Auto-style + re-render docs

R/fetch_data.R

@@ -84,29 +84,30 @@
 #' #> 172.28 MB
 #' }
 fetch_data <-
-    function(type = c(
-        "sce",
-        "sce_layer",
-        "modeling_results",
-        "sce_example",
-        "spe",
-        "spatialDLPFC_Visium",
-        "spatialDLPFC_Visium_example_subset",
-        "spatialDLPFC_Visium_pseudobulk",
-        "spatialDLPFC_Visium_modeling_results",
-        "spatialDLPFC_Visium_SPG",
-        "spatialDLPFC_snRNAseq",
-        "Visium_SPG_AD_Visium_wholegenome_spe",
-        "Visium_SPG_AD_Visium_targeted_spe",
-        "Visium_SPG_AD_Visium_wholegenome_pseudobulk_spe",
-        "Visium_SPG_AD_Visium_wholegenome_modeling_results",
-        "Visium_LS_spe",
-        "Visium_LS_spaceranger",
-        "Visium_LS_ImageJ_out"
-    ),
-    destdir = tempdir(),
-    eh = ExperimentHub::ExperimentHub(),
-    bfc = BiocFileCache::BiocFileCache()) {
+    function(
+        type = c(
+            "sce",
+            "sce_layer",
+            "modeling_results",
+            "sce_example",
+            "spe",
+            "spatialDLPFC_Visium",
+            "spatialDLPFC_Visium_example_subset",
+            "spatialDLPFC_Visium_pseudobulk",
+            "spatialDLPFC_Visium_modeling_results",
+            "spatialDLPFC_Visium_SPG",
+            "spatialDLPFC_snRNAseq",
+            "Visium_SPG_AD_Visium_wholegenome_spe",
+            "Visium_SPG_AD_Visium_targeted_spe",
+            "Visium_SPG_AD_Visium_wholegenome_pseudobulk_spe",
+            "Visium_SPG_AD_Visium_wholegenome_modeling_results",
+            "Visium_LS_spe",
+            "Visium_LS_spaceranger",
+            "Visium_LS_ImageJ_out"
+        ),
+        destdir = tempdir(),
+        eh = ExperimentHub::ExperimentHub(),
+        bfc = BiocFileCache::BiocFileCache()) {
         ## Some variables
         sce <-
             sce_layer <- modeling_results <- sce_sub <- spe <- NULL

R/run_app.R

@@ -215,7 +215,8 @@
 #' spe_stitched$ManualAnnotation <- "NA"
 #'
 #' ## Run the app with this stitched data
-#' run_app(spe = spe_stitched,
+#' run_app(
+#'     spe = spe_stitched,
 #'     sce_layer = NULL, modeling_results = NULL, sig_genes = NULL,
 #'     title = "visiumStitched example data",
 #'     spe_discrete_vars = c("capture_area", "scran_quick_cluster", "ManualAnnotation"),
@@ -224,55 +225,56 @@
 #'     is_stitched = TRUE
 #' )
 #' }
-run_app <- function(spe = fetch_data(type = "spe"),
-    sce_layer = fetch_data(type = "sce_layer"),
-    modeling_results = fetch_data(type = "modeling_results"),
-    sig_genes = sig_genes_extract_all(
-        n = nrow(sce_layer),
-        modeling_results = modeling_results,
-        sce_layer = sce_layer
-    ),
-    docs_path = system.file("app", "www", package = "spatialLIBD"),
-    title = "spatialLIBD",
-    spe_discrete_vars = c(
-        "spatialLIBD",
-        "GraphBased",
-        "ManualAnnotation",
-        "Maynard",
-        "Martinowich",
-        paste0("SNN_k50_k", 4:28),
-        "SpatialDE_PCA",
-        "SpatialDE_pool_PCA",
-        "HVG_PCA",
-        "pseudobulk_PCA",
-        "markers_PCA",
-        "SpatialDE_UMAP",
-        "SpatialDE_pool_UMAP",
-        "HVG_UMAP",
-        "pseudobulk_UMAP",
-        "markers_UMAP",
-        "SpatialDE_PCA_spatial",
-        "SpatialDE_pool_PCA_spatial",
-        "HVG_PCA_spatial",
-        "pseudobulk_PCA_spatial",
-        "markers_PCA_spatial",
-        "SpatialDE_UMAP_spatial",
-        "SpatialDE_pool_UMAP_spatial",
-        "HVG_UMAP_spatial",
-        "pseudobulk_UMAP_spatial",
-        "markers_UMAP_spatial"
-    ),
-    spe_continuous_vars = c(
-        "cell_count",
-        "sum_umi",
-        "sum_gene",
-        "expr_chrM",
-        "expr_chrM_ratio"
-    ),
-    default_cluster = "spatialLIBD",
-    auto_crop_default = TRUE,
-    is_stitched = FALSE,
-    ...) {
+run_app <- function(
+        spe = fetch_data(type = "spe"),
+        sce_layer = fetch_data(type = "sce_layer"),
+        modeling_results = fetch_data(type = "modeling_results"),
+        sig_genes = sig_genes_extract_all(
+            n = nrow(sce_layer),
+            modeling_results = modeling_results,
+            sce_layer = sce_layer
+        ),
+        docs_path = system.file("app", "www", package = "spatialLIBD"),
+        title = "spatialLIBD",
+        spe_discrete_vars = c(
+            "spatialLIBD",
+            "GraphBased",
+            "ManualAnnotation",
+            "Maynard",
+            "Martinowich",
+            paste0("SNN_k50_k", 4:28),
+            "SpatialDE_PCA",
+            "SpatialDE_pool_PCA",
+            "HVG_PCA",
+            "pseudobulk_PCA",
+            "markers_PCA",
+            "SpatialDE_UMAP",
+            "SpatialDE_pool_UMAP",
+            "HVG_UMAP",
+            "pseudobulk_UMAP",
+            "markers_UMAP",
+            "SpatialDE_PCA_spatial",
+            "SpatialDE_pool_PCA_spatial",
+            "HVG_PCA_spatial",
+            "pseudobulk_PCA_spatial",
+            "markers_PCA_spatial",
+            "SpatialDE_UMAP_spatial",
+            "SpatialDE_pool_UMAP_spatial",
+            "HVG_UMAP_spatial",
+            "pseudobulk_UMAP_spatial",
+            "markers_UMAP_spatial"
+        ),
+        spe_continuous_vars = c(
+            "cell_count",
+            "sum_umi",
+            "sum_gene",
+            "expr_chrM",
+            "expr_chrM_ratio"
+        ),
+        default_cluster = "spatialLIBD",
+        auto_crop_default = TRUE,
+        is_stitched = FALSE,
+        ...) {
     ## Run the checks in the relevant order
     stopifnot(length(default_cluster) == 1)
     stopifnot(default_cluster %in% spe_discrete_vars)

