fixes for Bioc 3.19 release

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: CATALYST
 Type: Package
 Title: Cytometry dATa anALYSis Tools
-Version: 1.26.0
+Version: 1.26.1
 Depends: R (>= 4.2), SingleCellExperiment
 Authors@R: c(
 	person("Helena L.", "Crowell", 
@@ -44,7 +44,7 @@ Suggests:
 URL: https://github.com/HelenaLC/CATALYST
 BugReports: https://github.com/HelenaLC/CATALYST/issues
 VignetteBuilder: knitr
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 License: GPL (>=2)
 Encoding: UTF-8
 LazyData: true

NEWS

@@ -1,3 +1,13 @@
+changes in version 1.26.1
+
++ fixed typoes in man pages and vignette
++ fixed unit test failures due to 'ggplot2'-updates etc.
++ omit usage of ':::' operator throughout the package
+
+changes in version 1.26.0
+
++ Bioc 3.18 release
+
 changes in version 1.25.1
 
 + fixed unit tests for differential plotting

R/clrDR.R

@@ -33,7 +33,7 @@
 #'   of cells in a given sample/cluster (for \code{by = "sample/cluster_id"}).
 #' @param point_pal,arrow_pal character string of colors to use
 #'   for points and PC loading arrows. Arguments default to
-#'   \code{CATALYST:::.cluster_cols} for clusters,
+#'   \code{.cluster_cols} for clusters (defined internally),
 #'   and \code{brewer.pal}'s \code{"Set3"} for samples.
 #' @inheritParams runDR
 #' @inheritParams pbMDS
@@ -43,7 +43,7 @@
 #' \describe{
 #' \item{The centered log-ratio (CLR)}{
 #' Let \code{k} be one of \eqn{S} samples, \code{k} one of \eqn{K} clusters,
-#' and \code{p(s,k)} be the proprtion of cells from \code{s} in \eqn{k}.
+#' and \code{p(s,k)} be the proportion of cells from \code{s} in \eqn{k}.
 #' The centered log-ratio (CLR) is defined as
 #' \deqn{clr(sk) = log p(s,k) - \sum p(s,k) / K}
 #' and analogous for clusters replacing \code{s} by \code{k} and \code{K} by

R/pbMDS.R

@@ -120,11 +120,13 @@ pbMDS <- function(x,
     # get number of legend columns to use
     ncol <- ifelse(!is.null(color_by) && nlevels(df[[color_by]]) > 10, 2, 1)
 
-    ggplot(df, aes_string("x", "y", 
-        col = color_by, shape = shape_by)) + 
-        geom_point(alpha = 0.8, aes_string(size = size_by)) + 
+    ggplot(df, aes(.data$x, .data$y, 
+        col = if (!is.null(color_by)) .data[[color_by]], 
+        shape = if (!is.null(shape_by)) .data[[shape_by]])) + 
+        geom_point(alpha = 0.8, 
+            aes(size = if (!is.null(size_by)) .data[[size_by]])) + 
         (if (!is.null(label_by)) geom_label_repel(
-            aes_string(label = label_by), show.legend = FALSE)) + 
+            aes(label = .data[[label_by]]), show.legend = FALSE)) + 
         (if (!is.null(pal)) scale_color_manual(values = pal)) +
         scale_shape_manual(values = .get_shapes(x, shape_by)) +
         guides(
@@ -134,7 +136,8 @@ pbMDS <- function(x,
             size = guide_legend(order = 3)) + 
         labs(
             x = paste("MDS dim.", dims[1]), 
-            y = paste("MDS dim.", dims[2])) +
+            y = paste("MDS dim.", dims[2]),
+            col=color_by, shape=shape_by, size=size_by) +
         coord_equal() + theme_linedraw() + theme(
             panel.grid.minor = element_blank(),
             legend.key.height  =  unit(0.8, "lines"))

R/plotAbundances.R

@@ -76,7 +76,7 @@ plotAbundances <- function(x, k = "meta20",
     linkage = c(
         "average", "ward.D", "single", "complete", 
         "mcquitty", "median", "centroid", "ward.D2"),
-    k_pal = CATALYST:::.cluster_cols) {
+    k_pal = .cluster_cols) {
 
