bioRxivBioinformaticsPreprint
A universal tool for chromatin loop annotation in bulk and single-cell Hi-C data
Yusen HouiD, Audrey BaguetteiD, Mathieu BlanchetteiD, Yanlin ZhangiD
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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
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