fix(dataProcessPlots, groupComparisonPlots): Migrate away from deprecated functions for ggplot

DESCRIPTION

@@ -37,7 +37,8 @@ Imports:
     graphics,
     methods,
     statmod,
-    parallel
+    parallel,
+    rlang
 Suggests: 
     BiocStyle,
     knitr,
@@ -53,7 +54,7 @@ biocViews: ImmunoOncology, MassSpectrometry, Proteomics, Software, Normalization
 LazyData: true
 URL: http://msstats.org
 BugReports: https://groups.google.com/forum/#!forum/msstats
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Encoding: UTF-8
 NeedsCompilation: no
 Packaged: 2017-10-20 02:13:12 UTC; meenachoi

NAMESPACE

@@ -106,6 +106,7 @@ importFrom(plotly,plot_ly)
 importFrom(plotly,style)
 importFrom(plotly,subplot)
 importFrom(preprocessCore,normalize.quantiles)
+importFrom(rlang,.data)
 importFrom(stats,dist)
 importFrom(stats,fitted)
 importFrom(stats,formula)

R/groupComparisonQCPlots.R

@@ -121,7 +121,7 @@ modelBasedQCPlots = function(
         slope = diff(y) / diff(x)
         int = y[1L] - slope * x[1L]
 
-        plot = ggplot(sub.residuals.table, aes(sample = residual)) +
+        plot = ggplot(sub.residuals.table, aes(sample = .data$residual)) +
             geom_point(stat = "qq", alpha = 0.8, 
                        shape = 20, size = dot.size) +
             scale_shape(solid=FALSE) + 
@@ -172,7 +172,7 @@ modelBasedQCPlots = function(
         sub.residuals.table = data.frame("residual" = sub.residuals, 
                                          "fitted" = sub.fitted)
 
-        plot = ggplot(aes_string(x = "fitted", y = "residual"), 
+        plot = ggplot(aes(x = .data$fitted, y = .data$residual), 
                        data = sub.residuals.table) +
             geom_point(size = dot.size, 
                        alpha = 0.5) +
@@ -263,4 +263,4 @@ groupComparisonQCPlots = function(data, type, axis.size = 10, dot.size = 3, widt
 
     modelBasedQCPlots(data, type, axis.size, dot.size, width, height, 
                                  which.Protein, address, FALSE)
-}
+}

R/msstats-package.R

@@ -1,6 +1,7 @@
 #' @import data.table
 ## usethis namespace: start
 #' @importFrom Rcpp sourceCpp
+#' @importFrom rlang .data
 ## usethis namespace: end
 #' @useDynLib MSstats, .registration=TRUE
 NULL

R/utils_dataprocess_plots.R

@@ -56,14 +56,14 @@
         type_color = "PEPTIDE"
     }
 
-    profile_plot = ggplot(input, aes_string(x = "RUN", y = "newABUNDANCE",
-                                            color = type_color, linetype = "FEATURE")) +
+    profile_plot = ggplot(data = input, aes(x = .data$RUN, y = .data$newABUNDANCE,
+                                            color = .data[[type_color]], linetype = .data$FEATURE)) +
         facet_grid(~LABEL) +
-        geom_line(size = 0.5)
+        geom_line(linewidth = 0.5)
 
     if (is_censored) {
         profile_plot = profile_plot +
-        geom_point(aes_string(x = "RUN", y = "newABUNDANCE", color = type_color, shape = "censored"),
+        geom_point(aes(x = .data$RUN, y = .data$newABUNDANCE, color = .data[[type_color]], shape = .data$censored),
                    data = input,
                    size = dot.size.profile) +
         scale_shape_manual(values = c(16, 1),
@@ -97,7 +97,7 @@
         scale_y_continuous(yaxis.name, limits = c(y.limdown, y.limup)) +
         geom_vline(xintercept = lineNameAxis + 0.5, colour = "grey", linetype = "longdash") +
         labs(title = unique(input$PROTEIN)) +
-        geom_text(data = groupNametemp, aes(x = RUN, y = ABUNDANCE, label = Name), 
+        geom_text(data = groupNametemp, aes(x = .data$RUN, y = .data$ABUNDANCE, label = .data$Name), 
                   size = text.size, 
                   angle = text.angle, 
                   color = "black") +
@@ -156,22 +156,22 @@
 
     num_features = data.table::uniqueN(input$FEATURE)
     profile_plot = ggplot(data = input, 
-                          aes_string(x = "RUN", y = "newABUNDANCE", 
-                                     color = "analysis", linetype = "FEATURE", 
-                                     size = "analysis")) +
+                          aes(x = .data$RUN, y = .data$newABUNDANCE, 
+                                     color = .data$analysis, linetype = .data$FEATURE, 
+                                     size = .data$analysis)) +
         facet_grid(~LABEL) +
-        geom_line(size = 0.5)
+        geom_line(linewidth = 0.5)
 
