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Merge pull request #83 from HelenaLC/master
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cleaning `BiocCheck()`; linting revision; GHA bump to Bioc devel
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stemangiola authored Aug 21, 2023
2 parents d05b3fd + 0464ebc commit 797cf25
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18 changes: 9 additions & 9 deletions .github/workflows/check-bioc.yml
Original file line number Diff line number Diff line change
Expand Up @@ -52,9 +52,9 @@ jobs:
fail-fast: false
matrix:
config:
- { os: ubuntu-latest, r: '4.3', bioc: '3.17', cont: "bioconductor/bioconductor_docker:RELEASE_3_17", rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest" }
- { os: macOS-latest, r: '4.3', bioc: '3.17'}
- { os: windows-latest, r: '4.3', bioc: '3.17'}
- { os: ubuntu-latest, r: '4.3', bioc: '3.18', cont: "bioconductor/bioconductor_docker:devel", rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest" }
- { os: macOS-latest, r: '4.3', bioc: '3.18'}
- { os: windows-latest, r: '4.3', bioc: '3.18'}
## Check https://github.com/r-lib/actions/tree/master/examples
## for examples using the http-user-agent
env:
Expand Down Expand Up @@ -105,16 +105,16 @@ jobs:
uses: actions/cache@v3
with:
path: ${{ env.R_LIBS_USER }}
key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-${{ hashFiles('.github/depends.Rds') }}
restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-
key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-devel-r-4.3-${{ hashFiles('.github/depends.Rds') }}
restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-devel-r-4.3-

- name: Cache R packages on Linux
if: "!contains(github.event.head_commit.message, '/nocache') && runner.os == 'Linux' "
uses: actions/cache@v3
with:
path: /home/runner/work/_temp/Library
key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-${{ hashFiles('.github/depends.Rds') }}
restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-
key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-devel-r-4.3-${{ hashFiles('.github/depends.Rds') }}
restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-devel-r-4.3-

# - name: Install Linux system dependencies
# if: runner.os == 'Linux'
Expand Down Expand Up @@ -202,7 +202,7 @@ jobs:
- name: Install pkgdown
if: github.ref == 'refs/heads/devel' && env.run_pkgdown == 'true' && runner.os == 'Linux'
run: |
remotes::install_cran("pkgdown")
remotes::install_github("r-lib/pkgdown")
shell: Rscript {0}

- name: Session info
Expand Down Expand Up @@ -285,7 +285,7 @@ jobs:
if: failure()
uses: actions/upload-artifact@master
with:
name: ${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-results
name: ${{ runner.os }}-biocversion-devel-r-4.3-results
path: check


Expand Down
7 changes: 4 additions & 3 deletions DESCRIPTION
Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,9 @@ Package: tidySingleCellExperiment
Title: Brings SingleCellExperiment to the Tidyverse
Version: 1.11.4
Authors@R: c(person("Stefano", "Mangiola",
comment=c(ORCID="0000-0001-7474-836X"),
email="[email protected]",
role=c("aut", "cre")))
role=c("aut", "cre")))
Description: 'tidySingleCellExperiment' is an adapter that abstracts
the 'SingleCellExperiment' container in the form of a 'tibble'.
This allows *tidy* data manipulation, nesting, and plotting.
Expand Down Expand Up @@ -61,10 +62,10 @@ VignetteBuilder:
RdMacros:
lifecycle
Biarch: true
biocViews: AssayDomain, Infrastructure, RNASeq, DifferentialExpression,
biocViews:
AssayDomain, Infrastructure, RNASeq, DifferentialExpression, SingleCell,
GeneExpression, Normalization, Clustering, QualityControl, Sequencing
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
URL: https://github.com/stemangiola/tidySingleCellExperiment
BugReports: https://github.com/stemangiola/tidySingleCellExperiment/issues
9 changes: 7 additions & 2 deletions NAMESPACE
Original file line number Diff line number Diff line change
Expand Up @@ -50,10 +50,15 @@ importFrom(S4Vectors,"metadata<-")
importFrom(S4Vectors,DataFrame)
importFrom(S4Vectors,metadata)
importFrom(SingleCellExperiment,cbind)
importFrom(SingleCellExperiment,reducedDims)
importFrom(SummarizedExperiment,"assays<-")
importFrom(SummarizedExperiment,"colData<-")
importFrom(SummarizedExperiment,assay)
importFrom(SummarizedExperiment,assayNames)
importFrom(SummarizedExperiment,assays)
importFrom(SummarizedExperiment,colData)
importFrom(dplyr,add_count)
importFrom(dplyr,any_of)
importFrom(dplyr,arrange)
importFrom(dplyr,contains)
importFrom(dplyr,count)
Expand All @@ -74,12 +79,10 @@ importFrom(dplyr,rowwise)
importFrom(dplyr,sample_frac)
importFrom(dplyr,sample_n)
importFrom(dplyr,select)
importFrom(dplyr,select_if)
importFrom(dplyr,slice)
importFrom(dplyr,summarise)
importFrom(dplyr,summarize)
importFrom(dplyr,vars)
importFrom(ellipsis,check_dots_unnamed)
importFrom(ellipsis,check_dots_used)
importFrom(fansi,strwrap_ctl)
importFrom(ggplot2,aes)
Expand All @@ -90,6 +93,7 @@ importFrom(magrittr,"%>%")
importFrom(magrittr,equals)
importFrom(magrittr,set_rownames)
importFrom(methods,getMethod)
importFrom(methods,is)
importFrom(pillar,align)
importFrom(pillar,get_extent)
importFrom(pillar,style_subtle)
Expand Down Expand Up @@ -127,6 +131,7 @@ importFrom(tidyr,extract)
importFrom(tidyr,nest)
importFrom(tidyr,pivot_longer)
importFrom(tidyr,separate)
importFrom(tidyr,spread)
importFrom(tidyr,unite)
importFrom(tidyr,unnest)
importFrom(tidyselect,eval_select)
Expand Down
21 changes: 11 additions & 10 deletions R/attach.R
Original file line number Diff line number Diff line change
@@ -1,22 +1,23 @@
core <- c("dplyr", "tidyr", "ttservice", "ggplot2")

