inst/ProstarApp/server/srv_Home.R

In samWieczorek/Prostar: Provides a GUI for DAPAR

callModule(moduleInsertMarkdown, "ProstarPresentation_MD",URL_ProstarPresentation)

output$citationText <- renderUI({
  tagList(
    tags$div(style="background-color: lightgrey;",
    tags$p(class="body",tags$b("Maintaining ProStaR as free software is a heavy and time-consuming
                duty. If you use it, please cite the following reference:")),
    tags$p(tags$i("S. Wieczorek, F. Combes, C. Lazar, Q. Giai-Gianetto, 
                L. Gatto, A. Dorffer, A.-M. Hesse, Y. Coute, M. Ferro, 
                C. Bruley and T. Burger."),
          tags$u("DAPAR & ProStaR: software to perform statistical 
                analyses in quantitative discovery."),
                tags$b("Bioinformatics"),", 33(1), 135-136, 2017.",
                tags$a("http://doi.org/10.1093/bioinformatics/btw580", href="http://doi.org/10.1093/bioinformatics/btw580", target="_blank")
                )
      )
  )
  })


output$versionsText <- renderUI({
  t <- sessionInfo()
  
  daparVersion <- installed.packages(lib.loc=DAPAR.loc)["DAPAR","Version"]
  ProstarVersion <- installed.packages(lib.loc=Prostar.loc)["Prostar","Version"]

  tagList(
     tags$p(class="body",
            tags$b("DAPAR"),
            " and ", 
            tags$b("Prostar"), 
            " form a software suite devoted to the differential analysis of 
              quantitative data resulting from discovery proteomics experiments.", 
            tags$br(),
            "It is composed of two distinct ",
            tags$b("R"),
            " packages:",
            tags$ul(
              tags$li(tags$p(tags$a("Prostar", href="http://www.bioconductor.org/packages/release/bioc/html/Prostar.html", target="_blank"),paste0(" (version ",
                             ProstarVersion,"), which proposes a web-based graphical user interface to DAPAR."))),
               tags$li(tags$p(tags$a("DAPAR", href="http://www.bioconductor.org/packages/release/bioc/html/DAPAR.html", target="_blank"),paste0(" (version ",
                              daparVersion,"), which contains all the routines to analyze and visualize proteomics data.")))
            )
     )
)
})


output$NoteForNewVersion <- renderUI({
  
  #df <- getPackagesVersions2()
  df <- getPackagesVersions()
  if (sum(grepl("(Out of date)",df[,1])) >= 1) {
  tags$div(
    style="font-size: 16px",
    tags$div( style="display:inline-block; vertical-align: top;",
              p(style="color: red",'Newer versions of Prostar and/or DAPAR packages have been released. For more information, please go to the page ')
    ),
    tags$div( style="display:inline-block; vertical-align: top;",
              actionLink('goToReleasesNotes', "'Check for updates'",style="background-color: white, color: blue")
    )
  )
  
   }
})

observeEvent(input$goToReleasesNotes, {
  updateTabsetPanel(session, 'navPage', "checkForUpdatesTab")
})



# #-------------------------------------------------------------------
# output$descriptionText <- renderUI({
#   
#   tagList(
# #    tags$p(class="body",
# #        "The package DAPAR includes wrappers to numerous other R packages, either available on the ",
# #           tags$a("CRAN", href="https://cran.r-project.org", target="_blank"), " or the ",
# #           tags$a("Bioconductor", href="http://www.bioconductor.org", target="_blank"),
# #           tags$br(),
# #           "Here is a brief overview of the available functionalities:"),
#     tags$p(style=" font-size:20px;",tags$b("Data processing")),
#     tags$ul(
#       style="list-style-type:disc;",
#       tags$li(tags$p(class="body",tags$b("Filtering"), "options allows pruning the protein or peptide list according to 
#                 various criteria (missing values, contaminants, reverse sequences);")),
#       tags$li(tags$p(class="body",tags$b("Cross replicate normalization"), ", so as to make the quantitative 
#                 values comparable between the different analyzed samples;")),
#       tags$li(tags$p(class="body",tags$b("Missing values imputation"), " with different methods, depending 
#                 on the nature of  the missing values;")),
#       tags$li(tags$p(class="body",tags$b("Aggregation"), " from peptide to protein intensity values;")),
#       tags$li(tags$p(class="body",tags$b("Hypothesis testing"), ", which includes null hypothesis 
#                 significance testing."))
#     ),
#       
#     tags$br(),
#     tags$p(style=" font-size:20px;",tags$b("Data mining")),
#     tags$ul(
#       style="list-style-type:disc;",
#       tags$li(tags$p(class="body",tags$b("Descriptive statistics"), "are available, for exploration and visualization of the 
#                      quantitative dataset;")),
#       tags$li(tags$p(class="body",tags$b("Differential analysis"), " which includes multiple testing correction 
#                      (for false discovery rate estimation).")),
#       tags$li(tags$p(class="body",tags$b("Gene Ontology (GO) analysis"), " allows is to map protein list onto GO terms and 
#                      to test category enrichment."))
#     )
#   )
#    
#   
# })