feat(plotting): Refactor QC plot headings to be compatible for protein turnover

R/dataProcessPlots.R

@@ -261,15 +261,10 @@ dataProcessPlots = function(
                             labels = seq(1, length(unique(RUN))))]
   summarized[, RUN := as.numeric(RUN)]
 
-  ## Meena :due to GROUP=0 for labeled.. extra care required.
   tempGroupName = unique(processed[, c("GROUP", "RUN")])
-  if (length(unique(processed$LABEL)) == 2) {
-    tempGroupName = tempGroupName[GROUP != '0']
-  } 
-  tempGroupName = tempGroupName[order(RUN), ] ## Meena : should we order by GROUP or RUN? I guess by RUn, because x-axis is by RUN
+  tempGroupName = tempGroupName[order(RUN), ]
   level.group = as.character(unique(tempGroupName$GROUP))
-  tempGroupName$GROUP = factor(tempGroupName$GROUP,
-                                levels = level.group) ## Meena : factor GROUP again, due to 1, 10, 2, ... if you have better way, please change
+  tempGroupName$GROUP = factor(tempGroupName$GROUP, levels = level.group)
 
   groupAxis = as.numeric(xtabs(~GROUP, tempGroupName))
   cumGroupAxis = cumsum(groupAxis)
@@ -291,16 +286,22 @@ dataProcessPlots = function(
                          Name = levels(tempGroupName$GROUP))
 
 
-  if (length(unique(processed$LABEL)) == 2) {
-    processed[, LABEL := factor(LABEL, labels = c("Reference", "Endogenous"))]
+  if ("is_labeled_ref" %in% colnames(processed)) {
+    processed[, LABEL := factor(
+      ifelse(is_labeled_ref, "Reference", "Endogenous"),
+      levels = c("Reference", "Endogenous")
+    )]
   } else {
-    if (unique(processed$LABEL) == "L") {
+    label_levels = levels(factor(processed$LABEL))
+    if (length(label_levels) == 2) {
+      processed[, LABEL := factor(LABEL, labels = c("Heavy", "Light"))]
+    } else if ("L" %in% label_levels) {
       processed[, LABEL := factor(LABEL, labels = c("Endogenous"))]
     } else {
-      processed[, LABEL := factor(LABEL, labels = c("Reference"))]
+      processed[, LABEL := factor(LABEL, labels = c("Heavy"))]
     }
   }
-  
+
   if ("feature_quality" %in% colnames(processed)) {
     processed[, feature_quality := NULL]
   }
@@ -357,10 +358,11 @@ dataProcessPlots = function(
   }
 
   if (summaryPlot) {
-    protein_by_run = expand.grid(Protein = unique(summarized$Protein), 
+    protein_by_run = expand.grid(Protein = unique(summarized$Protein),
                                  RUN = unique(summarized$RUN))
     summarized = merge(summarized, protein_by_run, by = c("Protein", "RUN"),
                        all.x = TRUE, all.y = TRUE)
+    summary_label = if ("Light" %in% levels(processed$LABEL)) "Light" else "Endogenous"
     if(!isPlotly) {
         savePlot(address, "ProfilePlot_wSummarization", width, height)
     }
@@ -384,7 +386,7 @@ dataProcessPlots = function(
         Protein == all_proteins[i],
         list(PROTEIN = unique(Protein), PEPTIDE = "Run summary",
              TRANSITION = "Run summary", FEATURE = "Run summary",
-             LABEL = "Endogenous", RUN = RUN,
+             LABEL = summary_label, RUN = RUN,
              ABUNDANCE = LogIntensities, FRACTION = 1, 
              UPPERBOUND = if("Variance" %in% names(.SD)) LogIntensities + 1.96 * sqrt(Variance) else NA_real_, # 95% confidence interval
              LOWERBOUND = if("Variance" %in% names(.SD)) LogIntensities - 1.96 * sqrt(Variance) else NA_real_
@@ -442,30 +444,32 @@ dataProcessPlots = function(
   processed[, RUN := factor(RUN, levels = unique(processed$RUN),
                             labels = seq(1, data.table::uniqueN(processed$RUN)))]
 
-  if (length(unique(processed$LABEL)) == 2) {
-    processed[, LABEL := factor(LABEL, labels = c("Reference", "Endogenous"))]
+  if ("is_labeled_ref" %in% colnames(processed)) {
+    processed[, LABEL := factor(
+      ifelse(is_labeled_ref, "Reference", "Endogenous"),
+      levels = c("Reference", "Endogenous")
+    )]
     label.color = c("darkseagreen1", "lightblue")
   } else {
-    if (unique(processed$LABEL) == "L") {
+    label_levels = levels(factor(processed$LABEL))
+    if (length(label_levels) == 2) {
+      processed[, LABEL := factor(LABEL, labels = c("Heavy", "Light"))]
+      label.color = c("darkseagreen1", "lightblue")
+    } else if ("L" %in% label_levels) {
       processed[, LABEL := factor(LABEL, labels = c("Endogenous"))]
       label.color = c("lightblue")
     } else {
-      processed[, LABEL := factor(LABEL, labels = c("Reference"))]
+      processed[, LABEL := factor(LABEL, labels = c("Heavy"))]
       label.color = c("darkseagreen1")
     }
   }
 
   processed = processed[order(LABEL, GROUP, SUBJECT)]
 
-  ## Meena :due to GROUP=0 for labeled.. extra care required.
   tempGroupName = unique(processed[, list(GROUP, RUN)])
-  if (length(unique(processed$LABEL)) == 2) {
-    tempGroupName = tempGroupName[GROUP != '0']
-  } 
-  tempGroupName = tempGroupName[order(RUN), ] ## Meena : should we order by GROUP or RUN? I guess by RUn, because x-axis is by RUN
+  tempGroupName = tempGroupName[order(RUN), ]
   level.group = as.character(unique(tempGroupName$GROUP))
-  tempGroupName$GROUP = factor(tempGroupName$GROUP,
-                                levels = level.group) ## Meena : factor GROUP again, due to 1, 10, 2, ... if you have better way, please change
+  tempGroupName$GROUP = factor(tempGroupName$GROUP, levels = level.group)
 
   groupAxis = as.numeric(xtabs(~GROUP, tempGroupName))
   cumGroupAxis = cumsum(groupAxis)

R/utils_checks.R

@@ -295,8 +295,8 @@ setMethod(".checkDataValidity", "MSstatsValidated", .prepareForDataProcess)
         skip_absent = TRUE)
 
     input[, FEATURE := paste(PEPTIDE, TRANSITION, sep = "_")]
-    input[, GROUP := ifelse(LABEL == "L", GROUP_ORIGINAL, "0")]
-    input[, SUBJECT := ifelse(LABEL == "L", SUBJECT_ORIGINAL, "0")]
+    input[, GROUP := GROUP_ORIGINAL]
+    input[, SUBJECT := SUBJECT_ORIGINAL]
 
     cols = c("PROTEIN", "PEPTIDE", "TRANSITION", "FEATURE", "LABEL", 
              "GROUP_ORIGINAL", "SUBJECT_ORIGINAL", "RUN", "GROUP",