     # check validity of input arguments
     by <- match.arg(by)

R/plotCodes.R

@@ -42,8 +42,7 @@
 #' @importFrom S4Vectors metadata
 #' @export
 
-plotCodes <- function(x, k = "meta20", 
-    k_pal = CATALYST:::.cluster_cols) {
+plotCodes <- function(x, k = "meta20", k_pal = .cluster_cols) {
 
     # check validity of input arguments
     .check_sce(x, TRUE)
@@ -92,7 +91,7 @@ plotCodes <- function(x, k = "meta20",
     )
 
     # arrange plots side-by-side
-    lgd <- get_legend(ps[[2]])
+    suppressWarnings(lgd <- get_legend(ps[[2]]))
     ps <- lapply(ps, "+", theme(legend.position = "none"))
     plot_grid(
         lgd, ncol = 1, rel_heights = c(1, 5),

R/plotDR.R

@@ -82,8 +82,7 @@
 plotDR <- function(x, dr = NULL, 
     color_by = "condition", facet_by = NULL, ncol = NULL,
     assay = "exprs", scale = TRUE, q = 0.01, dims = c(1, 2),
-    k_pal = CATALYST:::.cluster_cols, 
-    a_pal = hcl.colors(10, "Viridis")) {
+    k_pal = .cluster_cols, a_pal = hcl.colors(10, "Viridis")) {
 
     # check validity of input arguments
     stopifnot(

R/plotExprHeatmap.R

@@ -141,7 +141,7 @@ plotExprHeatmap <- function(x, features = NULL,
     row_dend = TRUE, col_dend = TRUE, 
     bars = FALSE, perc = FALSE, bin_anno = FALSE,
     hm_pal = rev(brewer.pal(11, "RdYlBu")), 
-    k_pal = CATALYST:::.cluster_cols, m_pal = k_pal,
+    k_pal = .cluster_cols, m_pal = k_pal,
     distance = c(
         "euclidean", "maximum", "manhattan", 
         "canberra", "binary", "minkowski"), 

R/plotFreqHeatmap.R

@@ -75,7 +75,7 @@ plotFreqHeatmap <- function(x,
     row_dend = TRUE, col_dend = TRUE,
     bars = TRUE, perc = FALSE,
     hm_pal = rev(brewer.pal(11, "RdBu")),
-    k_pal = CATALYST:::.cluster_cols, m_pal = k_pal) {
+    k_pal = .cluster_cols, m_pal = k_pal) {
 
     # check validity of input arguments
     args <- as.list(environment())

R/plotMahal.R

@@ -116,7 +116,7 @@ plotMahal <- function(x, which, assay = "exprs", n = 1e3) {
                         legend.key.width = unit(4, "line"),
                         legend.text = element_text(size = 8), 
                         legend.key = element_blank())
-                lgd <- get_legend(foo)
+                suppressWarnings(lgd <- get_legend(foo))
                 first <- FALSE
             }
         }

R/plotMultiHeatmap.R

@@ -134,7 +134,7 @@ plotMultiHeatmap <- function(x,
     hm1_pal = rev(brewer.pal(11, "RdYlBu")), 
     hm2_pal = if (isTRUE(hm2 == "abundances")) 
         rev(brewer.pal(11, "PuOr")) else hm1_pal,
-    k_pal = CATALYST:::.cluster_cols, m_pal = k_pal,
+    k_pal = .cluster_cols, m_pal = k_pal,
     distance = c(
         "euclidean", "maximum", "manhattan", 
         "canberra", "binary", "minkowski"), 

