Merge pull request #80 from Breeding-Insight/development

Development

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: BIGapp
 Title: Breeding Insight Genomics Shiny Application
-Version: 0.6.2
+Version: 1.0.0
 Authors@R: 
     c(
               person(c("Alexander", "M."), "Sandercock",
@@ -20,10 +20,9 @@ Authors@R:
                     role = "aut"),
               person("Breeding Insight Team",
                     role = "aut"))
-Description: This R shiny app provides a web-based user friendly way for our internal and 
-             external collaborators to analyze genomic data without needing to use command-line tools.
+Description: This R shiny app provides a web-based user friendly way for researchers to analyze genomic data without needing to use command-line tools.
              Initial supported analyses will include the mature genomics/bioinformatics pipelines developed 
-             within Breeding Insight, with additional analyses continuing to be added.
+             within Breeding Insight, with additional analyses continuing to be added. Both diploid and polyploid species are supported.
 License: Apache License (== 2.0)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
@@ -32,6 +31,7 @@ biocViews:
 Imports: 
     vcfR (>= 1.15.0),
     adegenet,
+    curl,
     DT,
     dplyr,
     bs4Dash,
@@ -51,6 +51,7 @@ Imports:
     GWASpoly,
     AGHmatrix,
     factoextra,
+    httr,
     future,
     shinycssloaders,
     RColorBrewer,

NAMESPACE

@@ -50,6 +50,8 @@ importFrom(bs4Dash,updatebs4TabItems)
 importFrom(bs4Dash,valueBox)
 importFrom(bs4Dash,valueBoxOutput)
 importFrom(config,get)
+importFrom(curl,curl_fetch_memory)
+importFrom(curl,new_handle)
 importFrom(factoextra,get_eigenvalue)
 importFrom(future,availableCores)
 importFrom(golem,activate_js)
@@ -72,6 +74,9 @@ importFrom(graphics,strheight)
 importFrom(graphics,strwidth)
 importFrom(graphics,text)
 importFrom(graphics,title)
+importFrom(httr,GET)
+importFrom(httr,content)
+importFrom(httr,status_code)
 importFrom(matrixcalc,is.positive.definite)
 importFrom(plotly,add_markers)
 importFrom(plotly,ggplotly)

R/app_server.R

@@ -3,6 +3,8 @@
 #' @param input,output,session Internal parameters for {shiny}.
 #'     DO NOT REMOVE.
 #' @import shiny
+#' @importFrom httr GET content status_code
+#' @importFrom curl new_handle curl_fetch_memory
 #' @noRd
 app_server <- function(input, output, session) {
   # Your application server logic
@@ -68,6 +70,88 @@ app_server <- function(input, output, session) {
       )
     ))
   })
+
+  #Check for updates from GitHub for BIGapp
+  get_latest_github_commit <- function(repo, owner) {
+    url <- paste0("https://api.github.com/repos/", owner, "/", repo, "/commits/main")
+    response <- GET(url)
+    content <- content(response, "parsed")
+
+    if (status_code(response) == 200) {
+      return(content$sha)
+    } else {
+      return(NULL)
+    }
+  }
+
+  is_internet_connected <- function() {
+    handle <- new_handle()
+    success <- tryCatch({
+      curl_fetch_memory("https://www.google.com", handle = handle)
+      TRUE
+    }, error = function(e) {
+      FALSE
+    })
+    return(success)
+  }
+
+  observeEvent(input$updates_info_button, {
+    # Check internet connectivity
+    if (!is_internet_connected()) {
+      # Display internet connectivity issues message
+      showModal(modalDialog(
+        title = "No Internet Connection",
+        easyClose = TRUE,
+        footer = tagList(
+          modalButton("Close")
+        ),
+        "Please check your internet connection and try again."
+      ))
+      return()
+    }
+
+    package_name <- "BIGapp"
+    repo_name <- "BIGapp" # GitHub repo name
+    repo_owner <- "Breeding-Insight" # User or organization name
+
+    # Get the installed version
+    installed_version <- as.character(packageVersion(package_name))
+
+    # Get the latest version from GitHub (can be tag version or latest commit)
+    latest_commit <- get_latest_github_commit(repo_name, repo_owner)
+
+    # Compare versions and prepare message
+    if (latest_commit > installed_version) {
+      update_status <- "A new version is available. Please update your package."
+      # Prepare styled HTML text for the modal
+      message_html <- paste(
+        "Installed version:", installed_version, "<br>",
+        #"Latest version commit SHA:", latest_commit, "<br>",
+        "<span>A new version is available on GitHub!</span><br>",
+        "<span style='color: red;'>Please update your package.</span>"
+      )
+    } else {
+      update_status <- "Your package is up-to-date!"
+      # Prepare non-styled text for no update needed
+      message_html <- paste(
+        "Installed version:", installed_version, "<br>",
+        #"Latest version commit SHA:", latest_commit, "<br>",
+        update_status
+      )
+    }
+
+    # Display message in a Shiny modal
+    showModal(modalDialog(
+      title = "BIGapp Updates",
+      size = "m",
+      easyClose = TRUE,
+      footer = tagList(
+        modalButton("Close")
+      ),
+      # Use HTML to format the message and include styling
+      HTML(message_html)
+    ))
+  })
 
