Importfix

DESCRIPTION

@@ -59,7 +59,7 @@ Imports:
     circlize,
     BioQC,
     shinyWidgets
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 Encoding: UTF-8
 Remotes: 
     github::omnideconv/omnideconv
@@ -76,3 +76,4 @@ URL: https://github.com/omnideconv/DeconvExplorer/
 BugReports: https://github.com/omnideconv/DeconvExplorer/issues
 VignetteBuilder: knitr
 Config/testthat/edition: 3
+Roxygen: list(markdown = TRUE)

NAMESPACE

@@ -18,8 +18,7 @@ export(returnSelectedDeconvolutions)
 export(selectGenesByScore)
 import(omnideconv)
 import(shiny, except = c(renderDataTable, dataTableOutput))
-importFrom(BioQC,entropySpecificity)
-importFrom(BioQC,gini)
+import(shinyBS)
 importFrom(ComplexHeatmap,Heatmap)
 importFrom(ComplexHeatmap,UpSet)
 importFrom(ComplexHeatmap,comb_size)
@@ -86,7 +85,6 @@ importFrom(rintrojs,readCallback)
 importFrom(rlang,.data)
 importFrom(shiny,addResourcePath)
 importFrom(shinyWidgets,actionBttn)
-importFrom(shinyBS,bsPopover)
 importFrom(shinycssloaders,withSpinner)
 importFrom(shinydashboard,box)
 importFrom(shinydashboard,dashboardBody)
@@ -100,6 +98,7 @@ importFrom(shinydashboard,renderValueBox)
 importFrom(shinydashboard,sidebarMenu)
 importFrom(shinydashboard,tabItem)
 importFrom(shinydashboard,tabItems)
+importFrom(shinydashboard,updateTabItems)
 importFrom(shinydashboard,valueBox)
 importFrom(shinydashboard,valueBoxOutput)
 importFrom(shinyjs,hide)

R/BenchmarkingPlots.R

@@ -60,7 +60,7 @@ plot_benchmark_scatter <- function(gtruth_df,
     theme(axis.text.x = element_text(angle = 60, hjust = 1), strip.background = ggplot2::element_rect(fill = "white")) +
     labs(x = "true cellular fractions", y = "cell type estimates", title = "") +
     theme(legend.position = "none", text = element_text(size = 15)) +
-    ggplot::geom_abline(linetype = "dashed")
+    ggplot2::geom_abline(linetype = "dashed")
 
   # get palette
   max_colors <- RColorBrewer::brewer.pal.info[color_palette, ]$maxcolors # for brewer.pal()

R/DeconvExplorer-pkg.R

@@ -6,10 +6,10 @@
 #' @import omnideconv
 #' @importFrom shinydashboard box dashboardBody dashboardHeader dashboardPage
 #' dashboardSidebar dropdownMenu menuItem notificationItem sidebarMenu valueBox valueBoxOutput renderValueBox
-#' tabItem tabItems
+#' tabItem tabItems updateTabItems
 #' @importFrom plotly ggplotly plotlyOutput renderPlotly plot_ly layout config
 #' @importFrom ggplot2 aes aes_ aes_string coord_cartesian coord_flip element_text
-#' facet_wrap geom_abline geom_boxplot geom_col geom_jitter geom_point
+#' facet_wrap geom_abline geom_boxplot geom_col geom_jitter geom_point ggsave
 #' geom_tile ggplot guide_colorbar guides labs scale_fill_gradient theme geom_text element_blank
 #' geom_hline scale_colour_brewer scale_fill_brewer ylim theme_minimal geom_rect element_rect
 #' @importFrom shinycssloaders withSpinner