R/vis_grid_clus.R

@@ -47,23 +47,24 @@
 #'     cowplot::plot_grid(plotlist = p_list, ncol = 2)
 #' }
 vis_grid_clus <-
-    function(spe,
-    clustervar,
-    pdf_file,
-    sort_clust = TRUE,
-    colors = NULL,
-    return_plots = FALSE,
-    spatial = TRUE,
-    height = 24,
-    width = 36,
-    image_id = "lowres",
-    alpha = NA,
-    sample_order = unique(spe$sample_id),
-    point_size = 2,
-    auto_crop = TRUE,
-    na_color = "#CCCCCC40",
-    is_stitched = FALSE,
-    ...) {
+    function(
+        spe,
+        clustervar,
+        pdf_file,
+        sort_clust = TRUE,
+        colors = NULL,
+        return_plots = FALSE,
+        spatial = TRUE,
+        height = 24,
+        width = 36,
+        image_id = "lowres",
+        alpha = NA,
+        sample_order = unique(spe$sample_id),
+        point_size = 2,
+        auto_crop = TRUE,
+        na_color = "#CCCCCC40",
+        is_stitched = FALSE,
+        ...) {
         stopifnot(all(sample_order %in% unique(spe$sample_id)))
 
         if (sort_clust) {

R/vis_grid_gene.R

@@ -35,25 +35,26 @@
 #'     cowplot::plot_grid(plotlist = p_list, ncol = 2)
 #' }
 vis_grid_gene <-
-    function(spe,
-    geneid = rowData(spe)$gene_search[1],
-    pdf_file,
-    assayname = "logcounts",
-    minCount = 0,
-    return_plots = FALSE,
-    spatial = TRUE,
-    viridis = TRUE,
-    height = 24,
-    width = 36,
-    image_id = "lowres",
-    alpha = NA,
-    cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
-    sample_order = unique(spe$sample_id),
-    point_size = 2,
-    auto_crop = TRUE,
-    na_color = "#CCCCCC40",
-    is_stitched = FALSE,
-    ...) {
+    function(
+        spe,
+        geneid = rowData(spe)$gene_search[1],
+        pdf_file,
+        assayname = "logcounts",
+        minCount = 0,
+        return_plots = FALSE,
+        spatial = TRUE,
+        viridis = TRUE,
+        height = 24,
+        width = 36,
+        image_id = "lowres",
+        alpha = NA,
+        cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
+        sample_order = unique(spe$sample_id),
+        point_size = 2,
+        auto_crop = TRUE,
+        na_color = "#CCCCCC40",
+        is_stitched = FALSE,
+        ...) {
         stopifnot(all(sample_order %in% unique(spe$sample_id)))
 
         plots <- lapply(sample_order, function(sampleid) {