Merge pull request #58 from stemangiola/r-cmd-check

R CMD check

Author: stemangiola

.Rbuildignore

@@ -1,10 +1,9 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
-^dev*
+^dev
 ^\.github$
 ^LICENSE\.md$
 ^README\.Rmd$
 ^doc$
 ^Meta$
 makeflow*
-dev/makeflow*

DESCRIPTION

@@ -2,9 +2,13 @@ Type: Package
 Package: CuratedAtlasQueryR
 Title: Queries the Human Cell Atlas
 Version: 0.1.0
-Authors@R: c(person("Stefano", "Mangiola", email = "[email protected]",
-                  role = c("aut", "cre"))
-                  )
+Authors@R: c(
+    person(
+        "Stefano",
+        "Mangiola",
+        email = "[email protected]",
+        role = c("aut", "cre")
+    ))
 Description: Provides access to a copy of the Human Cell Atlas, but with 
     harmonised metadata. This allows for uniform querying across numerous 
     datasets within the Atlas using common fields such as cell type, tissue 
@@ -13,8 +17,7 @@ Description: Provides access to a copy of the Human Cell Atlas, but with
     into a SingleCellExperiment object. 
 License: GPL-3
 Depends:
-    R (>= 4.2.0),
-    dbplyr (>= 2.3.0)
+    R (>= 4.2.0)
 Imports:
     dplyr,
     SummarizedExperiment,
@@ -33,7 +36,11 @@ Imports:
     methods,
     rlang,
     stats,
-    RSQLite
+    RSQLite,
+    S4Vectors,
+    tibble,
+    utils,
+    dbplyr (>= 2.3.0)
 Suggests:
     here,
     stringr,
@@ -45,7 +52,6 @@ Suggests:
     cellxgenedp,
     celldex,
     SingleR,
-    tools,
     rmarkdown,
     knitr,
     testthat,

NAMESPACE

@@ -4,15 +4,16 @@ S3method(as.sparse,DelayedMatrix)
 export(get_SingleCellExperiment)
 export(get_metadata)
 export(get_seurat)
-importClassesFrom(SingleCellExperiment,SingleCellExperiment)
+import(Seurat)
+import(dbplyr)
 importFrom(BiocGenerics,cbind)
 importFrom(DBI,dbConnect)
 importFrom(HDF5Array,HDF5RealizationSink)
 importFrom(HDF5Array,loadHDF5SummarizedExperiment)
 importFrom(RSQLite,SQLITE_RO)
 importFrom(RSQLite,SQLite)
 importFrom(S4Vectors,DataFrame)
-importFrom(Seurat,as.Seurat)
+importFrom(SeuratObject,as.Seurat)
 importFrom(SeuratObject,as.sparse)
 importFrom(SingleCellExperiment,SingleCellExperiment)
 importFrom(SingleCellExperiment,simplifyToSCE)
@@ -53,3 +54,6 @@ importFrom(rlang,.data)
 importFrom(stats,setNames)
 importFrom(tibble,column_to_rownames)
 importFrom(tools,R_user_dir)
+importFrom(utils,head)
+importFrom(utils,packageName)
+importFrom(utils,untar)

R/query.R

@@ -1,11 +1,17 @@
+# These are hacks to force the above packages to be loaded, and also to
+# satisfy R CMD check. We don't need to attach them at all.
+#' @import dbplyr 
+#' @import Seurat
+NULL
+
 # Maps user provided assay names to their corresponding paths in the repository
 assay_map <- c(
     counts = "original",
     cpm = "cpm"
 )
 