   #Download Session Info
   output$download_session_info <- downloadHandler(

R/app_ui.R

@@ -34,6 +34,12 @@ app_ui <- function(request) {
               href = "#",
               "Session Info",
               onclick = "Shiny.setInputValue('session_info_button', Math.random())"
+            ),
+            tags$a(
+              class = "dropdown-item",
+              href = "#",
+              "Check for Updates",
+              onclick = "Shiny.setInputValue('updates_info_button', Math.random())"
             )
           )
         )
@@ -62,19 +68,19 @@ app_ui <- function(request) {
                    menuItem("GWASpoly", tabName = "gwas", icon = icon("think-peaks")),
           tags$li(class = "header", style = "color: grey; margin-top: 18px; margin-bottom: 10px; padding-left: 15px;", "Genomic Selection"),
                   menuItem(
-                    span("Predictive Ability", bs4Badge("beta", position = "right", color = "success")),
+                    span("Predictive Ability"),
                            tabName = "prediction_accuracy",
                            icon = icon("right-left")),
                   menuItem(
-                    span("Genomic Prediction", bs4Badge("beta", position = "right", color = "success")),
+                    span("Genomic Prediction"),
                       tabName = "prediction",
                       icon = icon("angles-right")),
           tags$li(class = "header", style = "color: grey; margin-top: 18px; margin-bottom: 10px; padding-left: 15px;", "Information"),
           menuItem("Source Code", icon = icon("circle-info"), href = "https://www.github.com/Breeding-Insight/Genomics_Shiny_App"),
-          menuItem(
-            span("Job Queue", bs4Badge("demo", position = "right", color = "warning")),
-            tabName = "slurm",
-            icon = icon("clock")),
+          #menuItem(
+          #  span("Job Queue", bs4Badge("demo", position = "right", color = "warning")),
+          #  tabName = "slurm",
+          #  icon = icon("clock")),
           menuItem("Help", tabName = "help", icon = icon("circle-question"))
         )
       ),
@@ -98,7 +104,7 @@ app_ui <- function(request) {
         ),
         left = div(
           style = "display: flex; align-items: center; height: 100%;",  # Center the version text vertically
-          "v0.6.2")
+          "v1.0.0")
       ),
       dashboardBody(
         disconnectMessage(), #Adds generic error message for any error if not already accounted for

