R Observatory: Metrics for SlimR version 1.2.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

SlimR

1.2.0Package record

Adaptive Machine Learning-Powered, Context-Matching Tool for Single-Cell and Spatial Transcriptomics Annotation

0packages depend

4.8Kdownloads / year

24.3%test coverage

13/13flavors OK

Overview

About

Maintained by Zhaoqing WangCRAN page ↗GitHub ↗Issues ↗

Annotates single-cell and spatial-transcriptomic (ST) data using context-matching marker datasets. It creates a unified marker list (`Markers_list`) from multiple sources: built-in curated databases ('Cellmarker2', 'PanglaoDB', 'ScType', 'CellTypist', 'scBaseCount', 'scIBD', 'TCellSI', 'PCTIT', 'PCTAM'), Seurat objects with cell labels, or user-provided Excel tables. SlimR first uses adaptive machine learning for parameter optimization, and then offers two automated annotation approaches: 'cluster-based' and 'per-cell'. Cluster-based annotation assigns one label per cluster, expression-based probability calculation, and AUC validation. Per-cell annotation assigns labels to individual cells using three scoring methods with adaptive thresholds and ratio-based confidence filtering, plus optional UMAP spatial smoothing, making it ideal for heterogeneous clusters and rare cell types. The package also supports semi-automated workflows with heatmaps, feature plots, and combined visualizations for manual annotation. For more information, see the package documentation at https://github.com/zhaoqing-wang/SlimR.

Changes in 1.2.0

**New Features**
Added the scBaseCount database, covering Human, Mouse, Drosophila, and Zebrafish, with four species-specific marker gene set lists: human_gene_sets, mouse_gene_sets, fly_gene_sets, and zebrafish_gene_sets.
New function Compute_Gene_PRC(): Computes PRC-AUC (Average Precision) and the no-skill baseline for a single gene against a user-defined cell group. Complements Compute_Gene_AUC_ROC() and is better suited to rare cell types under dropout and background contamination.
**Improvements**
Added roxygen2 documentation and citation for scBaseCount (Youngblut et al., 2026, doi:10.1016/j.cell.2026.08.025), plus README section 2.5.
Added README section 5.3 for single-gene PRC-AUC analysis.
Updated general documentation and README structure.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("SlimR", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("zhaoqing-wang/SlimR")

Development version from zhaoqing-wang/SlimR. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-slimr

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-SlimR

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-SlimR

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 8.3 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-09-08
ERROR12 OK, 1 ERROR2026-09-07
OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09

Show 4 earlier changesHide 4 earlier changes

ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-04-10
ERROR13 OK, 1 ERROR2026-04-09
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

Documentation signals are not tracked yet for this package.

Websitenot declared in DESCRIPTION

How these are measured

Downloads

4.8K

CRAN downloads in the past year

Rank #8,144 · ~13/day · ~396/mo

SlimR Releases R versions

Daily download trend is not available in this view yet.

42730 days

1.1K90 days

4.8K1 year

Compare downloads with other packages →

Also on177 r2u5 autocran

How downloads are counted

Repository

zhaoqing-wang/slimr ↗Account: zhaoqing-wang

8Stars

2Forks

1Open issues

0Open PRs

20Releases

358Commits

1Commit identities

358 commits · Last activity 2026-10-16 · 0% stars, 30d

Responsiveness

not measured

How these are measured

PracticesBeta

Checks run against github.com/zhaoqing-wang/slimr on 2026-10-11.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

16 external dependencies (excludes base and recommended)

Installing SlimR adds 143 packages (82 with compiled code, 129 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (1)

R >= 4.1.0

Imports (14)

cowplot dplyr ggplot2 patchwork pheatmap readxl scales Seurat tidyrtoolstibble gtools RColorBrewermethods

LinkingTo (0)

none

Suggests (4)

crayon RANN testthat WeightedTreemaps

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (1)

Zhaoqing Wang

Author, Maintainer · added in 1.0.8

Maintainer since 1.0.3 (2025)

Listed in earlier versions (1)

Zhao qing Wang

no longer listed · 1.0.3 to 1.0.7

Releases (13)

1.2.0Latest
record
2026-10-16 · current release · diff ↗ ·
added 2 exports
Compute_Gene_PRC, Plot_Group_Gene_Heatmap
·
listed once in CRAN's queue
Seen in one reading of CRAN's incoming queue, at 2026-10-16 02:28 UTC, so it stayed less than the time between readings.
1.1.8
record
2026-07-31 · diff ↗ ·
added 1 export
paletteDiscrete
1.1.7
record
2026-07-22 · diff ↗ ·
added 2 exports
Plot_Hierarchy_Proportion, Plot_Voronoi_diagram
1.1.6
record
2026-06-30 · diff ↗ ·
added 1 export
Compute_Gene_AUC_ROC
1.1.5
record
2026-06-03 · diff ↗ ·
added 1 export
Celltype_Compare
R
R 4.6.0 released · 2026-04-24
1.1.3
record
2026-04-07 · diff ↗
1.1.2
record
2026-03-13 · diff ↗ ·
added 1 export
Markers_filter_ScType
1.1.1
record
2026-02-05 · diff ↗ ·
added 3 exports
Celltype_Annotation_PerCell, Celltype_Calculate_PerCell, Celltype_Verification_PerCell
1.1.0
record
2026-01-20 · diff ↗
1.0.9
record
2025-12-17 · diff ↗
1.0.8
record
2025-10-08 · diff ↗ ·
added 1 export
Parameter_Calculate
1.0.7
record
2025-08-19 · diff ↗ ·
removed 4 exports
Celltype_annotation_Box, Celltype_annotation_Heatmap, read_excel_markers, read_seurat_markers

added 8 exports
Celltype_Annotation, Celltype_Annotation_Combined, Celltype_Annotation_Features, Celltype_Annotation_Heatmap, Celltype_Calculate, Celltype_Verification, Read_excel_markers, Read_seurat_markers
1.0.3
record
2025-07-29
R
R 4.5.0 released · 2025-04-11

Across CRAN, the median accepted release of the past year spent 15 hours in the queue, 90% under 11 days.How queue time is measured

Package metadata

First published: 2025-07-29
Total releases: 13 / 1 yrs
License: MIT + file LICENSE OSI · relicensed from GPL-3 in 1.0.7
Download size: 3.5 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SlimR")

Format

Wang, Z. (2026). SlimR: Adaptive Machine Learning-Powered, Context-Matching Tool for Single-Cell and Spatial Transcriptomics Annotation (Version 1.2.0) [Computer software]. https://doi.org/10.32614/CRAN.package.SlimR

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SlimR version 1.2.0 [Data set]. HJJB, LLC. Data release v2026-10-19. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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