bioRxivBioinformaticsPreprint
cellNexus: Quality control, annotation, aggregation and analytical layers for the Human Cell Atlas data
Mengyuan SheniD, Yingnan GaoiD, Ning LiuiD, Dharmesh Dinesh BhuvaiD, Michael MiltoniD, Juan HenaoiD, Jared M. AndrewsiD, Edward YangiD, Chen Zhan, Nora Liu, Susan Si, William J. HutchisoniD, Muhammad Haroon ShakeeliD, Martin T. MorganiD, Anthony T. PapenfussiD, Julie IskanderiD, Jose Maria PoloiD, Stefano MangiolaiD
Abstract
Large-scale single-cell atlases such as the Human Cell Atlas have transformed our understanding of human biology. Yet, the lack of a robust framework that standardises quality control, expands cellular annotation, and adds normalisation and analytical layers, limits multi-study analyses and the usefulness of this resource. Here we present cellNexus, a comprehensive resource that enhances the Human Cell Atlas collection into analysis-ready data by linking quality control layers, metadata enrichment, expression normalisation, analysis and data aggregation. These enhancements enable robust large-scale statistical modelling across studies, exemplified here by a multi-tissue map of immune cell communication during ageing. All harmonised layers are accessible via a public web interface and with R and Python APIs. By providing continuous integration with CELLxGENE releases, cellNexus transforms large cell atlas corpora into an accessible, reproducible, interoperable foundation for large-scale biological discovery and the next generation of single-cell foundation models.
- organism: human
- assay: scRNA-seq
- research focus: batch correction / integration
- research focus: dimensionality reduction
- research focus: database / resource
- approach: statistical model
- Citations
- 1
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