Merge pull request #33 from CRI-iAtlas/nanostring_ui

add interface in ici cohort selection for nanostring

R/cohort_dataset_selection_functions.R

@@ -42,3 +42,16 @@ create_cohort_module_string <- function(.datasets, tbl = NULL){
     }
 
 }
+
+#Create a list of ICI datasets based on whether the data is RNA-Seq or Nanostring. Needs to be updated if more Nanostring data is added
+create_ici_options <- function(.datasets){
+    nanostring_ds <- c("Chen_CanDisc_2016", "Melero_GBM_2019", "Prat_CanRes_2017")
+    rnaseq_nano_ds <- "Prins_GBM_2019" #this dataset has both RNA-Seq and Nanostring data available
+
+    return(
+        list(
+            'RNA-Seq' = .datasets[!(.datasets %in% nanostring_ds)],
+            'Nanostring' = .datasets[.datasets %in% c(nanostring_ds, rnaseq_nano_ds)]
+        )
+    )
+}

R/cohort_dataset_selection_server.R

@@ -10,26 +10,50 @@ cohort_dataset_selection_server <- function(
       ns <- session$ns
 
       choices <- shiny::reactive({
-        iatlasGraphQLClient::query_datasets(types = dataset_type()) %>%
+        options <- iatlasGraphQLClient::query_datasets(types = dataset_type()) %>%
           dplyr::select("display", "name") %>%
           tibble::deframe(.)
+        if(dataset_type() == "analysis") return(options)
+        else return(create_ici_options(options)) #for the ICI Cohort Selection, we have RNA-Seq and Nanostring data. This function returns a list organizing them. 
       })
 
-      ui_func <- shiny::reactive({
-        shiny::req(dataset_type())
-        if(dataset_type() == "analysis") return(shiny::selectInput)
-        else return(shiny::checkboxGroupInput)
-      })
-
-
       output$dataset_selection_ui <- shiny::renderUI({
-        shiny::req(ui_func(), choices(), default_datasets())
-        ui_func()(
-          inputId  = ns("dataset_choices"),
-          label    = "Select Datasets",
-          choices  = choices(),
-          selected = default_datasets()
-        )
+        shiny::req(choices(), default_datasets())
+
+        if(dataset_type() == "analysis"){
+          shiny::selectInput(
+            inputId  = ns("dataset_choices"),
+            label    = "Select Datasets",
+            choices  = choices(),
+            selected = default_datasets()
+          )
+        }else{ #ICI Cohort selection will have two dataset columns, one for RNA-Seq and the other for Nanostring datasets
+          shiny::fluidRow(
+            shiny::column(
+              width = 6,
+              shiny::checkboxGroupInput(
+                inputId  = ns("dataset_choices"),
+                label    = "Select Datasets - RNA-Seq data",
+                choices  = choices()[[1]], #list RNA-seq datasets
+                selected = default_datasets()
+              )
+            ),
+            shiny::column(
+              width = 6,
+              shiny::checkboxGroupInput(
+                inputId  = ns("dataset_choices_ns"),
+                label    = "Select Datasets - Nanostring data (only Immunomodulators module)",
+                choices  = choices()[[2]], #list nanostring datasets
+                selected = default_datasets()
+              )
+            )
+          )
+        }
+      })
+
+      dataset_selection <- shiny::reactive({
+        if(dataset_type() == "analysis") return(input$dataset_choices)
+        else return(c(input$dataset_choices, input$dataset_choices_ns)) #ICI Cohort selection can have RNA-Seq and Nanostring ds selected
       })
 
       # This is so that the conditional panel can see the various shiny::reactives
@@ -50,7 +74,7 @@ cohort_dataset_selection_server <- function(
         )
       })
 
-      return(shiny::reactive(input$dataset_choices))
+      return(shiny::reactive(sort(dataset_selection())))
     }
   )
 }

inst/markdown/cohort_dataset_selection.markdown

@@ -1 +1 @@
-First, select a cancer genomics dataset from the dropdown below.
+First, select data of interest from the options below.