added modifications for iqwidth and correlation plots

R/CorrelationMethods.R

@@ -486,10 +486,10 @@ pairs.DataFrame <- function (x, labels, panel = points, ..., horInd = 1:nc, verI
                              , tagCountThreshold, applyThresholdBoth
                              , digits) {
   # Select samples
-  if (all(samples %in% colnames(expr.table))) {
-    expr.table <- expr.table[,samples]
-  } else if(samples == "all"){
+  if(samples == "all"){
     samples <- colnames(expr.table)
+  } else if (all(samples %in% colnames(expr.table))) {
+    expr.table <- expr.table[,samples]
   } else stop("'samples' parameter must be either \"all\" or a character vector of valid sample labels!")
   nr.samples <- length(samples)
 
@@ -540,16 +540,18 @@ pairs.DataFrame <- function (x, labels, panel = points, ..., horInd = 1:nc, verI
     points(df, ...)
   }
 
-  pairs( expr.table
-       , lower.panel = pointsUnique
-       , upper.panel = panel.cor
-       , pch = "."
-       , cex = 4
-       , log = "xy"
-       , las = 1
-       , xaxp = c(1,10,1)
-       , yaxp = c(1,10,1)
-       , labels = samples)
+  if (TOPLOT){
+    pairs( expr.table
+        , lower.panel = pointsUnique
+        , upper.panel = panel.cor
+        , pch = "."
+        , cex = 4
+        , log = "xy"
+        , las = 1
+        , xaxp = c(1,10,1)
+        , yaxp = c(1,10,1)
+        , labels = samples)
+  }
 
   # Return a correlation matrix
   corr.m <- matrix(1, nr.samples, nr.samples)

R/ExportMethods.R

@@ -101,6 +101,7 @@ setGeneric( "plotReverseCumulatives",
     group <- "group"
   }
 
+  # no need for colors if a multi-facet plot and many colors
   if (is.null(object@metadata$colData$Colors)) {
     object@metadata$colData$Colors <- scales::hue_pal()(length(object))
   }
@@ -230,8 +231,8 @@ setMethod("plotReverseCumulatives", "GRanges",
 #' @family CAGEr plot functions
 #' @family CAGEr clusters functions
 #' 
-#' @importFrom ggplot2 ggplot scale_fill_manual geom_histogram facet_wrap
-#' @importFrom ggplot2 ggtitle xlab ylab labs
+#' @importFrom ggplot2 ggplot aes_string scale_fill_manual geom_histogram facet_wrap
+#' @importFrom ggplot2 ggtitle xlab ylab
 #' 
 #' @examples
 #' 
@@ -278,17 +279,22 @@ setMethod( "plotInterquantileWidth", "CAGEexp"
 
 	binsize <- round(max(iqwidths$iq_width)/2)
 
-	ggplot2::ggplot(iqwidths) +
-	  ggplot2::aes_string(x = "iq_width", fill = "sampleName") +
-	  ggplot2::scale_fill_manual(values = names(sampleLabels(object))) +
-	  ggplot2::geom_histogram(bins = binsize) +
-	  ggplot2::facet_wrap("~sampleName") +
-	  ggplot2::ggtitle(paste0(
+	iqwidth_plot <- ggplot(iqwidths) +
+	  aes_string(x = "iq_width") +
+	  scale_fill_manual(values = names(sampleLabels(object))) +
+	  geom_histogram(bins = binsize) +
+	  facet_wrap("~sampleName") +
+	  ggtitle(paste0(
 	    switch(clusters, tagClusters = "Tag Clusters", consensusClusters = "Consenss Clusters"),
 	    " interquantile width (quantile ", qLow, " to ", qUp, ")")) +
-	  ggplot2::xlab("Interquantile width (bp)") +
-	  ggplot2::ylab("Frequency") +
-	  ggplot2::labs(fill = "Sample name")
+	  xlab("Interquantile width (bp)") +
+	  ylab("Frequency")
+
+    if (TOPLOT){
+      print(iqwidth_plot)
+    }
+
+    return(iqwidth_plot)
 })
 
 #' @name plotExpressionProfiles