small fixes

DESCRIPTION

@@ -3,7 +3,7 @@ Title: Differential Enrichment analysis of Proteomics data
 Version: 0.99.0
 Authors@R: c(
     person("Arne", "Smits", email = "arne.smits@embl.de", role = "cre"),
-    person("Wolfgang", "Huber", email = "winston@rstudio.com", role = "aut"))
+    person("Wolfgang", "Huber", role = "aut"))
 Description: This package provides an integrated analysis workflow for robust and reproducible analysis of mass spectrometry proteomics data for differential protein expression or differential enrichment.
     It requires tabular input (e.g. txt files) as generated by quantitative analysis softwares of raw mass spectrometry data, such as MaxQuant or IsobarQuant.
     Functions are provided for data preparation, filtering, variance normalization and imputation of missing values, as well as statistical testing of differentially enriched / expressed proteins.

R/DEP.R

@@ -14,9 +14,6 @@
 #' such as normalization and missing values imputation.
 #' Finally, visualization tools are provided to explore the results,
 #' including heatmap, volcano plot and barplot representations.
-#' Besides differential analysis, the package includes a set of functions
-#' to calculate relative stoichiometry, as originally described in
-#' \href{http://nar.oxfordjournals.org/content/41/1/e28.full}{Smits et al 2013}.
 #' For scientists with limited experience in R, the package also entails
 #' wrapper functions that entail the complete analysis workflow and generate
 #' a report. Even easier to use are the interactive Shiny apps that

R/functions.R

@@ -117,8 +117,8 @@ make_se <- function(proteins_unique, columns, expdesign) {
   expdesign <- mutate(expdesign, condition = make.names(condition)) %>%
     unite(ID, condition, replicate, remove = FALSE)
   rownames(expdesign) <- expdesign$ID
-  colnames(raw)[match(delete_prefix(expdesign$label),
-                      delete_prefix(colnames(raw)))] <- expdesign$ID
+  colnames(raw)[match(make.names(delete_prefix(expdesign$label)),
+                      make.names(delete_prefix(colnames(raw))))] <- expdesign$ID
   raw <- raw[, !is.na(colnames(raw))][rownames(expdesign)]
 
   # Select the rowData

inst/shiny_apps/LFQ/app.R

@@ -62,16 +62,6 @@ ui <- shinyUI(
   				      plotOutput("volcano", height = 600),
   				      downloadButton('downloadVolcano', 'Save volcano')
   				    )
-  				  ),
-  				  tabPanel(title = "iBAQ vs LFC plot",
-  				           fluidRow(
-  				             box(uiOutput("ibaq_cntrst"), width = 6),
-  				             box(numericInput("ibaq_fontsize", "Font size", min = 0, max = 8, value = 2), width = 6)
-  				           ),
-  				           fluidRow(
-  				             plotOutput("ibaq_plot", height = 600),
-  				             downloadButton('downloadIBAQ', 'Save iBAQ plot')
-  				           )
   				  )
 				  ),
   				tabBox(title = "QC Plots", width = 12,
@@ -309,12 +299,6 @@ server <- shinyServer(function(input, output) {
       }
     })
 
-    ibaq_input <- reactive({
-      if(!is.null(input$ibaq_cntrst) & length(grep("^iBAQ.", colnames(rowData(selected())))) > 1) {
-        plot_ibaq(selected(), input$ibaq_cntrst, input$ibaq_fontsize)
-      }
-    })
-
     norm_input <- reactive({
       plot_normalization(filt(), norm())
     })
@@ -356,10 +340,6 @@ server <- shinyServer(function(input, output) {
       volcano_input()
     })
 
-    output$ibaq_plot <- renderPlot({
-      ibaq_input()
-    })
-
     output$norm <- renderPlot({
       norm_input()
     })
@@ -431,15 +411,6 @@ server <- shinyServer(function(input, output) {
       }
     )
 
-    output$downloadIBAQ <- downloadHandler(
-      filename = function() { paste("iBAQ_vs_LFC_", input$contrast, ".pdf", sep = "") },
-      content = function(file) {
-        pdf(file)
-        print(ibaq_input())
-        dev.off()
-      }
-    )
-
     output$downloadNorm <- downloadHandler(
       filename = "normalization.pdf",
       content = function(file) {