Automatic cell-type harmonization and integration across Human Cell Atlas datasets.
Cell
; 186(26): 5876-5891.e20, 2023 12 21.
Article
in En
| MEDLINE
| ID: mdl-38134877
ABSTRACT
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 â¼3.7 million cells and various machine learning models for automatic cell annotation across human tissues.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Gene Expression Profiling
/
Transcriptome
Limits:
Humans
Language:
En
Journal:
Cell
Year:
2023
Type:
Article
Affiliation country:
United kingdom