{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T08:59:03Z","timestamp":1775984343416,"version":"3.50.1"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,3,17]],"date-time":"2024-03-17T00:00:00Z","timestamp":1710633600000},"content-version":"vor","delay-in-days":55,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFF1200900"],"award-info":[{"award-number":["2021YFF1200900"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62250005"],"award-info":[{"award-number":["62250005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61721003"],"award-info":[{"award-number":["61721003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62373210"],"award-info":[{"award-number":["62373210"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Recent advancements in single-cell sequencing technologies have generated extensive omics data in various modalities and revolutionized cell research, especially in the single-cell RNA and ATAC data. The joint analysis across scRNA-seq data and scATAC-seq data has paved the way to comprehending the cellular heterogeneity and complex cellular regulatory networks. Multi-omics integration is gaining attention as an important step in joint analysis, and the number of computational tools in this field is growing rapidly. In this paper, we benchmarked 12 multi-omics integration methods on three integration tasks via qualitative visualization and quantitative metrics, considering six main aspects that matter in multi-omics data analysis. Overall, we found that different methods have their own advantages on different aspects, while some methods outperformed other methods in most aspects. We therefore provided guidelines for selecting appropriate methods for specific scenarios and tasks to help obtain meaningful insights from multi-omics data integration.<\/jats:p>","DOI":"10.1093\/bib\/bbae095","type":"journal-article","created":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T13:37:44Z","timestamp":1708609064000},"source":"Crossref","is-referenced-by-count":30,"title":["Benchmarking multi-omics integration algorithms across single-cell RNA and ATAC data"],"prefix":"10.1093","volume":"25","author":[{"given":"Chuxi","family":"Xiao","sequence":"first","affiliation":[{"name":"MOE Key Laboratory of Bioinformatics and Bioinformatics Division , BNRIST, Department of Automation, , Beijing 100084 , China"},{"name":"Tsinghua University , BNRIST, Department of Automation, , Beijing 100084 , China"}]},{"given":"Yixin","family":"Chen","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Bioinformatics and Bioinformatics Division , BNRIST, Department of Automation, , Beijing 100084 , China"},{"name":"Tsinghua University , BNRIST, Department of Automation, , Beijing 100084 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6013-9475","authenticated-orcid":false,"given":"Qiuchen","family":"Meng","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Bioinformatics and Bioinformatics Division , BNRIST, Department of Automation, , Beijing 100084 , China"},{"name":"Tsinghua University , BNRIST, Department of Automation, , Beijing 100084 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1546-6458","authenticated-orcid":false,"given":"Lei","family":"Wei","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Bioinformatics and Bioinformatics Division , BNRIST, Department of Automation, , Beijing 100084 , China"},{"name":"Tsinghua University , BNRIST, Department of Automation, , Beijing 100084 , China"}]},{"given":"Xuegong","family":"Zhang","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Bioinformatics and Bioinformatics Division , BNRIST, Department of Automation, , Beijing 100084 , China"},{"name":"Tsinghua University , BNRIST, Department of Automation, , Beijing 100084 , China"},{"name":"School of Life Sciences and School of Medicine , Center for Synthetic and Systems Biology, , Beijing 100084 , China"},{"name":"Tsinghua University , Center for Synthetic and Systems Biology, , Beijing 100084 , China"}]}],"member":"286","published-online":{"date-parts":[[2024,3,16]]},"reference":[{"key":"2024031710080956000_ref1","doi-asserted-by":"crossref","first-page":"550","DOI":"10.1038\/s41576-023-00586-w","article-title":"Best practices for single-cell analysis across modalities","volume":"24","author":"Heumos","year":"2023","journal-title":"Nat Rev Genet"},{"key":"2024031710080956000_ref2","doi-asserted-by":"crossref","first-page":"1419","DOI":"10.1038\/s12276-020-00499-2","article-title":"Single-cell sequencing techniques from individual to multiomics 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