R/DeconvExplorer.R

@@ -127,7 +127,6 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
     width = 12,
     fileInput("userSignatureUpload", "Upload Signature"),
     div(style = "margin-top: -25px"),
-
     p("You can upload a previsouly generated signature matrix of a deconvolution method and analyse it with DeconvExplorer. Multiple uploads are possible."),
     fluidRow(
       column(4, shinyWidgets::actionBttn("selectSigExploration", "Explore the signature", icon = icon("arrow-right"), color = "success", style = "simple")),
@@ -202,7 +201,7 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
     column(
       width = 4,
       selectInput("deconvMethod", "Deconvolution Method",
-        choices = c('MuSiC'='music', omnideconv::deconvolution_methods[-10])
+        choices = c("MuSiC" = "music", omnideconv::deconvolution_methods[-10])
       )
     ),
     column(
@@ -221,8 +220,10 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
     column(
       width = 3,
       div(
-        shinyBS::popify(shinyWidgets::actionBttn("deconvolute", "Deconvolute", style = 'simple', icon = icon('triangle-exclamation'), color = 'warning'),
-                        "Attention", "Some methods are considerably slower than others; please keep this in mind when using DeconvExplorer for deconvolution."),
+        shinyBS::popify(
+          shinyWidgets::actionBttn("deconvolute", "Deconvolute", style = "simple", icon = icon("triangle-exclamation"), color = "warning"),
+          "Attention", "Some methods are considerably slower than others; please keep this in mind when using DeconvExplorer for deconvolution."
+        ),
         style = "margin-top:1.7em"
       )
     ),
@@ -235,7 +236,7 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
       title = "",
       content = "Select a deconvolution method to run. If required and supported by the deconvolution method you can additionally select a custom signature to be used in computation. Please note this is an advanced feature and should be used with caution. "
     )
-  
+
 
   deconv_plot_box <- shinydashboard::box(
     id = "tour_deconvPlot",
@@ -512,43 +513,45 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
     title = span("Clustered Signature", icon("question-circle", id = "sigHeatmapQ")),
     status = "info", solidHeader = TRUE,
     width = 12,
-    fluidRow(    
+    fluidRow(
       column(
         width = 4,
         selectInput("signatureToHeatmap", "Select a Signature", choices = NULL)
       ),
       column(
         width = 2,
         selectInput("signatureAnnotationScore", "Select an annotation score",
-                    choices = c("Entropy" = "entropy", "Gini Index" = "gini")
+          choices = c("Entropy" = "entropy", "Gini Index" = "gini")
         )
       ),
       column(
         width = 2,
         selectInput("signatureAnnotationPlotType", "Annotation Type",
-                    choices = c("Bars" = "bar", "Lines" = "line")
+          choices = c("Bars" = "bar", "Lines" = "line")
         )
       ),
       column(
         width = 2,
         selectInput("clusterCelltypes", "Order rows (cell types)",
-                    choices = c(".. by cell-type similarity" = "cluster", ".. alphabetically" = "no_cluster")
+          choices = c(".. by cell-type similarity" = "cluster", ".. alphabetically" = "no_cluster")
         )
       ),
       column(
         width = 2,
         selectInput("clusterGenes", "Order columns (genes)",
-                    choices = c(".. by maximal z-score per cell type" = "z-score cutoff",
-                                ".. hierarchically based on euclidean distance" = "hierarchical clustering",
-                                ".. alphabetically" = "alphabetical")
+          choices = c(
+            ".. by maximal z-score per cell type" = "z-score cutoff",
+            ".. hierarchically based on euclidean distance" = "hierarchical clustering",
+            ".. alphabetically" = "alphabetical"
+          )
         )
       )
     ),
     fluidRow(
       column(
         width = 12,
         InteractiveComplexHeatmap::originalHeatmapOutput("clusteredHeatmapOneSignature",
-                                                         width = "1250px", height = "450px", containment = TRUE
+          width = "1250px", height = "450px", containment = TRUE
         )
       )
     ),
@@ -726,7 +729,7 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
       column(
         width = 7,
         sliderInput("refinePercentZero", "Maximum percentage of zeroes allowed for each gene",
-                    min = 0, max = 100, value = 90, step = 1, post = "%"
+          min = 0, max = 100, value = 90, step = 1, post = "%"
         )
       ),
       column(
@@ -760,7 +763,7 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
     )
   )
 
