          main=title,
-          ylab="Running Enrichment Score", 
-          xlab="Position in Ranked List of Genes",
-          geom="line")+
-    geom_rug(data=data.frame(positions), aes(x=positions), inherit.aes=FALSE)+
-    geom_hline(yintercept=0) +
-    geom_vline(xintercept=n/2, linetype="dotted") +
-    annotate("point", x=x_axis[score], y=y_axis[score], color="red") +
-    annotate("text", x=x_axis[score]+n/20, y=y_axis[score], label=round(y_axis[score],2)) +
-    annotate("point", x=x_axis[score], y=y_axis[score], color="red") +
-    theme(plot.title=element_text(hjust=0.5),
-          panel.background=element_blank(), 
-          axis.line=element_line(color="black"),
-          panel.border=element_rect(color="black", fill=NA, size=1))    
+ggeplot <- function(n, positions, x_axis, y_axis, title = "") {
+  score <- which.max(abs(y_axis))
+  DF <- data.frame(x_axis = x_axis, y_axis = y_axis)
+  ggplot2::ggplot(DF, aes(x = x_axis, y = y_axis)) +
+    ggplot2::geom_line() +
+    ggplot2::labs(
+      title = title,
+      y = "Running Enrichment Score",
+      x = "Position in Ranked List of Genes"
+    ) +
+    ggplot2::geom_rug(data = data.frame(positions), aes(x = positions), inherit.aes = FALSE) +
+    ggplot2::geom_hline(yintercept = 0) +
+    ggplot2::geom_vline(xintercept = n / 2, linetype = "dotted") +
+    ggplot2::annotate("point", x = x_axis[score], y = y_axis[score], color = "red") +
+    ggplot2::annotate("text", x = x_axis[score] + n / 20, y = y_axis[score], label = round(y_axis[score], 2)) +
+    ggplot2::annotate("point", x = x_axis[score], y = y_axis[score], color = "red") +
+    ggplot2::theme(
+      plot.title = ggplot2::element_text(hjust = 0.5),
+      panel.background = ggplot2::element_blank(),
+      axis.line = ggplot2::element_line(color = "black"),
+      panel.border = ggplot2::element_rect(color = "black", fill = NA, linewidth = 1)
+    )
 }

R/ggvenn.R

@@ -37,7 +37,7 @@ ggvenn <- function(a, b, ga, gb, title="") {
                         paste(gb, " (", x.b, ")", sep=""))) %>%
 
     ggplot(aes(x0=x, y0=y, r=c(r.a, r.b), fill=groups)) +
-    geom_circle(alpha=0.3, size=0.5) +
+    geom_circle(alpha=0.3, linewidth=0.5) +
     coord_fixed() +
     theme_void() +
     theme(plot.title=element_text(hjust=0.5),

R/hype.R

@@ -117,8 +117,8 @@ hypeR <- function(signature,
           weights <- NULL
           signature.type <- "ranked"
         }
-        data <- data.frame(matrix(ncol=7, nrow=0))
-        colnames(data) <- c("label", "pval", "fdr", "signature", "geneset", "overlap", "score")
+        data <- data.frame(matrix(ncol=8, nrow=0))
+        colnames(data) <- c("label", "score", "pval", "fdr", "geneset", "signature", "overlap", "hits")
         results <- .ks_enrichment(signature=signature, 
                                   genesets=gsets.obj$genesets,
                                   weights=weights, 

