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scPyviewer
xuan13hao edited this page Sep 4, 2026
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scPyviewer is an open-source, lightweight, and high-performance Python-native interactive web viewer for single-cell RNA-seq datasets (.h5ad / AnnData objects).
- Quick Start Guide - Get up and running in under 2 minutes.
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Installation & Deployment - Setup via
pip, local deployment, and HPC server workflows. - Core Features & Usage - Comprehensive guide to cell cluster viewing, gene expression mapping, and metadata filters.
- Publication-Ready Plotting - Customize, export, and download high-resolution vector figures.
- FAQ & Troubleshooting - Solutions for common issues and performance tuning for large datasets.
- Native AnnData / Python First: No need to export your data to R/Seurat or deal with complex object conversions.
- Instant Interactive Exploration: Seamlessly query cell clusters, marker genes, and metadata distributions.
- Collaboration Made Easy: Share interactive dashboards directly with biological collaborators without requiring them to write code.
- High Performance: Optimized for fast rendering even with large single-cell cohorts.
If you use scPyviewer in your research, please cite our pre-print:
Xuan, H., Huang, Y., Bian, J., & Liu, X. (2026). scPyviewer: a Python-native interactive viewer from AnnData single-cell data. bioRxiv, 2026.08.26.747418. https://doi.org/10.64898/2026.08.26.747418
@article{Xuan2026.08.26.747418,
author = {Xuan, Hao and Huang, Yu and Bian, Jiang and Liu, Xiangtao},
title = {scPyviewer: a Python-native interactive viewer from AnnData single-cell data},
year = {2026},
doi = {10.64898/2026.08.26.747418},
publisher = {Cold Spring Harbor Laboratory},
journal = {bioRxiv},
URL = {[https://www.biorxiv.org/content/early/2026/08/31/2026.08.26.747418](https://www.biorxiv.org/content/early/2026/08/31/2026.08.26.747418)}
}