Details

Autor(en) / Beteiligte

• Xu, Chuan
• Prete, Martin
• Webb, Simone
• Jardine, Laura
• Stewart, Benjamin J
• Hoo, Regina
• He, Peng
• Meyer, Kerstin B
• Teichmann, Sarah A

Titel

Automatic cell-type harmonization and integration across Human Cell Atlas datasets

Ist Teil von

• Cell, 2023-12, Vol.186 (26), p.5876-5891.e20

Ort / Verlag

United States

Erscheinungsjahr

2023

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Harmonizing cell types across the single-cell community and assembling them into a common framework is central to building a standardized Human Cell Atlas. Here, we present CellHint, a predictive clustering tree-based tool to resolve cell-type differences in annotation resolution and technical biases across datasets. CellHint accurately quantifies cell-cell transcriptomic similarities and places cell types into a relationship graph that hierarchically defines shared and unique cell subtypes. Application to multiple immune datasets recapitulates expert-curated annotations. CellHint also reveals underexplored relationships between healthy and diseased lung cell states in eight diseases. Furthermore, we present a workflow for fast cross-dataset integration guided by harmonized cell types and cell hierarchy, which uncovers underappreciated cell types in adult human hippocampus. Finally, we apply CellHint to 12 tissues from 38 datasets, providing a deeply curated cross-tissue database with ∼3.7 million cells and various machine learning models for automatic cell annotation across human tissues.