Merge pull request #34 from fmicompbio/update-plotpairs

ADd option to include identity line in pairs plots; select points to …

Author: csoneson

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mutscan
 Title: Preprocessing and Analysis of Deep Mutational Scanning Data
-Version: 0.2.30
+Version: 0.2.31
 Authors@R: 
     c(person(given = "Charlotte",
              family = "Soneson",

NAMESPACE

@@ -68,6 +68,7 @@ importFrom(ggplot2,coord_cartesian)
 importFrom(ggplot2,element_blank)
 importFrom(ggplot2,element_text)
 importFrom(ggplot2,facet_wrap)
+importFrom(ggplot2,geom_abline)
 importFrom(ggplot2,geom_bar)
 importFrom(ggplot2,geom_density)
 importFrom(ggplot2,geom_histogram)

NEWS.md

@@ -1,3 +1,9 @@
+# mutscan 0.2.31
+
+* Add option to include identity line in pairs plots
+* Select points to label in result plots based on nominal p-value
+* Add option to manually set the correlation range for coloring pairs plots
+
 # mutscan 0.2.30
 
 * Swap to MIT license

R/plotPairs.R

@@ -32,11 +32,18 @@
 #'   opacity of points in the plot.
 #' @param colorByCorrelation Logical scalar, indicating whether the correlation
 #'   panels should be colored according to the correlation value.
+#' @param corrColorRange Numeric vector of length 2, providing the lower and 
+#'   upper limits of the color scale when coloring by correlation. Both 
+#'   values should be positive; the same range is used for negative 
+#'   correlations. If \code{NULL} (the default), the range is inferred from 
+#'   the data.
+#' @param addIdentityLine Logical scalar, indicating whether the identity line 
+#'   should be added (only used if \code{pointsType = "points"}).
 #'
 #' @importFrom GGally eval_data_col ggpairs wrap
 #' @importFrom ggplot2 ggplot annotate theme_void ylim stat_density2d
 #'   scale_fill_continuous geom_point theme_bw theme element_blank aes
-#'   geom_histogram scale_x_continuous scale_y_continuous
+#'   geom_histogram scale_x_continuous scale_y_continuous geom_abline
 #' @importFrom stats cor
 #' @importFrom SummarizedExperiment assayNames assay
 #' @importFrom grDevices hcl.colors rgb colorRamp
@@ -46,7 +53,8 @@ plotPairs <- function(se, selAssay = "counts", doLog = TRUE, pseudocount = 1,
                       corMethod = "pearson", histBreaks = 40,
                       pointsType = "points", corSizeMult = 5,
                       corSizeAdd = 2, pointSize = 0.1, pointAlpha = 0.3,
-                      colorByCorrelation = TRUE) {
+                      colorByCorrelation = TRUE, corrColorRange = NULL,
+                      addIdentityLine = FALSE) {
 
     .assertVector(x = se, type = "SummarizedExperiment")
     .assertScalar(x = selAssay, type = "character",
@@ -63,6 +71,12 @@ plotPairs <- function(se, selAssay = "counts", doLog = TRUE, pseudocount = 1,
     .assertScalar(x = pointSize, type = "numeric", rngExcl = c(0, Inf))
     .assertScalar(x = pointAlpha, type = "numeric", rngExcl = c(0, Inf))
     .assertScalar(x = colorByCorrelation, type = "logical")
+    .assertVector(x = corrColorRange, type = "numeric", rngIncl = c(0, 1), 
+                  len = 2, allowNULL = TRUE)
+    if (!is.null(corrColorRange)) {
+        stopifnot(corrColorRange[2] >= corrColorRange[1])
+    }
+    .assertScalar(x = addIdentityLine, type = "logical")
 
     ## ----------------------------------------------------------------------- ##
     ## Define shared theme elements
@@ -131,12 +145,22 @@ plotPairs <- function(se, selAssay = "counts", doLog = TRUE, pseudocount = 1,
     }
 
     ## Define function to create scatter plot (for use with ggpairs)
-    plotpoints <- function(data, mapping, ...) {
-        ggplot2::ggplot(data = data, mapping = mapping) +
-            ggplot2::geom_point(alpha = pointAlpha, size = pointSize) +
-            ggtheme
+    if (addIdentityLine) {
+        plotpoints <- function(data, mapping, ...) {
+            ggplot2::ggplot(data = data, mapping = mapping) +
+                ggplot2::geom_abline(slope = 1, intercept = 0, 
+                                     linetype = "dashed", color = "grey") + 
+                ggplot2::geom_point(alpha = pointAlpha, size = pointSize) +
+                ggtheme
+        }
+    } else {
+        plotpoints <- function(data, mapping, ...) {
+            ggplot2::ggplot(data = data, mapping = mapping) +
+                ggplot2::geom_point(alpha = pointAlpha, size = pointSize) +
+                ggtheme
+        }
     }
-
+    
     ## Define the function to use for the plots
     if (pointsType == "smoothscatter") {
         lower <- list(continuous = smoothscat)
@@ -176,7 +200,11 @@ plotPairs <- function(se, selAssay = "counts", doLog = TRUE, pseudocount = 1,
 
     ## Calculate correlations and get range
     allCors <- stats::cor(mat, method = corMethod)
-    corRange <- range(abs(allCors[upper.tri(allCors)]))
+    if (!is.null(corrColorRange)) {
+        corRange <- corrColorRange
+    } else {
+        corRange <- range(abs(allCors[upper.tri(allCors)]))
+    }
     if (length(unique(corRange)) == 1) {
         ## Having a range with width 0 leads to problems in the rescaling of the correlations
         corRange <- c(0, 1)