Marker Gene Analysis and Visualization for Single-Cell Data

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) and Hao et al. (2021) , as well as heatmap visualization methods implemented in 'ComplexHeatmap' described by Gu et al. (2016) .


Reference manual

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install.packages("CellWindX")

1.0.0 by Xiaofeng Yang, 4 months ago


Browse source code at https://github.com/cran/CellWindX


Authors: Xiaofeng Yang [aut, cre] (affiliation: Chongqing Medical University) , Shan Li [aut] (affiliation: Chongqing Medical University)


Documentation:   PDF Manual  


GPL-3 license


Imports circlize, ComplexHeatmap, dplyr, ggplot2, grDevices, grid, Matrix, patchwork, Seurat, tidyr, stats

Suggests SeuratObject


See at CRAN