R/mod_DosageCall.R

@@ -19,8 +19,9 @@ mod_DosageCall_ui <- function(id){
       fluidRow(
         box(
           title = "Inputs", status = "info", solidHeader = TRUE, collapsible = FALSE, collapsed = FALSE,
-          fileInput(ns("madc_file"), "Choose MADC or VCF File", accept = c(".csv",".vcf",".gz")),
-          fileInput(ns("madc_passport"), "Choose Passport File (optional)", accept = c(".csv")),
+          "* Required",
+          fileInput(ns("madc_file"), "Choose MADC or VCF File*", accept = c(".csv",".vcf",".gz")),
+          fileInput(ns("madc_passport"), "Choose Trait File", accept = c(".csv")),
           conditionalPanel(
             condition = "output.passportTablePopulated",
             ns = ns,
@@ -96,12 +97,11 @@ mod_DosageCall_ui <- function(id){
             tooltip = tooltipOptions(title = "Click to see info!")
           ))
         ),
-        valueBoxOutput(ns("MADCsnps"))
-      ),
-
-      fluidRow(
-        box(title = "Status", width = 3, collapsible = TRUE, status = "info",
+        column(width=4,
+          valueBoxOutput(ns("MADCsnps"), width=12),
+          box(title = "Status", width = 12, collapsible = TRUE, status = "info",
             progressBar(id = ns("pb_madc"), value = 0, status = "info", display_pct = TRUE, striped = TRUE, title = " ")
+          )
         )
       )
     )
@@ -161,7 +161,7 @@ mod_DosageCall_server <- function(input, output, session, parent_session){
   # Update dropdown menu choices based on uploaded passport file
   passport_table <- reactive({
     validate(
-      need(!is.null(input$madc_passport), "Upload passport file to access results in this section."),
+      need(!is.null(input$madc_passport), "Upload Trait File to access results in this section."),
     )
     info_df <- read.csv(input$madc_passport$datapath, header = TRUE, check.names = FALSE)
     info_df[,1] <- as.character(info_df[,1]) #Makes sure that the sample names are characters instead of numeric

R/mod_GS.R

@@ -21,7 +21,7 @@ mod_GS_ui <- function(id){
       column(width = 3,
              box(title="Inputs", width = 12, collapsible = TRUE, collapsed = FALSE, status = "info", solidHeader = TRUE,
                  fileInput(ns("pred_known_file"), "Choose Training VCF File", accept = c(".csv",".vcf",".gz")),
-                 fileInput(ns("pred_trait_file"), "Choose Passport File", accept = ".csv"),
+                 fileInput(ns("pred_trait_file"), "Choose Trait File", accept = ".csv"),
                  fileInput(ns("pred_est_file"), "Choose Prediction VCF File", accept = c(".csv",".vcf",".gz")),
                  numericInput(ns("pred_est_ploidy"), "Species Ploidy", min = 1, value = NULL),
                  virtualSelectInput(
@@ -52,7 +52,14 @@ mod_GS_ui <- function(id){
                    status = "warning",
                    icon = icon("info"), width = "300px",
                    tooltip = tooltipOptions(title = "Click to see info!")
-                 ))
+                 )),
+                 tags$hr(style="border-color: #d3d3d3; margin-top: 20px; margin-bottom: 20px;"),  # Lighter grey line
+                 div(style="text-align: left; margin-top: 10px;",
+                     actionButton(ns("advanced_options_pred"),
+                                  label = HTML(paste(icon("cog", style = "color: #007bff;"), "Advanced Options (beta)")),
+                                  style = "background-color: transparent; border: none; color: #007bff; font-size: smaller; text-decoration: underline; padding: 0;"
+                     )
+                 )
 
              )
       ),
@@ -105,6 +112,78 @@ mod_GS_ui <- function(id){
 mod_GS_server <- function(input, output, session, parent_session){
 