R/plotScatter.R

@@ -67,7 +67,7 @@
 plotScatter <- function(x, chs, color_by = NULL, facet_by = NULL,
     bins = 100, assay = "exprs", 
     label = c("target", "channel", "both"),
-    zeros = FALSE, k_pal = CATALYST:::.cluster_cols) {
+    zeros = FALSE, k_pal = .cluster_cols) {
     # check validity of input arguments
     label <- match.arg(label)
     args <- as.list(environment())

tests/testthat/test_plotDiffHeatmap.R

@@ -33,7 +33,7 @@ test_that("plotDiffHeatmap() - DA", {
     y <- p@matrix
     expect_gte(min(y), 0)
     expect_lte(max(y), 1)
-    expect_true(all(colSums(y) == 1))
+    expect_equivalent(colSums(y), rep(1, ncol(y)))
     expect_equal(dim(y), c(nlevels(kids), nlevels(x$sample_id)))
     expect_identical(rownames(y), levels(kids))
     expect_identical(colnames(y), levels(x$sample_id))
@@ -78,6 +78,7 @@ test_that("plotDiffHeatmap() - DS; cluster filtering", {
         expect_true(!any(ks %in% hm_ks))
     }
 })
+
 test_that("plotDiffHeatmap() - DS; marker filtering", {
     for (ms in lapply(c(1, 3, 5), sample, x = state_markers(x))) {
         n <- sample(nlevels(kids)-5, 1)

tests/testthat/test_plotMultiHeatmap.R

@@ -23,7 +23,7 @@ test_that("plotMultiHeatmap() - hm2 = 'abundances'", {
     p <- plotMultiHeatmap(x, hm2 = "abundances", k = k, normalize = FALSE)
     y <- p@ht_list$frequency@matrix
     expect_is(p, "HeatmapList")
-    expect_true(all(colSums(y) == 1))
+    expect_equivalent(colSums(y), rep(1, ncol(y)))
     expect_equal(c(y), c(prop.table(table(kids, x$sample_id), 2)))
 })
 
@@ -40,7 +40,7 @@ test_that("plotMultiHeatmap() - hm2 = 'state'", {
         summarize_at(state_markers(x), median) %>% 
         do(.[, state_markers(x)]) %>% 
         do.call(what = "cbind")
-    expect_identical(c(y), c(ms))
+    expect_equal(c(y), c(ms))
 })
 
 test_that("plotMultiHeatmap() - hm2 = specific state markers", {
@@ -54,8 +54,8 @@ test_that("plotMultiHeatmap() - hm2 = specific state markers", {
         replace(., is.na(.), 0) %>% {( lapply(ms, function(m) 
             acast(., cluster_id~sample_id, value.var = m)) )}
     for (i in seq_along(ms)) {
-        expect_identical(p@ht_list[[i+1]]@column_title, ms[i])
-        expect_identical(p@ht_list[[i+1]]@matrix, meds[[i]])
+        expect_equal(p@ht_list[[i+1]]@column_title, ms[i])
+        expect_equal(p@ht_list[[i+1]]@matrix, meds[[i]])
     }
 })
 

tests/testthat/test_plotScatter.R

@@ -36,5 +36,5 @@ test_that("plotScatter() - color_by", {
     expect_is(p$scales$scales[[1]], "ScaleContinuous")    
     p <- plotScatter(x, chs, color_by = "bc_id")
     expect_is(p, "ggplot")
-    expect_is(p$guides$colour, "guide")
+    expect_is(p$guides$guides[[1]], "GuideLegend")
 })

vignettes/differential.Rmd

@@ -124,7 +124,7 @@ Let K = `xdim` x `ydim` be the number of `r BiocStyle::Biocpkg("FlowSOM")` clust
 - `rowData`:
   - `cluster_id`: cluster ID as inferred by `r BiocStyle::Biocpkg("FlowSOM")`. One of 1, ..., K.
 - `colData`:
-  - `marker_class`: factor `"type"` or `"state"`. Specifyies whether a marker has been used for clustering or not, respectively.
+  - `marker_class`: factor `"type"` or `"state"`. Specifies whether a marker has been used for clustering or not, respectively.
 - `metadata`:
   - `SOM_codes`: a table with dimensions K x (# type markers). Contains the SOM codes. 
   - `cluster_codes`: a table with dimensions K x (`maxK` + 1). Contains the cluster codes for all metaclusterings.