bioRxivBioinformaticsPreprint
A universal tool for chromatin loop annotation in bulk and single-cell Hi-C data
Yusen HouiD, Audrey BaguetteiD, Mathieu BlanchetteiD, Yanlin ZhangiD
Abstract
Annotating chromatin loops is essential for understanding the 3D genomes role in gene regulation, but current methods struggle with low coverage, particularly in single-cell datasets. Chromatin loops are kilo-to mega-range structures that exhibit broader features, such as co-occurring loops, stripes, and domain boundaries along axial directions of Hi-C contact maps. However, existing tools primarily focus on detecting localized, highly-concentrated, interactions. Furthermore, the wide variety of available chromatin conformation datasets is rarely utilized in developing effective loop callers. Here, we present Polaris, a universal tool that integrates axial attention with a U-shaped backbone to accurately detect loops across different 3D genome assays. By leveraging extensive Hi-C contact maps in a pretrain-finetune paradigm, Polaris achieves consistent performance across various datasets. We compare Polaris against existing tools in loop annotation from both bulk and single-cell data and find that Polaris outperforms other programs across different cell types, species, sequencing depths, and assays.
- assay: Hi-C
- research focus: gene regulatory network inference
- research focus: benchmarking
- research focus: software / tool
- approach: deep learning
- approach: transformer / foundation model
- Citations
- 0
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