Auto updated the code style with https://github.com/LieberInstitute/s…

…patialDLPFC/blob/main/code/update_style.R

code/analysis/01_build_spe/03_add_deconvolution.R

@@ -151,19 +151,19 @@ for (sample_id in anno_samples) {
         "\\{sample_id\\}", sample_id, anno_wrinkle_path
     )
     this_anno_layers_path <- sub("\\{sample_id\\}", sample_id, anno_layers_path)
-    
+
     #   Read in wrinkle annotation and use unique and informative colnames
     anno_wrinkle <- this_anno_wrinkle_path |>
         read.csv() |>
         as_tibble() |>
         rename(wrinkle_type = ManualAnnotation, barcode = spot_name)
-    
+
     #   Read in layer annotation and use unique and informative colnames
     anno_layers <- this_anno_layers_path |>
         read.csv() |>
         as_tibble() |>
         rename(manual_layer_label = ManualAnnotation, barcode = spot_name)
-    
+
     anno_list[[sample_id]] <- anno_layers |>
         full_join(anno_wrinkle, by = c("sample_id", "barcode"))
 }
@@ -191,11 +191,11 @@ colData(spe) <- colData(spe)[, sort(colnames(colData(spe)))]
 #   Interactively double-check that the annotations merged as expected
 
 # table(is.na(spe$manual_layer_label))
-# FALSE   TRUE 
+# FALSE   TRUE
 # 11991 101936
 
 # table(is.na(spe$wrinkle_type))
-# FALSE   TRUE 
+# FALSE   TRUE
 # 2094 111833
 
 # vis_clus(spe, sampleid = anno_samples[1], clustervar = "wrinkle_type") +
@@ -271,7 +271,7 @@ session_info()
 # tz       US/Eastern
 # date     2023-02-09
 # pandoc   2.19.2 @ /jhpce/shared/jhpce/core/conda/miniconda3-4.11.0/envs/svnR-4.2.x/bin/pandoc
-# 
+#
 # ─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────
 # package                * version   date (UTC) lib source
 # AnnotationDbi            1.60.0    2022-11-01 [2] Bioconductor

code/analysis/01_build_spe/my_functions/vis_gene_300.R

@@ -1,17 +1,16 @@
 vis_gene_300 <-
-    function(
-        spe,
-        sampleid,
-        geneid = "SCGB2A2; ENSG00000110484",
-        spatial = TRUE,
-        assayname = "logcounts",
-        minCount = 0,
-        viridis = TRUE,
-        image_id = "lowres",
-        alpha = 1,
-        cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
-        point_size = 1.25,
-        ...) {
+    function(spe,
+    sampleid,
+    geneid = "SCGB2A2; ENSG00000110484",
+    spatial = TRUE,
+    assayname = "logcounts",
+    minCount = 0,
+    viridis = TRUE,
+    image_id = "lowres",
+    alpha = 1,
+    cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
+    point_size = 1.25,
+    ...) {
         spe_sub <- spe[, spe$sample_id == sampleid]
         d <- as.data.frame(cbind(colData(spe_sub), SpatialExperiment::spatialCoords(spe_sub)), optional = TRUE)
 

code/analysis/01_build_spe/my_functions/vis_gene_p_300.R

@@ -1,15 +1,14 @@
 vis_gene_p_300 <-
-    function(
-        spe,
-        d,
-        sampleid,
-        spatial,
-        title,
-        viridis = TRUE,
-        image_id = "lowres",
-        alpha = 1,
-        cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
-        point_size = 1.25) {
+    function(spe,
+    d,
+    sampleid,
+    spatial,
+    title,
+    viridis = TRUE,
+    image_id = "lowres",
+    alpha = 1,
+    cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
+    point_size = 1.25) {
         ## Some variables
         pxl_row_in_fullres <- pxl_col_in_fullres <- key <- COUNT <- NULL
         # stopifnot(all(c("pxl_col_in_fullres", "pxl_row_in_fullres", "COUNT", "key") %in% colnames(d)))

code/analysis/01_build_spe/my_functions/vis_grid_gene_300.R

@@ -1,21 +1,20 @@
 vis_grid_gene_300 <-
-    function(
-        spe,
-        geneid = "SCGB2A2; ENSG00000110484",
-        pdf_file,
-        assayname = "logcounts",
-        minCount = 0,
-        return_plots = FALSE,
-        spatial = TRUE,
-        viridis = TRUE,
-        height = 24,
-        width = 36,
-        image_id = "lowres",
-        alpha = 1,
-        cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
-        sample_order = unique(spe$sample_id),
-        point_size = 1.25,
-        ...) {
+    function(spe,
+    geneid = "SCGB2A2; ENSG00000110484",
+    pdf_file,
+    assayname = "logcounts",
+    minCount = 0,
+    return_plots = FALSE,
+    spatial = TRUE,
+    viridis = TRUE,
+    height = 24,
+    width = 36,
+    image_id = "lowres",
+    alpha = 1,
+    cont_colors = if (viridis) viridisLite::viridis(21) else c("aquamarine4", "springgreen", "goldenrod", "red"),
+    sample_order = unique(spe$sample_id),
+    point_size = 1.25,
+    ...) {
         stopifnot(all(sample_order %in% unique(spe$sample_id)))
 
