Auto-style code with dev/04_update.R

R/create_cell_colors.R

@@ -21,10 +21,11 @@
 #' @importFrom graphics barplot par
 #' @importFrom grDevices hcl
 #' @importFrom utils head
-create_cell_colors <- function(cell_types = c("Astro", "Micro", "Oligo", "OPC", "Inhib", "Excit"),
-    pallet = c("classic", "gg", "tableau"),
-    split = NA,
-    preview = FALSE) {
+create_cell_colors <- function(
+        cell_types = c("Astro", "Micro", "Oligo", "OPC", "Inhib", "Excit"),
+        pallet = c("classic", "gg", "tableau"),
+        split = NA,
+        preview = FALSE) {
     pallet <- match.arg(pallet)
 
     base_cell_types <- unique(ss(cell_types, pattern = split))

R/fetch_deconvo_data.R

@@ -11,14 +11,14 @@
 #'  Based on spatialLIBD::fetch_data()
 #'
 #' @param type A `character(1)` specifying which file you want to download.
-#' * `rse_gene`: A [RangedSummarizedExperiment-class][SummarizedExperiment::RangedSummarizedExperiment-class] 
+#' * `rse_gene`: A [RangedSummarizedExperiment-class][SummarizedExperiment::RangedSummarizedExperiment-class]
 #' with 110 bulk RNA-seq samples x 21k genes. (41 MB)
-#' * `sce`: A [SingleCellExperiment][SingleCellExperiment::SingleCellExperiment-class] 
+#' * `sce`: A [SingleCellExperiment][SingleCellExperiment::SingleCellExperiment-class]
 #' object with Human DLPFC snRNA-seq data. 77k nuclei x 36k genes (172 MB)
-#' * `sce_DLPFC_example`: An example subset of `sec` 
-#' [SingleCellExperiment][SingleCellExperiment::SingleCellExperiment-class] 
+#' * `sce_DLPFC_example`: An example subset of `sec`
+#' [SingleCellExperiment][SingleCellExperiment::SingleCellExperiment-class]
 #' with 10k nuclei x 557 genes (49 MB)
-#' 
+#'
 #' @param destdir The destination directory to where files will be downloaded
 #' to in case the `ExperimentHub` resource is not available. If you already
 #' downloaded the files, you can set this to the current path where the files
@@ -83,10 +83,11 @@
 #'     file.path(tempdir(), "sce_DLPFC_annotated")
 #' )
 #' }
-fetch_deconvo_data <- function(type = c("rse_gene", "sce", "sce_DLPFC_example"),
-    destdir = tempdir(),
-    eh = ExperimentHub::ExperimentHub(),
-    bfc = BiocFileCache::BiocFileCache()) {
+fetch_deconvo_data <- function(
+        type = c("rse_gene", "sce", "sce_DLPFC_example"),
+        destdir = tempdir(),
+        eh = ExperimentHub::ExperimentHub(),
+        bfc = BiocFileCache::BiocFileCache()) {
     rse_gene <- sce_DLPFC_example <- NULL
 
     ## Choose a type among the valid options

R/get_mean_ratio.R

@@ -5,7 +5,7 @@
 #'
 #' Improved argument names and documentaion, but same functionalty from `get_mean_ratio2()`.
 #'
-#' @param sce [SummarizedExperiment-class][SummarizedExperiment::SummarizedExperiment-class] 
+#' @param sce [SummarizedExperiment-class][SummarizedExperiment::SummarizedExperiment-class]
 #' (or any derivative class) object containing single cell/nucleus gene expression data
 #' @param cellType_col A `character(1)` name of the column in the
 #' [colData()][SummarizedExperiment::SummarizedExperiment-class] of `sce` that
@@ -39,19 +39,19 @@
 #' ## Explore properties of the sce object
 #' sce_DLPFC_example
 #'
-#' ## this data contains logcounts of gene expression 
+#' ## this data contains logcounts of gene expression
 #' SummarizedExperiment::assays(sce_DLPFC_example)$logcounts[1:5, 1:5]
-#' 
+#'
 #' ## nuclei are classified in to cell types
 #' table(sce_DLPFC_example$cellType_broad_hc)
-#' 
+#'
 #' ## Get the mean ratio for each gene for each cell type defined in `cellType_broad_hc`
 #' get_mean_ratio(sce_DLPFC_example, cellType_col = "cellType_broad_hc")
 #'
 #' # Option to specify gene_name as the "Symbol" column from rowData
 #' # this will be added to the marker stats output
 #' SummarizedExperiment::rowData(sce_DLPFC_example)
-#' 
+#'
 #' ## specify rowData col names for gene_name and gene_ensembl
 #' get_mean_ratio(sce_DLPFC_example, cellType_col = "cellType_broad_hc", gene_name = "gene_name", gene_ensembl = "gene_id")
 #'
@@ -60,11 +60,12 @@
 #' @importFrom purrr map
 #' @importFrom purrr map2
 #' @importFrom matrixStats rowMedians
-get_mean_ratio <- function(sce,
-    cellType_col,
-    assay_name = "logcounts",
-    gene_ensembl = NULL,
-    gene_name = NULL) {
+get_mean_ratio <- function(
+        sce,
+        cellType_col,
+        assay_name = "logcounts",
+        gene_ensembl = NULL,
+        gene_name = NULL) {
     # RCMD fix
     cellType.target <- NULL
     cellType <- NULL
@@ -78,10 +79,10 @@ get_mean_ratio <- function(sce,
 
