[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

R/DeconvExplorer.R

@@ -888,11 +888,12 @@ DeconvExplorer <- function(deconvexp_bulk = NULL,
 
     # start the tour
     observeEvent(input$startTour, {
-      tour_steps <- read.delim(system.file("extdata", "tour_intro.txt",
-        package = "DeconvExplorer"
-      ),
-      sep = ";", stringsAsFactors = FALSE,
-      row.names = NULL, quote = ""
+      tour_steps <- read.delim(
+        system.file("extdata", "tour_intro.txt",
+          package = "DeconvExplorer"
+        ),
+        sep = ";", stringsAsFactors = FALSE,
+        row.names = NULL, quote = ""
       )
       introjs(session, options = list(
         steps = tour_steps,

R/Global.R

@@ -1,4 +1,3 @@
-
 #' Get subset of deconvolution results
 #'
 #' This function returns the requested deconvolution results as a list
@@ -44,66 +43,56 @@ returnSelectedDeconvolutions <- function(deconv_select, deconv_list) {
 #' @examples
 #' # CosTODO
 # plot_benchmark <- function(deconvolutions) {
-#   # import and preformat data
-#
-#   # deconvolution_list <- list()
-#   # for (deconvolution in deconv_select) {
-#   #   # deconvolution_list[length(deconvolution_list) + 1] <- deconv_list[[deconvolution]][1]
-#   #   deconvolution_list[deconvolution] <- deconv_list[[deconvolution]][1]
-#   # }
-#
-#   # add samples and deconvolution method
-#   deconvolutions <- lapply(deconvolutions, function(x) cbind(x, sample = rownames(x)))
-#   deconvolutions <- lapply(names(deconvolutions), function(x) {
-#     cbind(deconvolutions[[x]], method = rep(x, nrow(deconvolutions[[x]])))
-#   })
-#
-#   deconvolutions <- lapply(deconvolutions, function(x) {
-#     tidyr::pivot_longer(data.frame(x), !c("sample", "method"),
-#       names_to = "cell_type", values_to = "predicted_fraction"
-#     )
-#   })
-#
-#   # combine to one dataframe
-#   data <- do.call("rbind", deconvolutions)
-#
-#   # preformat reference data
-#   ref <- omnideconv::RefData
-#   ref$sample <- rownames(ref)
-#   ref <- tidyr::pivot_longer(ref, !sample, names_to = "cell_type", values_to = "true_fraction")
-#
-#   # merge the reference data with the deconvolution results
-#   data <- merge(ref, data, by = c("sample", "cell_type"))
-#
-#   # change datatype to numeric
-#   data$predicted_fraction <- as.numeric(data$predicted_fraction)
-#   data$true_fraction <- as.numeric(data$true_fraction)
-#
-#   # calculate max width/heigth -> plot symmetric and line @ 45 Degrees
-#   max_value <- max(max(data$true_fraction), max(data$predicted_fraction)) + 0.1
-#
-#   # create plot
-#   plot <- ggplot(data, aes(
-#     x = .data$true_fraction, y = predicted_fraction, color = cell_type,
-#     text = paste0("Sample: ", sample, "\nTrue: ", true_fraction, "\nPredicted: ", predicted_fraction)
-#   )) +
-#     geom_point(size = 4) +
-#     facet_wrap(~method) +
-#     geom_abline(color = "black") +
-#     labs(x = "True Fraction", y = "predicted Fraction", color = "cell type") +
-#     coord_cartesian(xlim = c(0, max_value), ylim = c(0, max_value))
-#
-#   # render
-#   plotly::ggplotly(plot, tooltip = c("text")) |>
-#     plotly::config(
-#       displaylogo = FALSE, showTips = FALSE, toImageButtonOptions = list(filename = paste0("plotMethod", "_plot")),
-#       modeBarButtonsToRemove = list(
-#         "hoverClosestCartesian",
-#         "hoverCompareCartesian",
-#         "zoomIn2d", "zoomOut2d",
-#         "lasso2d", "zoom2d",
-#         "pan2d", "autoScale2d", "select2d"
-#       )
-#     ) |>
-#     plotly::layout(xaxis = list(fixedrange = TRUE), yaxis = list(fixedrange = TRUE))
+#' #  # import and preformat data
+#' #  # deconvolution_list <- list()
+#' #  # for (deconvolution in deconv_select) {
+#' #  #   # deconvolution_list[length(deconvolution_list) + 1] <- deconv_list[[deconvolution]][1]
+#' #  #   deconvolution_list[deconvolution] <- deconv_list[[deconvolution]][1]
+#' #  # }
+#' #  # add samples and deconvolution method
+#' #  deconvolutions <- lapply(deconvolutions, function(x) cbind(x, sample = rownames(x)))
+#' #  deconvolutions <- lapply(names(deconvolutions), function(x) {
+#' #    cbind(deconvolutions[[x]], method = rep(x, nrow(deconvolutions[[x]])))
+#' #  })
+#' #  deconvolutions <- lapply(deconvolutions, function(x) {
+#' #    tidyr::pivot_longer(data.frame(x), !c("sample", "method"),
+#' #      names_to = "cell_type", values_to = "predicted_fraction"
+#' #    )
+#' #  })
+#' #  # combine to one dataframe
+#' #  data <- do.call("rbind", deconvolutions)
+#' #  # preformat reference data
+#' #  ref <- omnideconv::RefData
+#' #  ref$sample <- rownames(ref)
+#' #  ref <- tidyr::pivot_longer(ref, !sample, names_to = "cell_type", values_to = "true_fraction")
+#' #  # merge the reference data with the deconvolution results
+#' #  data <- merge(ref, data, by = c("sample", "cell_type"))
+#' #  # change datatype to numeric
+#' #  data$predicted_fraction <- as.numeric(data$predicted_fraction)
+#' #  data$true_fraction <- as.numeric(data$true_fraction)
+#' #  # calculate max width/heigth -> plot symmetric and line @ 45 Degrees
+#' #  max_value <- max(max(data$true_fraction), max(data$predicted_fraction)) + 0.1
+#' #  # create plot
+#' #  plot <- ggplot(data, aes(
+#' #    x = .data$true_fraction, y = predicted_fraction, color = cell_type,
+#' #    text = paste0("Sample: ", sample, "\nTrue: ", true_fraction, "\nPredicted: ", predicted_fraction)
+#' #  )) +
+#' #    geom_point(size = 4) +
+#' #    facet_wrap(~method) +
+#' #    geom_abline(color = "black") +
+#' #    labs(x = "True Fraction", y = "predicted Fraction", color = "cell type") +
+#' #    coord_cartesian(xlim = c(0, max_value), ylim = c(0, max_value))
+#' #  # render
+#' #  plotly::ggplotly(plot, tooltip = c("text")) |>
+#' #    plotly::config(
+#' #      displaylogo = FALSE, showTips = FALSE, toImageButtonOptions = list(filename = paste0("plotMethod", "_plot")),
+#' #      modeBarButtonsToRemove = list(
+#' #        "hoverClosestCartesian",
+#' #        "hoverCompareCartesian",
+#' #        "zoomIn2d", "zoomOut2d",
+#' #        "lasso2d", "zoom2d",
+#' #        "pan2d", "autoScale2d", "select2d"
+#' #      )
+#' #    ) |>
+#' #    plotly::layout(xaxis = list(fixedrange = TRUE), yaxis = list(fixedrange = TRUE))
 # }