         plots <- lapply(sample_order, function(sampleid) {

code/analysis/07_layer_differential_expression/custom_plotExpression.R

@@ -16,14 +16,15 @@
 #'     cat = "Mutation_Status",
 #'     fill_colors = c(negative = "green", positive = "pink")
 #' )
-custom_plotExpression <- function(sce,
-    genes,
-    assay = "logcounts",
-    cat,
-    highlight_sample = "None",
-    line = FALSE,
-    fill_colors = NULL,
-    title = NULL) {
+custom_plotExpression <- function(
+        sce,
+        genes,
+        assay = "logcounts",
+        cat,
+        highlight_sample = "None",
+        line = FALSE,
+        fill_colors = NULL,
+        title = NULL) {
     cat_df <- as.data.frame(colData(sce))[, c("sample_id", cat), drop = FALSE]
 
     expression_long <- reshape2::melt(as.matrix(assays(sce)[[assay]][genes, , drop = FALSE]))

code/analysis/08_spatial_registration/deprecated/03_custom_spatial_registration_plots.R

@@ -18,20 +18,19 @@ cor_stats_layer <- layer_stat_cor(
 )
 
 layer_matrix_plot_AS <-
-    function(
-        matrix_values,
-        matrix_labels = NULL,
-        xlabs = NULL,
-        layerHeights = NULL,
-        mypal = c(
-            "white",
-            grDevices::colorRampPalette(RColorBrewer::brewer.pal(9, "YlOrRd"))(50)
-        ),
-        breaks = NULL,
-        axis.args = NULL,
-        srt = 0,
-        mar = c(8, 4 + (max(nchar(rownames(matrix_values))) %/% 3) * 0.5, 4, 2) + 0.1,
-        cex = 1.2) {
+    function(matrix_values,
+    matrix_labels = NULL,
+    xlabs = NULL,
+    layerHeights = NULL,
+    mypal = c(
+        "white",
+        grDevices::colorRampPalette(RColorBrewer::brewer.pal(9, "YlOrRd"))(50)
+    ),
+    breaks = NULL,
+    axis.args = NULL,
+    srt = 0,
+    mar = c(8, 4 + (max(nchar(rownames(matrix_values))) %/% 3) * 0.5, 4, 2) + 0.1,
+    cex = 1.2) {
         ## Create some default values in case the user didn't specify them
         if (is.null(xlabs)) {
             if (is.null(colnames(matrix_values))) {
@@ -111,12 +110,11 @@ layer_matrix_plot_AS <-
     }
 
 layer_stat_cor_plot_AS <-
-    function(
-        cor_stats_layer,
-        max = 0.81,
-        min = -max,
-        layerHeights = NULL,
-        cex = 1.2) {
+    function(cor_stats_layer,
+    max = 0.81,
+    min = -max,
+    layerHeights = NULL,
+    cex = 1.2) {
         ## From https://github.com/LieberInstitute/HumanPilot/blob/master/Analysis/Layer_Guesses/dlpfc_snRNAseq_annotation.R
         theSeq <- seq(min, max, by = 0.01)
         my.col <- grDevices::colorRampPalette(RColorBrewer::brewer.pal(7, "PRGn"))(length(theSeq))

code/analysis/08_spatial_registration/deprecated/layer_matrix_plot_AS.R

@@ -55,20 +55,19 @@
 #'     cex = 2
 #' )
 layer_matrix_plot_AS <-
-    function(
-        matrix_values,
-        matrix_labels = NULL,
-        xlabs = NULL,
-        layerHeights = NULL,
-        mypal = c(
-            "white",
-            grDevices::colorRampPalette(RColorBrewer::brewer.pal(9, "YlOrRd"))(50)
-        ),
-        breaks = NULL,
-        axis.args = NULL,
-        srt = 45,
-        mar = c(8, 4 + (max(nchar(rownames(matrix_values))) %/% 3) * 0.5, 4, 2) + 0.1,
-        cex = 1.2) {
+    function(matrix_values,
+    matrix_labels = NULL,
+    xlabs = NULL,
+    layerHeights = NULL,
+    mypal = c(
+        "white",
+        grDevices::colorRampPalette(RColorBrewer::brewer.pal(9, "YlOrRd"))(50)
+    ),
+    breaks = NULL,
+    axis.args = NULL,
+    srt = 45,
+    mar = c(8, 4 + (max(nchar(rownames(matrix_values))) %/% 3) * 0.5, 4, 2) + 0.1,
+    cex = 1.2) {
         ## Create some default values in case the user didn't specify them
         if (is.null(xlabs)) {
             if (is.null(colnames(matrix_values))) {