     cell_types <- unique(sce[[cellType_col]])
     names(cell_types) <- cell_types
-    
+
     ct_table <- table(sce[[cellType_col]])
-    
-    if(any(ct_table < 10)) warning("One or more cell types has < 10 cells, this may result in unstable marker genes results")
+
+    if (any(ct_table < 10)) warning("One or more cell types has < 10 cells, this may result in unstable marker genes results")
 
     sce_assay <- as.matrix(SummarizedExperiment::assays(sce)[[assay_name]])
 

R/plot_composition_bar.R

@@ -27,13 +27,14 @@
 #'
 #' @importFrom dplyr rename group_by summarise mutate arrange
 #' @importFrom ggplot2 ggplot geom_bar geom_text aes theme element_text
-plot_composition_bar <- function(prop_long,
-    sample_col = "RNum",
-    x_col = "ALL",
-    prop_col = "prop",
-    ct_col = "cell_type",
-    add_text = TRUE,
-    min_prop_text = 0) {
+plot_composition_bar <- function(
+        prop_long,
+        sample_col = "RNum",
+        x_col = "ALL",
+        prop_col = "prop",
+        ct_col = "cell_type",
+        add_text = TRUE,
+        min_prop_text = 0) {
     x_cat <- cell_type <- anno_y <- NULL
 
     # ct_col <- dplyr::enquo(ct_col)
@@ -68,11 +69,12 @@ plot_composition_bar <- function(prop_long,
 }
 
 
-.get_cat_prop <- function(prop_long,
-    sample_col = "RNum",
-    x_col = "ALL",
-    prop_col = "prop",
-    ct_col = "cell_type") {
+.get_cat_prop <- function(
+        prop_long,
+        sample_col = "RNum",
+        x_col = "ALL",
+        prop_col = "prop",
+        ct_col = "cell_type") {
     cell_type <- prop <- mean_prop <- x_cat <- anno_y <- sum_prop <- n <- NULL
 
     prop_long <- prop_long |>

R/plot_gene_express.R

@@ -37,15 +37,14 @@
 #'
 #' @family expression plotting functions
 #'
-plot_gene_express <- function(
-        sce,
-        genes,
-        assay_name = "logcounts",
-        category = "cellType",
-        color_pal = NULL,
-        title = NULL,
-        plot_points = FALSE,
-        ncol = 2) {
+plot_gene_express <- function(sce,
+    genes,
+    assay_name = "logcounts",
+    category = "cellType",
+    color_pal = NULL,
+    title = NULL,
+    plot_points = FALSE,
+    ncol = 2) {
     stopifnot(any(genes %in% rownames(sce)))
 
     if (!category %in% colnames(colData(sce))) {

R/plot_marker_express.R

@@ -34,17 +34,18 @@
 #' )
 #' @family expression plotting functions
 #' @importFrom ggplot2 ggplot geom_violin geom_text facet_wrap stat_summary
-plot_marker_express <- function(sce,
-    stats,
-    cell_type,
-    n_genes = 4,
-    rank_col = "MeanRatio.rank",
-    anno_col = "MeanRatio.anno",
-    gene_col = "gene",
-    cellType_col = "cellType",
-    color_pal = NULL,
-    plot_points = FALSE,
-    ncol = 2) {
+plot_marker_express <- function(
+        sce,
+        stats,
+        cell_type,
+        n_genes = 4,
+        rank_col = "MeanRatio.rank",
+        anno_col = "MeanRatio.anno",
+        gene_col = "gene",
+        cellType_col = "cellType",
+        color_pal = NULL,
+        plot_points = FALSE,
+        ncol = 2) {
     stopifnot(cellType_col %in% colnames(colData(sce)))
     stopifnot(cell_type %in% sce[[cellType_col]])
     stopifnot(cell_type %in% stats$cellType.target)

R/plot_marker_express_ALL.R

@@ -26,7 +26,7 @@
 #' @examples
 #' #' ## Fetch sce example data
 #' if (!exists("sce_DLPFC_example")) sce_DLPFC_example <- fetch_deconvo_data("sce_DLPFC_example")
-#' 
+#'
 #' # Plot marker gene expression to PDF, one page per cell type in stats
 #' pdf_file <- tempfile("test_marker_expression_ALL", fileext = ".pdf")
 #'
@@ -42,16 +42,17 @@
 #' @importFrom ggplot2 ggplot geom_violin geom_text facet_wrap stat_summary
 #' @importFrom SummarizedExperiment colData
 #' @importFrom purrr map
-plot_marker_express_ALL <- function(sce,
-    stats,
-    pdf_fn = "marker_expression.pdf",
-    n_genes = 10,
-    rank_col = "MeanRatio.rank",
-    anno_col = "MeanRatio.anno",
-    gene_col = "gene",
-    cellType_col = "cellType",
-    color_pal = NULL,
-    plot_points = FALSE) {
+plot_marker_express_ALL <- function(
+        sce,
+        stats,
+        pdf_fn = "marker_expression.pdf",
+        n_genes = 10,
+        rank_col = "MeanRatio.rank",
+        anno_col = "MeanRatio.anno",
+        gene_col = "gene",
+        cellType_col = "cellType",
+        color_pal = NULL,
+        plot_points = FALSE) {
     stopifnot(cellType_col %in% colnames(colData(sce)))
 