R/ks_enrichment.R

@@ -16,75 +16,84 @@
                     y, 
                     weights=NULL,
                     weights.pwr=1,
-                    absolute=FALSE, 
+                    absolute=FALSE, # this is not really implemented, should be removed
                     plotting=FALSE, 
-                    plot.title="") {
-
-    n.y <- length(y)
-    err = list(score=0, pval=1, plot=ggempty())
-    if (n.y < 1 ) return(err)
-    if (any(y > n.x)) return(err)
-    if (any(y < 1)) return(err)
-
-    x.axis <- y.axis <- NULL
+                    plot.title="") 
+{
+  n.y <- length(y)
+  err <- list(score = 0, pval = 1, leading_edge = NULL, leading_hits = NULL, plot = ggempty())
+  if (n.y < 1 || any(y > n.x) || any(y < 1) ) {
+    return(err)
+  }
+  x.axis <- y.axis <- NULL
+  leading_edge <- NULL # recording the x corresponding to the highest y value
+
+  ## If weights are provided
+  if ( !is.null(weights) ) {
+    weights <- abs(weights[y])^weights.pwr
 
-    # If weights are provided
-    if (!is.null(weights)) {
-        weights <- abs(weights[y])^weights.pwr
+    Pmis <- rep(1, n.x); Pmis[y] <- 0; Pmis <- cumsum(Pmis); Pmis <- Pmis/(n.x-n.y)
+    Phit <- rep(0, n.x); Phit[y] <- weights; Phit <- cumsum(Phit); Phit <- Phit/Phit[n.x]
+    z <- Phit-Pmis
 
-        Pmis <- rep(1, n.x); Pmis[y] <- 0; Pmis <- cumsum(Pmis); Pmis <- Pmis/(n.x-n.y)
-        Phit <- rep(0, n.x); Phit[y] <- weights; Phit <- cumsum(Phit); Phit <- Phit/Phit[n.x]
-        z <- Phit-Pmis
+    score <- if (absolute) max(z)-min(z) else z[leading_edge <- which.max(abs(z))]
 
-        score <- if (absolute) max(z)-min(z) else z[which.max(abs(z))]
-
-        x.axis <- 1:n.x
-        y.axis <- z
+    x.axis <- 1:n.x
+    y.axis <- z
+  } 
+  ## Without weights
+  else {
+    y <- sort(y)
+    n <- n.x*n.y/(n.x + n.y)
+    hit <- 1/n.y
+    mis <- 1/n.x
 
-    # Without weights
-    } else {
-        y <- sort(y)
-        n <- n.x*n.y/(n.x + n.y)
-        hit <- 1/n.y
-        mis <- 1/n.x
-
-        Y <- sort(c(y-1, y))
-        Y <- Y[diff(Y) != 0]
-        y.match <- match(y, Y)
-        D <- rep(0, length(Y))
-        D[y.match] <- (1:n.y)
-        zero <- which(D == 0)[-1]
-        D[zero] <- D[zero-1]
-
-        z <- D*hit-Y*mis
-
-        score <- if (absolute) max(z)-min(z) else z[which.max(abs(z))]
-
-        x.axis <- Y
-        y.axis <- z
-
-        if (Y[1] > 0) {
-            x.axis <- c(0, x.axis)
-            y.axis <- c(0, y.axis)
-        }
-        if (max(Y) < n.x) {
-            x.axis <- c(x.axis, n.x)
-            y.axis <- c(y.axis, 0)
-        }    
-    }
+    Y <- sort(c(y-1, y))    # append the positions preceding hits
+    Y <- Y[diff(Y) != 0]    # remove repeated position
+    y.match <- match(y, Y)  # find the hits' positions
+    D <- rep(0, length(Y))
+    D[y.match] <- (1:n.y)
+    zero <- which(D == 0)[-1]
+    D[zero] <- D[zero-1]
 