-# ' Used in a pipeline to run one or more expressions with side effects, but
-# ' return the input value as the output value unaffected
+#' Used in a pipeline to run one or more expressions with side effects, but
+#' return the input value as the output value unaffected
 aside <- function(x, ...) {
     # Courtesy of Hadley: https://fosstodon.org/@hadleywickham/109558265769090930
     list(...)
@@ -120,7 +126,7 @@ get_SingleCellExperiment <- function(
             )
 
             raw_data |>
-                dplyr::group_by(file_id_db) |>
+                dplyr::group_by(.data$file_id_db) |>
                 # Load each file and attach metadata
                 dplyr::summarise(sces = list(group_to_sce(
                     dplyr::cur_group_id(),
@@ -146,18 +152,17 @@ get_SingleCellExperiment <- function(
 
 #' Converts a data frame into a single SCE
 #'
-#' @param prefix Prefix to be added to the column names
+#' @param i Suffix to be added to the column names, to make them unique
 #' @param df The data frame to be converted
 #' @param dir_prefix The path to the single cell experiment, minus the final segment
 #' @param features The list of genes/rows of interest
-#'
 #' @return A SingleCellExperiment object
 #' @importFrom dplyr mutate
 #' @importFrom HDF5Array loadHDF5SummarizedExperiment
 #' @importFrom SummarizedExperiment colData<-
 #' @importFrom tibble column_to_rownames
-#' @importClassesFrom SingleCellExperiment SingleCellExperiment
-#'
+#' @importFrom utils head
+#' @noRd
 group_to_sce <- function(i, df, dir_prefix, features) {
     sce_path <- df$file_id_db |>
         head(1) |>
@@ -183,7 +188,7 @@ group_to_sce <- function(i, df, dir_prefix, features) {
     # variable
     new_cellnames <- paste0(cells, "_", i)
     new_coldata <- df |>
-        mutate(original_cell_id = .cell, .cell = new_cellnames) |>
+        mutate(original_cell_id = .data$.cell, .cell = new_cellnames) |>
         column_to_rownames(".cell") |>
         as("DataFrame")
 
@@ -300,18 +305,20 @@ sync_remote_file <- function(full_url, output_file, ...) {
 #'
 #' @return A length one character vector.
 #' @importFrom tools R_user_dir
+#' @importFrom utils packageName
 #' @noRd
 #'
 get_default_cache_dir <- function() {
     packageName() |>
         R_user_dir(
             "cache"
-        )
+        ) |>
+        normalizePath()
 }
 
-#' @importFrom SeuratObject as.sparse
 #' @importFrom assertthat assert_that
 #' @importFrom methods as
+#' @importFrom SeuratObject as.sparse
 #' @exportS3Method
 as.sparse.DelayedMatrix <- function(x) {
     # This is glue to ensure the SCE -> Seurat conversion works properly with
@@ -323,7 +330,7 @@ as.sparse.DelayedMatrix <- function(x) {
 #' the samples in that data frame
 #'
 #' @inheritDotParams get_SingleCellExperiment
-#' @importFrom Seurat as.Seurat
+#' @importFrom SeuratObject as.Seurat
 #' @export
 #' @return A Seurat object containing the same data as a call to
 #'   get_SingleCellExperiment.
@@ -365,7 +372,7 @@ get_seurat <- function(...) {
 #' @importFrom dplyr tbl
 #' @importFrom httr progress
 #' @importFrom cli cli_alert_info
-#'
+#' @importFrom utils untar
 get_metadata <- function(
     remote_url = "https://object-store.rc.nectar.org.au/v1/AUTH_06d6e008e3e642da99d806ba3ea629c5/metadata-sqlite/metadata.tar.xz",
     cache_directory = get_default_cache_dir()

tests/testthat/test-query.R

@@ -19,10 +19,11 @@ test_that("get_default_cache_dir() returns the correct directory on Linux", {
     grepl("linux", version$platform, fixed = TRUE) |>
         skip_if_not()
 
-    expect_equal(
-        get_default_cache_dir(),
-        "~/.cache/hca_harmonised"
-    )
+    "~/.cache/R/CuratedAtlasQueryR" |>
+        normalizePath() |>
+        expect_equal(
+            get_default_cache_dir(),
+        )
 })
 
 test_that("sync_assay_files() syncs appropriate files", {