Add files via upload

MS2:MS1 Ratio per precursor. Log2 Scale.

modules/dia-nn/020_Ion_Sampling/instrument_20_DIA_MS1_MS2_Ratio.R

@@ -0,0 +1,66 @@
+init <- function() {
+
+  type <- 'plot'
+  box_title <- 'MS2/MS1 Intensity Ratio per precursor'
+  help_text <- 'Plotting the MS2/MS1 Intensity Ratio for all precursors.'
+  source_file <- 'report'
+
+  .validate <- function(data, input) {
+    validate(need(data()[['report']], paste0('Upload report.txt')))
+    validate(need((nrow(data()[['report']]) > 1), paste0('No Rows selected')))
+
+  }
+
+  .plotdata <- function(data, input) {
+    plotdata <- data()[['report']][,c('Raw.file', 'Ms1.Area', 'Precursor.Quantity', 'Precursor.Id')]
+    plotdata$Ms1.Area <- as.numeric(plotdata$Ms1.Area)
+    plotdata$Precursor.Quantity <- as.numeric(plotdata$Precursor.Quantity)
+
+    plotdata <- plotdata %>% 
+      group_by(Raw.file, Precursor.Id) %>% 
+        mutate(Ms2.Ms1.Ratio = Precursor.Quantity / Ms1.Area)
+
+    plotdata <- dplyr::filter(plotdata, Ms2.Ms1.Ratio>0)
+    plotdata$Ms2.Ms1.Ratio <- log2(plotdata$Ms2.Ms1.Ratio)
+    # Thresholding data at 1 and 99th percentiles
+    ceiling <- quantile(plotdata$Ms2.Ms1.Ratio, probs=.99, na.rm = TRUE)
+    floor <- quantile(plotdata$Ms2.Ms1.Ratio, probs=.01, na.rm = TRUE)
+
+    plotdata <- dplyr::filter(plotdata, is.finite(Ms2.Ms1.Ratio))
+    if(nrow(plotdata) > 0){
+      plotdata[plotdata$Ms2.Ms1.Ratio >= ceiling, 2] <- ceiling
+      plotdata[plotdata$Ms2.Ms1.Ratio <= floor, 2] <- floor
+    }
+    return(plotdata)
+  }
+
+  .plot <- function(data, input) {
+    .validate(data, input)
+    plotdata <- .plotdata(data, input)
+    validate(need((nrow(plotdata) > 1), paste0('No Rows selected')))
+
+
+    medianData = plotdata %>% group_by(Raw.file) %>%
+      summarise(median = median(Ms2.Ms1.Ratio), .groups = "drop")
+
+
+    ggplot(plotdata, aes(Ms2.Ms1.Ratio)) + 
+      facet_wrap(~Raw.file, nrow = 1, scales = "free_x") + 
+      geom_histogram(bins=50, fill=custom_colors[[6]]) + 
+      coord_flip() + 
+      labs(x=expression(bold('Log'[2]*' Precursor Ratio')), y='Number of Precursors') +
+      theme_diann(input=input, show_legend=T)
+  }
+
+  return(list(
+    type=type,
+    box_title=box_title,
+    help_text=help_text,
+    source_file=source_file,
+    validate_func=.validate,
+    plotdata_func=.plotdata,
+    plot_func=.plot,
+    dynamic_width=200,
+    dynamic_width_base=50
+  ))
+}