Marker Gene Analysis and Visualization for Single-Cell Data R package CellWindX version 1.0.0 Provides a 'Seurat'-compatible toolkit for marker gene identification, expression summarization, and visualization of annotated single-cell transcriptomic data. 'CellWindX' identifies top cell-type-enriched markers, calculates marker expression percentages and average expression values across cell groups, and generates publication-oriented dimensional reduction plots, marker heatmaps, and gene-level radar plots. The package includes built-in aesthetic palettes and supports both exploratory analysis and downstream figure preparation for single-cell atlas studies. The workflow is designed to complement single-cell analysis frameworks such as 'Seurat' described by Satija et al. (2015) <doi:10.1038/nbt.3192> and Hao et al. (2021) <doi:10.1016/j.cell.2021.04.048>, as well as heatmap visualization methods implemented in 'ComplexHeatmap' described by Gu et al. (2016) <doi:10.1093/bioinformatics/btw313>. Software Depends: R (>= 4.1.0) Imports: circlize, ComplexHeatmap, dplyr, ggplot2, grDevices, grid, Matrix, patchwork, Seurat, tidyr, stats Suggests: SeuratObject Xiaofeng Yang <Youngxf02@163.com> Comprehensive R Archive Network (CRAN) Xiaofeng Yang [aut, cre] (affiliation: Chongqing Medical University), Shan Li [aut] (affiliation: Chongqing Medical University) GPL-3 2026-05-27 application/tgz https://CRAN.R-project.org/package=CellWindX doi:10.32614/CRAN.package.CellWindX