core_unloaded <- function() {
search <- paste0("package:", core)
core[!search %in% search()]
search <- paste0("package:", core)
core[!search %in% search()]
}

# Attach the package from the same library it was loaded from before.
# [source: https://github.com/tidy-biology/tidyverse/issues/171]
same_library <- function(pkg) {
loc <- if (pkg %in% loadedNamespaces()) dirname(getNamespaceInfo(pkg, "path"))
library(pkg, lib.loc=loc, character.only=TRUE, warn.conflicts=FALSE)
loc <- if (pkg %in% loadedNamespaces())
dirname(getNamespaceInfo(pkg, "path"))
library(pkg, lib.loc=loc, character.only=TRUE, warn.conflicts=FALSE)
}

tidyverse_attach <- function() {
to_load <- core_unloaded()

suppressPackageStartupMessages(
lapply(to_load, same_library))

invisible(to_load)
to_load <- core_unloaded()
suppressPackageStartupMessages(
lapply(to_load, same_library))
invisible(to_load)
}
29 changes: 18 additions & 11 deletions R/data.R
Original file line number Diff line number Diff line change
@@ -1,35 +1,41 @@
#' pbmc_small
#'
#' PBMC single cell RNA-seq data in SingleCellExperiment format
#' PBMC single cell RNA-seq data in `SingleCellExperiment` format.
#'
#' @format A SingleCellExperiment object containing 80 Peripheral Blood
#' Mononuclear Cells (PBMC) from 10x Genomics. Generated by subsampling the PBMC dataset of 2,700 single cells.
#' @format A `SingleCellExperiment` object containing 80 Peripheral Blood
#' Mononuclear Cells (PBMC) from 10x Genomics. Generated by subsampling
#' the PBMC dataset of 2,700 single cells.
#' @source \url{https://satijalab.org/seurat/v3.1/pbmc3k_tutorial.html}
#' @usage data(pbmc_small)
#' @return `tidySingleCellExperiment`
"pbmc_small"

#' Cell types of 80 PBMC single cells
#'
#' A dataset containing the barcodes and cell types of 80 PBMC single cells.
#'
#' @format A tibble containing 80 rows and 2 columns. Cells are a subsample of
#' the Peripheral Blood Mononuclear Cells (PBMC) dataset of 2,700 single
#' cell. Cell types were identified with SingleR.
#' @format A tibble containing 80 rows and 2 columns.
#' Cells are a subsample of the Peripheral Blood Mononuclear Cells (PBMC)
#' dataset of 2,700 single cell. Cell types were identified with SingleR.
#' \describe{
#' \item{cell}{cell identifier, barcode}
#' \item{first.labels}{cell type}
#' }
#' @source \url{https://satijalab.org/seurat/v3.1/pbmc3k_tutorial.html}
#' @usage data(cell_type_df)
#' @return `tibble`
"cell_type_df"

#' Intercellular ligand-receptor interactions for 38 ligands from a single cell RNA-seq cluster.
#' Intercellular ligand-receptor interactions for
#' 38 ligands from a single cell RNA-seq cluster.
#'
#' A dataset containing ligand-receptor interactions withibn a sample. There are 38 ligands from a single cell cluster versus
#' 35 receptors in 6 other clusters.
#' A dataset containing ligand-receptor interactions within a sample.
#' There are 38 ligands from a single cell cluster versus 35 receptors
#' in 6 other clusters.
#'
#' @format A tibble containing 100 rows and 9 columns. Cells are a subsample of
#' the PBMC dataset of 2,700 single cells. Cell interactions were identified with SingleCellSignalR.
#' @format A `tibble` containing 100 rows and 9 columns.
#' Cells are a subsample of the PBMC dataset of 2,700 single cells.
#' Cell interactions were identified with `SingleCellSignalR`.
#' \describe{
#' \item{sample}{sample identifier}
#' \item{ligand}{cluster and ligand identifier}
Expand All @@ -43,4 +49,5 @@
#' }
#' @source \url{https://satijalab.org/seurat/v3.1/pbmc3k_tutorial.html}
#' @usage data(pbmc_small_nested_interactions)
#' @return `tibble`
"pbmc_small_nested_interactions"
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