Package: SlimR
Version: 1.1.7
Title: Adaptive Machine Learning-Powered, Context-Matching Tool for
        Single-Cell and Spatial Transcriptomics Annotation
Description: 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', '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>.
Authors@R: 
    person(given = "Zhaoqing",family = "Wang",
           email = c("zhaoqingwang@mail.sdu.edu.cn"),
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0001-8348-7245"))
License: MIT + file LICENSE
URL: https://github.com/zhaoqing-wang/SlimR
BugReports: https://github.com/zhaoqing-wang/SlimR/issues
Depends: R (>= 4.1.0)
Imports: cowplot, dplyr, ggplot2, patchwork, pheatmap, readxl, scales,
        Seurat, tidyr, tools, tibble, gtools
Suggests: crayon, RANN, testthat (>= 3.0.0), WeightedTreemaps
Encoding: UTF-8
LazyData: true
Date: 2026-07-22
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-07-22 15:44:32 UTC; Runaw
Author: Zhaoqing Wang [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-8348-7245>)
Maintainer: Zhaoqing Wang <zhaoqingwang@mail.sdu.edu.cn>
Repository: CRAN
Date/Publication: 2026-07-22 16:00:09 UTC
Built: R 4.5.3; ; 2026-07-27 00:02:15 UTC; windows