     if (is_censored) { # splitting into two layers to keep red above grey
         profile_plot = profile_plot +
             geom_point(data = input[input$PEPTIDE != "Run summary"], 
-                       aes_string(x = "RUN", y = "newABUNDANCE", 
-                                  color = "analysis", size = "analysis", 
-                                  shape = "censored")) +
+                       aes(x = .data$RUN, y = .data$newABUNDANCE, 
+                                  color = .data$analysis, size = .data$analysis, 
+                                  shape = .data$censored)) +
             geom_point(data = input[input$PEPTIDE == "Run summary"], 
-                       aes_string(x = "RUN", y = "newABUNDANCE", 
-                                  color = "analysis", size = "analysis", 
-                                  shape = "censored")) +
+                       aes(x = .data$RUN, y = .data$newABUNDANCE, 
+                                  color = .data$analysis, size = .data$analysis, 
+                                  shape = .data$censored)) +
             scale_shape_manual(values = c(16, 1), 
                                labels = c("Detected data",
                                           "Censored missing data"))
@@ -191,7 +191,7 @@
         geom_vline(xintercept = lineNameAxis + 0.5, 
                    colour = "grey", linetype = "longdash") +
         labs(title = unique(input$PROTEIN)) +
-        geom_text(data = groupNametemp, aes(x = RUN, y = ABUNDANCE, label = Name), 
+        geom_text(data = groupNametemp, aes(x = .data$RUN, y = .data$ABUNDANCE, label = .data$Name), 
                   size = text.size, 
                   angle = text.angle, 
                   color = "black") +
@@ -209,8 +209,8 @@
     } else {
         profile_plot = profile_plot +
             guides(color = color_guide) +
-            geom_point(aes_string(x = "RUN", y = "newABUNDANCE", size = "analysis",
-                                  color = "analysis"), data = input)
+            geom_point(aes(x = .data$RUN, y = .data$newABUNDANCE, size = .data$analysis,
+                                  color = .data$analysis), data = input)
     }
     profile_plot
 }
@@ -234,17 +234,17 @@
         plot_title = unique(input$PROTEIN)
     }
 
-    ggplot(input, aes_string(x = "RUN", y = "ABUNDANCE")) +
+    ggplot(input, aes(x = .data$RUN, y = .data$ABUNDANCE)) +
         facet_grid(~LABEL) +
-        geom_boxplot(aes_string(fill = "LABEL"), outlier.shape = 1,
+        geom_boxplot(aes(fill = .data$LABEL), outlier.shape = 1,
                      outlier.size = 1.5) +
         scale_fill_manual(values = label.color, guide = "none") +
         scale_x_discrete("MS runs", breaks = cumGroupAxis) +
         scale_y_continuous(yaxis.name, limits = c(y.limdown, y.limup)) +
         geom_vline(xintercept = lineNameAxis + 0.5, colour = "grey",
                    linetype = "longdash") +
         labs(title  =  plot_title) +
-        geom_text(data = groupName, aes(x = RUN, y = ABUNDANCE, label = Name),
+        geom_text(data = groupName, aes(x = .data$RUN, y = .data$ABUNDANCE, label = .data$Name),
                   size = text.size, angle = text.angle, color = "black") +
         theme_msstats("QCPLOT", x.axis.size, y.axis.size,
                       legend_size = NULL)
@@ -268,8 +268,8 @@
         input$Label = as.numeric(gsub("\\D", "", unique(input$Label)))
     }
 
-    plot = ggplot(aes_string(x = "Label", y = "Mean"), data = input) +
-        geom_errorbar(aes(ymax = Mean + ciw, ymin = Mean - ciw),
+    plot = ggplot(aes(x = .data$Label, y = .data$Mean), data = input) +
+        geom_errorbar(aes(ymax = .data$Mean + .data$ciw, ymin = .data$Mean - .data$ciw),
                       data = input, width = 0.1, colour = "red") +
         geom_point(size = dot.size.condition, colour = "darkred")
 
@@ -283,9 +283,9 @@
     plot = plot +
         scale_y_continuous(yaxis.name, limits = c(y.limdown, y.limup)) +
         geom_hline(yintercept = 0, linetype = "twodash", 
-                   colour = "darkgrey", size = 0.6) +
+                   colour = "darkgrey", linewidth = 0.6) +
         labs(title = unique(single_protein$PROTEIN)) +
         theme_msstats("CONDITIONPLOT", x.axis.size, y.axis.size, 
                       text_angle = text.angle)
     plot
-}
+}