-    # One-sided Kolmogorov–Smirnov test
-    results <- suppressWarnings(ks.test(1:n.x, y, alternative="less"))
-    results$statistic <- score  # Use the signed statistic
-
-    # Enrichment plot
-    p <- if (plotting) ggeplot(n.x, y, x.axis, y.axis, plot.title) else ggempty()
-
-    return(list(score=as.numeric(results$statistic), 
-                pval=results$p.value, 
-                plot=p))
+    z <- D*hit-Y*mis
+
+    score <- if (absolute) max(z)-min(z) else z[leading_edge <- which.max(abs(z))]
+
+    x.axis <- Y
+    y.axis <- z
+
+    if (Y[1] > 0) {
+      x.axis <- c(0, x.axis)
+      y.axis <- c(0, y.axis)
+    }
+    if (max(Y) < n.x) {
+      x.axis <- c(x.axis, n.x)
+      y.axis <- c(y.axis, 0)
+    }    
+  }
+  leading_edge <- x.axis[leading_edge]
+  leading_hits <- intersect(x.axis[x.axis <= leading_edge], y)
+
+  ## One-sided Kolmogorov–Smirnov test
+  results <- suppressWarnings(ks.test(1:n.x, y, alternative="less"))
+  results$statistic <- score  # Use the signed statistic
+
+  ## Enrichment plot
+  p <- if (plotting && n.y > 0) {
+    ggeplot(n.x, y, x.axis, y.axis, plot.title) +
+      geom_vline(xintercept = leading_edge, linetype = "dotted", color = "red", linewidth = 0.25)
+  } else {
+    ggempty()
+  }
+  return(list(
+    score = as.numeric(results$statistic),
+    pval = results$p.value,
+    leading_edge = leading_edge,
+    leading_hits = leading_hits,
+    plot = p
+  ))
 }
-
 #' Enrichment test via one-sided Kolmogorov–Smirnov test
 #' 
 #' @param signature A vector of ranked symbols
@@ -96,48 +105,63 @@
 #' @return A list of data and plots
 #' 
 #' @keywords internal
-.ks_enrichment <- function(signature,
-                           genesets,
-                           weights=NULL,
-                           weights.pwr=1,
-                           absolute=FALSE,
-                           plotting=TRUE) {
-
-    if (!is(genesets, "list")) stop("Error: Expected genesets to be a list of gene sets\n")
-    if (!is.null(weights)) stopifnot(length(signature) == length(weights))
-
-    signature <- unique(signature)
-    genesets <- lapply(genesets, unique)
+.ks_enrichment <- function(
+    signature,
+    genesets,
+    weights = NULL,
+    weights.pwr = 1,
+    absolute = FALSE,
+    plotting = TRUE) 
+{
+  if (!is(genesets, "list")) stop("Error: Expected genesets to be a list of gene sets\n")
+  if (!is.null(weights)) stopifnot(length(signature) == length(weights))
 
-    results <- mapply(function(geneset, title) {
+  signature <- unique(signature)
+  genesets <- lapply(genesets, unique)
 
-                    ranks <- match(geneset, signature)
-                    ranks <- ranks[!is.na(ranks)]
-
-                    # Run ks-test
-                    results <- .kstest(n.x=length(signature), 
-                                       y=ranks,
-                                       weights=weights,
-                                       weights.pwr=weights.pwr,
-                                       absolute=absolute, 
-                                       plotting=plotting,
-                                       plot.title=title)
-
-                    results[['geneset']] <- length(geneset)
-                    results[['overlap']] <- length(ranks)
-                    return(results)
+  results <- mapply( function(geneset, title) {
+    ranks <- match(geneset, signature)
+    ranks <- ranks[!is.na(ranks)]
 
-    }, genesets, names(genesets), USE.NAMES=TRUE, SIMPLIFY=FALSE)
+    ## Run ks-test
+    results_in <- .kstest(
+      n.x = length(signature),
+      y = ranks,
+      weights = weights,
+      weights.pwr = weights.pwr,
+      absolute = absolute,
+      plotting = plotting,
+      plot.title = title
+    )
+    #results_in[["geneset"]] <- length(geneset)
+    results_in[["geneset"]] <- length(intersect(geneset, signature))
+    results_in[["overlap"]] <- length(results_in$leading_hits)
+    return(results_in)
+  }, genesets, names(genesets), USE.NAMES = TRUE, SIMPLIFY = FALSE)
 