   ns <- session$ns
+
+  #Default model choices
+  advanced_options_pred <- reactiveValues(
+    pred_model = "GBLUP",
+    pred_matrix = "Gmatrix",
+    ped_file = NULL
+  )
+
+  pred_outputs <- reactiveValues(corr_output = NULL,
+                                 comb_output = NULL,
+                                 all_GEBVs = NULL,
+                                 avg_GEBVs = NULL)
+
+  #List the ped file name if previously uploaded
+  output$uploaded_file_name <- renderText({
+    if (!is.null(advanced_options_pred$ped_file)) {
+      paste("Previously uploaded file:", advanced_options_pred$ped_file$name)
+    } else {
+      ""  # Return an empty string if no file has been uploaded
+    }
+  })
+
+  #UI popup window for input
+  observeEvent(input$advanced_options_pred, {
+    showModal(modalDialog(
+      title = "Advanced Options (beta)",
+      selectInput(
+        inputId = ns('pred_model'),
+        label = 'Model Choice',
+        choices = c("GBLUP"),
+        selected = advanced_options_pred$pred_model  # Initialize with stored value
+      ),
+      conditionalPanel(
+        condition = "input.pred_model == 'GBLUP'", ns = ns,
+        div(
+          selectInput(
+            inputId = ns('pred_matrix'),
+            label = 'GBLUP Matrix Choice',
+            choices = c("Gmatrix", "Amatrix", "Hmatrix"),
+            selected = advanced_options_pred$pred_matrix  # Initialize with stored value
+          )
+        )
+      ),
+      conditionalPanel(
+        condition = "input.pred_matrix != 'Gmatrix'", ns = ns,
+        div(
+          fileInput(ns("ped_file"), "Choose Pedigree File", accept = ".csv"),
+          conditionalPanel(
+            condition = "output.uploaded_file_name !== ''", # Show only if there's content
+            textOutput(ns("uploaded_file_name"))  # Display the uploaded file name
+          )
+        )
+      ),
+      footer = tagList(
+        modalButton("Close"),
+        actionButton(ns("save_advanced_options"), "Save")
+      )
+    ))
+  })
+
+
+
+  #Close popup window when user "saves options"
+  observeEvent(input$save_advanced_options, {
+    advanced_options$pred_model <- input$pred_model
+    advanced_options$pred_matrix <- input$pred_matrix
+    advanced_options$ped_file <- input$ped_file
+    # Save other inputs as needed
+
+    removeModal()  # Close the modal after saving
+  })
+
   ###Genomic Prediction
   #This tab involved 3 observeEvents
   #1) to get the traits listed in the phenotype file

R/mod_GSAcc.R

@@ -21,7 +21,7 @@ mod_GSAcc_ui <- function(id){
       column(width = 3,
              box(title="Inputs", width = 12, collapsible = TRUE, collapsed = FALSE, status = "info", solidHeader = TRUE,
                  fileInput(ns("pred_file"), "Choose VCF File", accept = c(".csv",".vcf",".gz")),
-                 fileInput(ns("trait_file"), "Choose Passport File", accept = ".csv"),
+                 fileInput(ns("trait_file"), "Choose Trait File", accept = ".csv"),
                  numericInput(ns("pred_ploidy"), "Species Ploidy", min = 1, value = NULL),
                  numericInput(ns("pred_cv"), "Iterations", min = 1, max=20, value = 5),
                  virtualSelectInput(
@@ -164,7 +164,7 @@ mod_GSAcc_server <- function(input, output, session, parent_session){
       selectInput(
         inputId = ns('pred_model'),
         label = 'Model Choice',
-        choices = c("rrBLUP", "GBLUP"),
+        choices = c("GBLUP"),
         selected = advanced_options$pred_model  # Initialize with stored value
       ),
       conditionalPanel(

R/mod_Home.R

@@ -20,17 +20,17 @@ mod_Home_ui <- function(id){
                box(
                  title = "Breeding Insight Genomics App", status = "info", solidHeader = FALSE, width = 12, collapsible = FALSE,
                  HTML(
-                   "<strong>The app is under development</strong>
-              <p>Breeding Insight provides bioinformatic processing support for our external collaborators. This R shiny app provides a web-based user friendly way for users to analyze genomic data without needing to use command-line tools.</p>
+              "<p>The BIGapp is a user-friendly tool for processing low to mid-density genotyping data for diploid and polyploid species. This R shiny app provides a web-based user friendly way for users to analyze genomic data without needing to use command-line tools.
+              Additional analysis will be added, with the initial focus on a core set of features for supporting breeding decisions.</p>
 
               <p><b>Supported Analyses</b></p>
               Initial supported analyses includes the mature genomics/bioinformatics pipelines developed within Breeding Insight:
               <ul>
-                <li>Genotype processing</li>
-                <li>Summary metrics</li>
+                <li>Genotype Processing</li>
+                <li>Summary Metrics</li>
                 <li>Population Structure</li>
                 <li>GWAS</li>
-                <li>GS</li>
+                <li>Genomic Selection</li>
               </ul>"
                  ),
                  style = "overflow-y: auto; height: 500px"