R/utils_groupcomparison_plots.R

@@ -189,10 +189,10 @@ colMin <- function(data) sapply(data, min, na.rm = TRUE)
     legend.size, log_adjp
 ) {
     Protein = NULL
-    plot = ggplot(aes_string(x = "logFC", 
-                             y = log_adjp,
-                             color = "colgroup",
-                             label = "Protein"),
+    plot = ggplot(aes(x = .data$logFC, 
+                             y = .data[[log_adjp]],
+                             color = .data$colgroup,
+                             label = .data$Protein),
                   data = input) +
         geom_point(size = dot.size) +
         scale_colour_manual(values = c("gray65", "blue", "red"), 
@@ -209,7 +209,7 @@ colMin <- function(data) sapply(data, min, na.rm = TRUE)
         if (!(length(unique(input$colgroup)) == 1 & any(unique(input$colgroup) == "black"))) {
             plot = plot +
                 geom_text_repel(data = input[input$colgroup != "black", ],
-                                aes(label = Protein),
+                                aes(label = .data$Protein),
                                 size = text.size,
                                 col = "black")
         }
@@ -226,9 +226,9 @@ colMin <- function(data) sapply(data, min, na.rm = TRUE)
     if (!FCcutoff) {
         plot = plot +
             geom_line(data = sigcut,
-                      aes_string(x = "logFC", y = log_adjp, linetype = "line"),
+                      aes(x = .data$logFC, y = .data[[log_adjp]], linetype = .data$line),
                       colour = "darkgrey",
-                      size = 0.6,
+                      linewidth = 0.6,
                       show.legend = TRUE) +
             scale_linetype_manual(values = c("twodash" = 6),
                                   labels = c(paste0("Adj p-value cutoff (", sig, ")"))) +
@@ -248,19 +248,19 @@ colMin <- function(data) sapply(data, min, na.rm = TRUE)
                                         c("Protein", "logFC", log_adjp, "line"))
         plot = plot +
             geom_line(data = sigcut, 
-                      aes_string(x = "logFC", y = log_adjp, linetype = "line"),
+                      aes(x = .data$logFC, y = .data[[log_adjp]], linetype = .data$line),
                       colour = "darkgrey",
-                      size = 0.6,
+                      linewidth = 0.6,
                       show.legend = TRUE) +
             geom_line(data = FCcutpos,
-                      aes_string(x = "logFC", y = log_adjp, linetype = "line"),
+                      aes(x = .data$logFC, y = .data[[log_adjp]], linetype = .data$line),
                       colour = "darkgrey",
-                      size = 0.6,
+                      linewidth = 0.6,
                       show.legend = TRUE) +
             geom_line(data = FCcutneg,
-                      aes_string(x = "logFC", y = log_adjp, linetype = "line"),
+                      aes(x = .data$logFC, y = .data[[log_adjp]], linetype = .data$line),
                       colour = "darkgrey",
-                      size = 0.6) +
+                      linewidth = 0.6) +
             scale_linetype_manual(values = c("dotted" = 3, "twodash" = 6),
                                   labels = c(paste0("Fold change cutoff (", FCcutoff, ")"),
                                              paste0("Adj p-value cutoff (", sig, ")"))) +
@@ -288,8 +288,8 @@ colMin <- function(data) sapply(data, min, na.rm = TRUE)
     logFC = ciw = NULL
 
     protein = unique(input$Protein)
-    plot = ggplot(input, aes_string(x = "Label", y = "logFC")) +
-        geom_errorbar(aes(ymax = logFC + ciw, ymin = logFC - ciw),
+    plot = ggplot(input, aes(x = .data$Label, y = .data$logFC)) +
+        geom_errorbar(aes(ymax = .data$logFC + .data$ciw, ymin = .data$logFC - .data$ciw),
                       data = input,
                       width = 0.1,
                       colour = "red") +
@@ -299,7 +299,7 @@ colMin <- function(data) sapply(data, min, na.rm = TRUE)
         geom_hline(yintercept = 0, 
                    linetype = "twodash", 
                    colour = "darkgrey", 
-                   size = 0.6) +
+                   linewidth = 0.6) +
         labs(title = protein) +
         theme_msstats("COMPARISONPLOT", x.axis.size, y.axis.size, 
                       text_angle = text.angle, text_hjust = hjust, 
@@ -308,4 +308,4 @@ colMin <- function(data) sapply(data, min, na.rm = TRUE)
         scale_y_continuous(paste0("Log", log_base, "-Fold Change"),
                            limits = c(y.limdown, y.limup))
     plot
-}
+}