     if (is.factor(sce[[cellType_col]])) {
@@ -64,29 +65,28 @@ plot_marker_express_ALL <- function(sce,
         # missing <- cell_types[!cell_types %in% stats$cellType.target]
         stop("Stats is missing cell types, check you're using the correct marker stats data and cellType_col")
     }
-
-  marker_plots <- purrr::map(
-    cell_types,
-    ~ plot_marker_express(
-      sce = sce,
-      stats = stats,
-      cell_type = .x,
-      n_genes = n_genes,
-      rank_col = rank_col,
-      anno_col = anno_col,
-      gene_col = gene_col,
-      cellType_col = cellType_col,
-      color_pal = color_pal,
-      plot_points = plot_points
+
+    marker_plots <- purrr::map(
+        cell_types,
+        ~ plot_marker_express(
+            sce = sce,
+            stats = stats,
+            cell_type = .x,
+            n_genes = n_genes,
+            rank_col = rank_col,
+            anno_col = anno_col,
+            gene_col = gene_col,
+            cellType_col = cellType_col,
+            color_pal = color_pal,
+            plot_points = plot_points
+        )
     )
-  )
 
-  if(is.null(pdf_fn)){
-    return(marker_plots)
-  } else {
-    grDevices::pdf(pdf_fn)
-    print(marker_plots)
-    grDevices::dev.off()
-  }
-
+    if (is.null(pdf_fn)) {
+        return(marker_plots)
+    } else {
+        grDevices::pdf(pdf_fn)
+        print(marker_plots)
+        grDevices::dev.off()
+    }
 }

R/plot_marker_express_List.R

@@ -24,15 +24,16 @@
 #'
 #' ## Create list-of-lists of genes to plot, names of sub-list become title of page
 #' my_gene_list <- list(Inhib = c("GAD2", "SAMD5"), Astro = c("RGS20", "PRDM16"))
-#' 
-#' # Return a list of plots 
+#'
+#' # Return a list of plots
 #' plots <- plot_marker_express_List(
 #'     sce_DLPFC_example,
 #'     gene_list = my_gene_list,
-#'     cellType_col = "cellType_broad_hc")
-#'     
+#'     cellType_col = "cellType_broad_hc"
+#' )
+#'
 #' print(plots[[1]])
-#'     
+#'
 #' # Plot marker gene expression to PDF, one page per cell type in stats
 #' pdf_file <- tempfile("test_marker_expression_List", fileext = ".pdf")
 #'
@@ -44,18 +45,17 @@
 #' )
 #'
 #' if (interactive()) browseURL(pdf_file)
-#' 
+#'
 #' @family expression plotting functions
 #' @importFrom ggplot2 ggplot geom_violin geom_text facet_wrap stat_summary
 #' @importFrom SummarizedExperiment colData
-plot_marker_express_List <- function(
-        sce,
-        gene_list,
-        pdf_fn = NULL,
-        cellType_col = "cellType",
-        gene_name_col = "gene_name",
-        color_pal = NULL,
-        plot_points = FALSE) {
+plot_marker_express_List <- function(sce,
+    gene_list,
+    pdf_fn = NULL,
+    cellType_col = "cellType",
+    gene_name_col = "gene_name",
+    color_pal = NULL,
+    plot_points = FALSE) {
     stopifnot(cellType_col %in% colnames(colData(sce)))
 
     if (!identical(rownames(sce), SummarizedExperiment::rowData(sce)[[gene_name_col]])) {
@@ -64,23 +64,22 @@ plot_marker_express_List <- function(
     }
 
     marker_plots <- purrr::map2(
-      gene_list, names(gene_list),
-      ~ plot_gene_express(
-        sce = sce,
-        genes = .x,
-        cat = cellType_col,
-        color_pal = color_pal,
-        plot_points = plot_points,
-        title = .y
-      )
+        gene_list, names(gene_list),
+        ~ plot_gene_express(
+            sce = sce,
+            genes = .x,
+            cat = cellType_col,
+            color_pal = color_pal,
+            plot_points = plot_points,
+            title = .y
+        )
     )
-    
-    if(is.null(pdf_fn)){
-      return(marker_plots)
+
+    if (is.null(pdf_fn)) {
+        return(marker_plots)
     } else {
-      grDevices::pdf(pdf_fn)
-      print(marker_plots)
-      grDevices::dev.off()
+        grDevices::pdf(pdf_fn)
+        print(marker_plots)
+        grDevices::dev.off()
     }
-
 }