Work

MINGLE: a mutual information-based interpretable framework for automatic cell type annotation in single-cell chromatin accessibility data

Year: 2025

Type: article

Abstract: Single-cell chromatin accessibility sequencing (scCAS) has proven invaluable for investigating the intricate landscape of epigenomic heterogeneity. We propose MINGLE, a mutual information-based interpretable framework that leverages cellular similarities and topological structures for accurate cell type annotation of scCAS data. Additionally, we introduce a convex hull-based strategy to effectively identify novel cell types. Extensive experiments demonstrate MINGLE's superior annotation performance, particularly for rare and novel cell types, delivering valuable biological insights compared to existing methods. Moreover, MINGLE excels in cross-batch, cross-tissue, and cross-species scenarios, showing robustness to data imbalance and size, highlighting its versatility for complex annotation tasks.

Source: Genome biology

DOI: 10.1186/s13059-025-03603-9

Authors: Siyu Li, Yifan Huang, Shengquan Chen

Institution: Nankai University

Language: English

Topic: Single-cell and spatial transcriptomics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $5,490

Funder: National Natural Science Foundation of China