-refUnspecificPopover <-
+  refUnspecificPopover <-
     shinyBS::bsPopover(
       id = "refUnspecificQ",
       title = "",
@@ -818,8 +821,8 @@ refUnspecificPopover <-
     shinyBS::bsPopover(
       id = "refManuallyQ",
       title = "",
-      content = 
-    )
+      content =
+      )
 
   # Info Boxes --------------------------------------------------------------
   info_overview <- shinydashboard::box(
@@ -1662,7 +1665,7 @@ refUnspecificPopover <-
           scoring_method = input$signatureAnnotationScore,
           annotation_type = input$signatureAnnotationPlotType,
           color_palette = input$globalColor,
-          order_rows = input$clusterCelltypes, 
+          order_rows = input$clusterCelltypes,
           order_columns = input$clusterGenes
         ),
         "clusteredHeatmapOneSignature",

R/SignatureExplorationPlots.R

@@ -163,6 +163,7 @@ plot_meanEntropyPerMethod <- function(signature_list,
 #' @param scoring_method The score used to annotate the genes (entropy, gini)
 #' @param annotation_type How the score is rendered (line, bar)
 #' @param order_rows Either 'cluster' to order cell types by similarity or 'no_cluster' to order alphabetically
+#' @param order_columns Character, either 'z-score cutoff', 'hierarchical clustering' or 'alphabetical'
 #' @param threshold the threshold for the z-scored expression in the signature matrix to consider
 #'    a gene as being differentially expressed. Default: 1.5
 #'
@@ -253,22 +254,19 @@ plot_signatureClustered <- function(signature_mat,
     cell.types.ordered <- order(colnames(mat))
   }
 
-  if(order_columns == 'z-score cutoff'){
+  if (order_columns == "z-score cutoff") {
     genes <- c()
     for (c in cell.types.ordered) {
       highly.expr.genes <- names(which(mat[, c] > threshold))
       genes <- union(genes, highly.expr.genes)
     }
-    
+
     genes <- union(genes, rownames(mat))
-  }else if(order_columns == 'hierarchical clustering'){
-
+  } else if (order_columns == "hierarchical clustering") {
     # use hierarchical ward D2 clustering based on euclidean distance
-    clustering <- hclust(dist(mat), method = 'ward.D2')
+    clustering <- hclust(dist(mat), method = "ward.D2")
     genes <- rownames(mat)[clustering$order]
-
-  }else if(order_columns == 'alphabetical'){
-
+  } else if (order_columns == "alphabetical") {
     genes <- sort(rownames(mat))
   }
 

R/SignatureRefinements.R

@@ -116,26 +116,26 @@ removeUnspecificGenes <- function(signature_mat,
 
   signature_mat <- as.matrix(signature_mat)
 
-  to_keep <- sapply(1:nrow(signature_mat), function(i){
+  to_keep <- sapply(1:nrow(signature_mat), function(i) {
     row <- signature_mat[i, ] # has colnames! drop FALSE is mandatory !!!!!
-    
+
     # calculate bins to prevent error
     breaks <- seq(floor(min(row)), ceiling(max(row)), length.out = number_of_bins + 1)
-    
+
     # cut into bins, seperate for each gene
     bins <- cut(row, breaks = breaks, labels = labels, include.lowest = TRUE)
-    
+
     nHighBins <- sum(bins == "high") # not working when labels is something else
-    
+
     # this value needs to be greater than one, depending of the step in the pipeline there arent
     # any rows producing zeros left but that is not the case for all signatures
     if (nHighBins <= max_count & nHighBins > 0) {
       return(TRUE)
-    }else{
+    } else {
       return(FALSE)
     }
   })
-  
+
 
   refinedSignature <- signature_mat[to_keep, ]