code/analysis/08_spatial_registration/deprecated/layer_stat_cor_plot_AS.R

@@ -64,12 +64,11 @@
 #'     top_n = 10
 #' ), max = 0.3)
 layer_stat_cor_plot_AS <-
-    function(
-        cor_stats_layer,
-        max = 0.81,
-        min = -max,
-        layerHeights = NULL,
-        cex = 1.2) {
+    function(cor_stats_layer,
+    max = 0.81,
+    min = -max,
+    layerHeights = NULL,
+    cex = 1.2) {
         ## From https://github.com/LieberInstitute/HumanPilot/blob/master/Analysis/Layer_Guesses/dlpfc_snRNAseq_annotation.R
         theSeq <- seq(min, max, by = 0.01)
         my.col <- grDevices::colorRampPalette(RColorBrewer::brewer.pal(7, "PRGn"))(length(theSeq))

code/analysis/09_position_differential_expression/02_summarize.R

@@ -6,8 +6,10 @@ library("ggplot2")
 library("Polychrome")
 
 ## Plot directory
-dir_plots <- here::here("plots",
-    "09_position_differential_expression")
+dir_plots <- here::here(
+    "plots",
+    "09_position_differential_expression"
+)
 dir.create(dir_plots, showWarnings = FALSE, recursive = TRUE)
 stopifnot(file.exists(dir_plots))
 
@@ -24,17 +26,20 @@ sce_pseudo <-
     )
 
 ## Define variables to use
-vars <- c("age",
+vars <- c(
+    "age",
     "sample_id",
     "BayesSpace",
     "subject",
     "sex",
-    "position")
+    "position"
+)
 
 ## Obtain percent of variance explained at the gene level
 ## using scater::getVarianceExplained()
 vars <- getVarianceExplained(sce_pseudo,
-    variables = vars)
+    variables = vars
+)
 
 ## Now visualize the percent of variance explained across all genes
 pdf(
@@ -49,13 +54,15 @@ dev.off()
 
 ## Load Sp09 DE results
 load(here("code", "deploy_app_k09", "sig_genes_subset_k09.Rdata"),
-    verbose = TRUE)
+    verbose = TRUE
+)
 sig_domain <- sig_genes
 rm(sig_genes)
 
 ## Load Sp16 DE results
 load(here("code", "deploy_app_k16", "sig_genes_subset_k16.Rdata"),
-    verbose = TRUE)
+    verbose = TRUE
+)
 sig_domain_16 <- sig_genes
 rm(sig_genes)
 
@@ -92,7 +99,7 @@ pdf(
 ## Plot densities of t-statistics
 ggplot(enriched, aes(x = stat, fill = test)) +
     geom_density() +
-    facet_grid( ~ Analysis + test, margins = "test") +
+    facet_grid(~ Analysis + test, margins = "test") +
     xlab("Enrichment t-statistic") +
     scale_color_manual(values = colors, name = "Test") +
     scale_fill_manual(values = colors, name = "Test") +
@@ -103,7 +110,7 @@ ggplot(enriched, aes(x = stat, fill = test)) +
 ## Plot histogram of t-statistics with FDR < 5%
 ggplot(subset(enriched, fdr < 0.05), aes(x = stat, fill = test)) +
     geom_histogram() +
-    facet_grid( ~ Analysis + test, margins = "test") +
+    facet_grid(~ Analysis + test, margins = "test") +
     xlab("Enrichment t-statistic (FDR <5%)") +
     scale_color_manual(values = colors, name = "Test") +
     scale_fill_manual(values = colors, name = "Test") +

code/analysis/09_position_differential_expression/03_export_csvs.R

@@ -1,19 +1,23 @@
 library("here")
 library("sessioninfo")
 
-dir_rdata <- here::here("processed-data", "rdata", "spe",
-    "09_position_differential_expression")
+dir_rdata <- here::here(
+    "processed-data", "rdata", "spe",
+    "09_position_differential_expression"
+)
 stopifnot(file.exists(dir_rdata))
 
 ## Load Sp09 DE results
 load(here("code", "deploy_app_k09", "sig_genes_subset_k09.Rdata"),
-    verbose = TRUE)
+    verbose = TRUE
+)
 sig_domain_09 <- sig_genes
 rm(sig_genes)
 
 ## Load Sp16 DE results
 load(here("code", "deploy_app_k16", "sig_genes_subset_k16.Rdata"),
-    verbose = TRUE)
+    verbose = TRUE
+)
 sig_domain_16 <- sig_genes
 rm(sig_genes)