-    results <- do.call(rbind, results)
-    data <- data.frame(apply(results[,c("score", "pval", "geneset", "overlap")], 2, unlist), stringsAsFactors=FALSE)
-    data$score <- signif(data$score, 2)
-    data$pval <- signif(data$pval, 2)
-    data$fdr <- signif(p.adjust(data$pval, method="fdr"), 2)
-    data$label <- names(genesets)
-    data$signature <- length(signature)
-    data <- data[,c("label", "pval", "fdr", "signature", "geneset", "overlap", "score")]
-    plots <- results[,"plot"]
-
-    return(list(data=data, plots=plots))
+  results <- do.call(rbind, results)
+  data <- data.frame(apply(results[, c("score", "pval", "geneset", "overlap")], 2, unlist),
+    stringsAsFactors = FALSE
+  )
+  ## add list of genes in the leading edge
+  data <- data %>%
+    #dplyr::mutate(hits = sapply(results[, "leading_hits"], function(x) paste(signature[x], collapse = ",")))
+    dplyr::mutate(hits = sapply(results[, "leading_hits"], function(x) paste(signature[x], collapse = " , ")))
+  data$score <- signif(data$score, 2)
+  data$pval <- signif(data$pval, 2)
+  data$label <- names(genesets)
+  data$signature <- length(signature)
+  data$fdr <- signif(p.adjust(data$pval, method = "fdr"), 2)
+  data <- data %>%
+    dplyr::relocate(fdr, .after = pval) %>%
+    dplyr::relocate(signature, .after = geneset) %>%
+    dplyr::relocate(label) %>%
+    tibble::remove_rownames() # make sure this is OK
+  plots <- results[, "plot"]
+
+  return(list(
+    data = data,
+    plots = plots,
+    leading_hits = sapply(results[, "leading_hits"], function(x) signature[x])
+  ))
 }

tests/testthat/test-hyp_dots.R

@@ -7,7 +7,7 @@ hyp_dots_tests <- function(hyp_obj, return_obj=FALSE) {
     expect_silent(hyp_dots(hyp_obj, size_by="genesets"))
     expect_silent(hyp_dots(hyp_obj, size_by="significance"))
     expect_silent(hyp_dots(hyp_obj, size_by="none"))
-    p <- hyp_dots(hyp_obj, "gg")
+    p <- hyp_dots(hyp_obj)
     expect_is(p, "gg")
     if (return_obj) return(hyp_obj)
 }
@@ -17,11 +17,11 @@ test_that("hyp_dots() is working", {
     testdat <- readRDS(file.path(system.file("extdata", package="hypeR"), "testdat.rds"))
     gsets_obj <- testdat$gsets
     rgsets_obj <- testdat$rgsets
-    
+
     # Overrepresentation (signature)
     signature <- testdat$signature
     experiment <- testdat$experiment
-    
+
     hypeR(signature, gsets_obj, test="hypergeometric", background=100) %>%
     hyp_dots_tests()
     hypeR(signature, rgsets_obj, test="hypergeometric", background=100) %>%
@@ -31,7 +31,7 @@ test_that("hyp_dots() is working", {
     expect_equal(length(p), 3)
     expect_equal(names(p), c("Signature 1", "Signature 2", "Signature 3"))
     expect_is(p[["Signature 3"]], "gg")
-    
+
     # Enrichment (ranked signature)
     signature <- names(testdat$weighted_signature)
     experiment <- lapply(testdat$weighted_experiment, names)
@@ -45,11 +45,11 @@ test_that("hyp_dots() is working", {
     expect_equal(length(p), 3)
     expect_equal(names(p), c("Signature 1", "Signature 2", "Signature 3"))
     expect_is(p[["Signature 3"]], "gg")
-        
+
     # Enrichment (weighted signature)
     signature <- testdat$weighted_signature
     experiment <- testdat$weighted_experiment
-    
+
     hypeR(signature, gsets_obj, test="kstest") %>%
     hyp_dots_tests()
     hypeR(signature, rgsets_obj, test="kstest") %>%