[pre-commit.ci] auto fixes from pre-commit.com hooks

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omnideconv · Aug 7, 2023 · c01e13f · c01e13f
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diff --git a/R/access_sfaira.R b/R/access_sfaira.R
@@ -248,12 +248,12 @@ download_sfaira_multiple <- function(setup_list, organisms = NULL, tissues = NUL
 #' @return a dataframe with information on each dataset
 #' @export
 #'
-#' @examples 
+#' @examples
 #' \donttest{
-#'   setup_list <- setup_sfaira(basedir=tempdir())
-#'   # all_datasets <- sfaira_overview(setup_list)
+#' setup_list <- setup_sfaira(basedir = tempdir())
+#' # all_datasets <- sfaira_overview(setup_list)
 #' }
-sfaira_overview <- function(setup_list){
+sfaira_overview <- function(setup_list) {
   # create conda environment with sfaira
   proc <- basilisk::basiliskStart(SimBu_env)
   on.exit(basilisk::basiliskStop(proc))

diff --git a/R/basilisk.R b/R/basilisk.R
@@ -1,4 +1,3 @@
-
 # dependencies for sfaira and anndata0.7.6 (taken from zellkonverter package)
 SimBu_env <- basilisk::BasiliskEnvironment(
   envname = "SimBu_env_1_1_1",

diff --git a/R/census.R b/R/census.R
@@ -1,4 +1,3 @@
-
 #' Applies the Census count transformation on a count matrix
 #'
 #' needs a sparse matrix with cells in columns and genes in rows. You can find the detailed explaination here:

diff --git a/R/dataset.R b/R/dataset.R
@@ -308,7 +308,7 @@ dataset_merge <- function(dataset_list, name = "SimBu_dataset", spike_in_col = N
 #' @export
 #'
 #' @examples
-#' #h5 <- system.file("extdata", "anndata.h5ad", package = "SimBu")
+#' # h5 <- system.file("extdata", "anndata.h5ad", package = "SimBu")
 #' # ds_h5ad <- SimBu::dataset_h5ad(
 #' #  h5ad_file_counts = h5,
 #' #  name = "h5ad_dataset",

diff --git a/R/simulator.R b/R/simulator.R
@@ -69,7 +69,7 @@ simulate_sample <- function(data,
     } else {
       # how many cells of this type do we need?
       n <- round(total_cells * simulation_vector[x])
-      if(n == 0){
+      if (n == 0) {
         n <- 1
       }
       cells <- dplyr::slice_sample(cells_of_type_x, n = n, replace = TRUE)
@@ -443,22 +443,24 @@ simulate_bulk <- function(data,
     return(samples)
   }, BPPARAM = BPPARAM)
 
-  bulk_counts <- Matrix::Matrix(vapply(
-    X = all_samples,
-    FUN = "[[",
-    ... = 1,
-    FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["counts"]])[1])
-  ),
-  sparse = TRUE
-  )
-  if ("tpm" %in% names(SummarizedExperiment::assays(data))) {
-    bulk_tpm <- Matrix::Matrix(vapply(
+  bulk_counts <- Matrix::Matrix(
+    vapply(
       X = all_samples,
       FUN = "[[",
-      ... = 2,
-      FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["tpm"]])[1])
+      ... = 1,
+      FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["counts"]])[1])
     ),
     sparse = TRUE
+  )
+  if ("tpm" %in% names(SummarizedExperiment::assays(data))) {
+    bulk_tpm <- Matrix::Matrix(
+      vapply(
+        X = all_samples,
+        FUN = "[[",
+        ... = 2,
+        FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["tpm"]])[1])
+      ),
+      sparse = TRUE
     )
     assays <- list(bulk_counts = bulk_counts, bulk_tpm = bulk_tpm)
   } else {

diff --git a/README.md b/README.md
@@ -1,4 +1,3 @@
-
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
 # SimBu
@@ -10,6 +9,7 @@
 [![docs](https://img.shields.io/badge/docs-pkgdown-blue.svg)](https://omnideconv.github.io/SimBu)
 [![Codecov test
 coverage](https://codecov.io/gh/omnideconv/SimBu/branch/master/graph/badge.svg)](https://app.codecov.io/gh/omnideconv/SimBu?branch=master)
+
 <!-- badges: end -->
 
 The goal of SimBu is to simulate pseudo-bulk RNAseq datasets with
@@ -20,14 +20,14 @@ RNAseq datasets.
 
 To install the developmental version of the package, run:
 
-``` r
+```r
 install.packages("devtools")
 devtools::install_github("omnideconv/SimBu")
 ```
 
 To install from Bioconductor:
 
-``` r
+```r
 if (!require("BiocManager", quietly = TRUE)) {
   install.packages("BiocManager")
 }
@@ -40,7 +40,7 @@ BiocManager::install("SimBu")
 Create a dataset-object with local data and simulate a pseudo-bulk
 dataset
 
-``` r
+```r
 library(SimBu)
 # use local data to build dataset
 dataset <- dataset(annotation = annotation_dataframe, count_matrix = expression_matrix, name = "test_dataset")

diff --git a/tests/testthat/test_dataset.R b/tests/testthat/test_dataset.R
@@ -73,7 +73,7 @@ test_that("can create dataset from seurat object", {
 # test_that("can load h5ad file with cells in obs and var", {
 #   h5 <- system.file("extdata", "anndata.h5ad", package = "SimBu")
 #   h5_rev <- system.file("extdata", "anndata_rev.h5ad", package = "SimBu")
-# 
+#
 #   testthat::expect_s4_class(SimBu::dataset_h5ad(h5ad_file_counts = h5, name = "h5ad_dataset", cell_id_col = "id", cell_type_col = "group", cells_in_obs = TRUE), "SummarizedExperiment")
 #   testthat::expect_s4_class(SimBu::dataset_h5ad(h5ad_file_counts = h5_rev, name = "h5ad_dataset", cell_id_col = "id", cell_type_col = "group", cells_in_obs = FALSE), "SummarizedExperiment")
 # })

diff --git a/vignettes/simulator_input_output.Rmd b/vignettes/simulator_input_output.Rmd
@@ -93,14 +93,14 @@ As this function uses the `SimBu` python environment to read the h5ad files and
 
 ```{r}
 # example h5ad file, where cell type info is stored in `obs` layer
-#h5 <- system.file("extdata", "anndata.h5ad", package = "SimBu")
-#ds_h5ad <- SimBu::dataset_h5ad(
+# h5 <- system.file("extdata", "anndata.h5ad", package = "SimBu")
+# ds_h5ad <- SimBu::dataset_h5ad(
 #  h5ad_file_counts = h5,
 #  name = "h5ad_dataset",
 #  cell_id_col = 0, # this will use the rownames of the metadata as cell identifiers
 #  cell_type_col = "group", # this will use the 'group' column of the metadata as cell type info
 #  cells_in_obs = TRUE # in case your cell information is stored in the var layer, switch to FALSE
-#) 
+# )
 ```
 
 ## Merging datasets