Package: SlimR Version: 1.1.6 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 . 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 Suggests: crayon, RANN, testthat (>= 3.0.0) Encoding: UTF-8 LazyData: true Roxygen: list(markdown = TRUE) Date: 2026-06-30 Config/roxygen2/version: 8.0.0 Config/pak/sysreqs: cmake libglpk-dev make libicu-dev libpng-dev libuv1-dev libxml2-dev libssl-dev python3 zlib1g-dev Repository: https://zhaoqing-wang.r-universe.dev Date/Publication: 2026-07-01 16:19:14 UTC RemoteUrl: https://github.com/zhaoqing-wang/slimr RemoteRef: HEAD RemoteSha: d84f47d462b1e0cb65978df2791f4b0d9eee7c89 NeedsCompilation: no Packaged: 2026-07-01 17:58:02 UTC; root Author: Zhaoqing Wang [aut, cre] (ORCID: ) Maintainer: Zhaoqing Wang