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However, current computational tools for single-cell multi-omics data integration are mainly tailored for bi-modality data, so new tools are urgently needed to integrate tri-modality data with complex associations. To this end, we develop scMHNN to integrate single-cell multi-omics data based on hypergraph neural network. After modeling the complex data associations among various modalities, scMHNN performs message passing process on the multi-omics hypergraph, which can capture the high-order data relationships and integrate the multiple heterogeneous features. Followingly, scMHNN learns discriminative cell representation via a dual-contrastive loss in self-supervised manner. Based on the pretrained hypergraph encoder, we further introduce the pre-training and fine-tuning paradigm, which allows more accurate cell-type annotation with only a small number of labeled cells as reference. Benchmarking results on real and simulated single-cell tri-modality datasets indicate that scMHNN outperforms other competing methods on both cell clustering and cell-type annotation tasks. In addition, we also demonstrate scMHNN facilitates various downstream tasks, such as cell marker detection and enrichment analysis.<\/jats:p>","DOI":"10.1093\/bib\/bbad391","type":"journal-article","created":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T01:11:25Z","timestamp":1699405885000},"source":"Crossref","is-referenced-by-count":17,"title":["scMHNN: a novel hypergraph neural network for integrative analysis of single-cell epigenomic, transcriptomic and proteomic data"],"prefix":"10.1093","volume":"24","author":[{"given":"Wei","family":"Li","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence, Nankai University , Tongyan Road, 300350 Tianjin , China"},{"name":"AI Lab, Tencent , Gaoxin 9th South Road, 518000 Shenzhen , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Xiang","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Computational Biology , Shanghai Institute of Nutrition and Health, , Yueyang Road, 200031 Shanghai , China"},{"name":"University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai Institute of Nutrition and Health, , Yueyang Road, 200031 Shanghai , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"AI Lab, Tencent , Gaoxin 9th South Road, 518000 Shenzhen , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Rong","sequence":"additional","affiliation":[{"name":"AI Lab, Tencent , Gaoxin 9th South Road, 518000 Shenzhen , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanbin","family":"Yin","sequence":"additional","affiliation":[{"name":"Department of Food Science and Technology, University of Nebraska - Lincoln , 1400 R Street, 68588 Nebraska , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhua","family":"Yao","sequence":"additional","affiliation":[{"name":"AI Lab, 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