{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T02:22:37Z","timestamp":1784254957646,"version":"3.55.0"},"reference-count":47,"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-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62225209"],"award-info":[{"award-number":["62225209"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hunan Provincial Science and Technology Program","award":["2019CB1007"],"award-info":[{"award-number":["2019CB1007"]}]},{"name":"Hunan Provincial Science and Technology Program","award":["2021RC4008"],"award-info":[{"award-number":["2021RC4008"]}]},{"DOI":"10.13039\/501100012476","name":"Fundamental Research Funds for the Central Universities of Central South University","doi-asserted-by":"publisher","award":["CX20220276"],"award-info":[{"award-number":["CX20220276"]}],"id":[{"id":"10.13039\/501100012476","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>Clustering cells based on single-cell multi-modal sequencing technologies provides an unprecedented opportunity to create high-resolution cell atlas, reveal cellular critical states and study health and diseases. However, effectively integrating different sequencing data for cell clustering remains a challenging task. Motivated by the successful application of Louvain in scRNA-seq data, we propose a single-cell multi-modal Louvain clustering framework, called scMLC, to tackle this problem. scMLC builds multiplex single- and cross-modal cell-to-cell networks to capture modal-specific and consistent information between modalities and then adopts a robust multiplex community detection method to obtain the reliable cell clusters. In comparison with 15 state-of-the-art clustering methods on seven real datasets simultaneously measuring gene expression and chromatin accessibility, scMLC achieves better accuracy and stability in most datasets. Synthetic results also indicate that the cell-network-based integration strategy of multi-omics data is superior to other strategies in terms of generalization. Moreover, scMLC is flexible and can be extended to single-cell sequencing data with more than two modalities.<\/jats:p>","DOI":"10.1093\/bib\/bbae101","type":"journal-article","created":{"date-parts":[[2024,3,17]],"date-time":"2024-03-17T10:05:42Z","timestamp":1710669942000},"source":"Crossref","is-referenced-by-count":8,"title":["scMLC: an accurate and robust multiplex community detection method for single-cell multi-omics data"],"prefix":"10.1093","volume":"25","author":[{"given":"Yuxuan","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6372-6798","authenticated-orcid":false,"given":"Ruiqing","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0188-1394","authenticated-orcid":false,"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,3,16]]},"reference":[{"issue":"13","key":"2024031710053184500_ref1","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","article-title":"Integrated analysis of multimodal single-cell data[J]","volume":"184","author":"Hao","year":"2021","journal-title":"Cell"},{"issue":"5","key":"2024031710053184500_ref2","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1038\/nmeth.4236","article-title":"SC3: consensus clustering of single-cell RNA-seq data[J]","volume":"14","author":"Kiselev","year":"2017","journal-title":"Nat Methods"},{"issue":"19","key":"2024031710053184500_ref3","doi-asserted-by":"crossref","first-page":"3642","DOI":"10.1093\/bioinformatics\/btz139","article-title":"SinNLRR: a robust subspace clustering method for cell type detection by non-negative and low-rank representation[J]","volume":"35","author":"Zheng","year":"2019","journal-title":"Bioinformatics"},{"issue":"1","key":"2024031710053184500_ref4","doi-asserted-by":"crossref","first-page":"btae020","DOI":"10.1093\/bioinformatics\/btae020","article-title":"scMAE: a masked autoencoder for single-cell RNA-seq clustering","volume":"40","author":"Fang","year":"2024","journal-title":"Bioinformatics"},{"issue":"5","key":"2024031710053184500_ref5","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1038\/s41592-019-0367-1","article-title":"cisTopic: cis-regulatory topic modeling on single-cell ATAC-seq data[J]","volume":"16","author":"Bravo Gonz\u00e1lez-Blas","year":"2019","journal-title":"Nat Methods"},{"issue":"1","key":"2024031710053184500_ref6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-019-12630-7","article-title":"SCALE method for single-cell ATAC-seq analysis via latent feature extraction[J]","volume":"10","author":"Xiong","year":"2019","journal-title":"Nat Commun"},{"issue":"1","key":"2024031710053184500_ref7","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1038\/s41467-021-21583-9","article-title":"Comprehensive analysis of single cell ATAC-seq data with SnapATAC[J]","volume":"12","author":"Fang","year":"2021","journal-title":"Nat Commun"},{"issue":"6409","key":"2024031710053184500_ref8","doi-asserted-by":"crossref","first-page":"1380","DOI":"10.1126\/science.aau0730","article-title":"Joint profiling of chromatin accessibility and gene expression in thousands of single cells[J]","volume":"361","author":"Cao","year":"2018","journal-title":"Science"},{"issue":"12","key":"2024031710053184500_ref9","doi-asserted-by":"crossref","first-page":"1452","DOI":"10.1038\/s41587-019-0290-0","article-title":"High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell[J]","volume":"37","author":"Chen","year":"2019","journal-title":"Nat Biotechnol"},{"issue":"11","key":"2024031710053184500_ref10","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1038\/s41594-019-0323-x","article-title":"An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome[J]","volume":"26","author":"Zhu","year":"2019","journal-title":"Nat Struct Mol Biol"},{"issue":"1","key":"2024031710053184500_ref11","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1089\/gen.41.01.17","article-title":"Single-cell multiomics: simultaneous epigenetic and transcriptional profiling: 10x genomics shares experimental planning and sample preparation tips for the chromium single cell Multiome ATAC+ gene expression system[J]","volume":"41","author":"Belhocine","year":"2021","journal-title":"Genetic Engineering & Biotechnology News"},{"issue":"1","key":"2024031710053184500_ref12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-020-02015-1","article-title":"MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data[J]","volume":"21","author":"Argelaguet","year":"2020","journal-title":"Genome Biol"},{"issue":"1","key":"2024031710053184500_ref13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-021-02556-z","article-title":"Cobolt: integrative analysis of multimodal single-cell sequencing data[J]","volume":"22","author":"Gong","year":"2021","journal-title":"Genome Biol"},{"issue":"8","key":"2024031710053184500_ref14","doi-asserted-by":"crossref","DOI":"10.1038\/s41592-023-01909-9","article-title":"MultiVI: deep generative model for the integration of multimodal data","volume":"20","author":"Ashuach","year":"2023","journal-title":"Nat Methods"},{"issue":"1","key":"2024031710053184500_ref15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-021-02595-6","article-title":"A deep generative model for multi-view profiling of single-cell RNA-seq and ATAC-seq data[J]","volume":"23","author":"Li","year":"2022","journal-title":"Genome Biol"},{"issue":"5","key":"2024031710053184500_ref16","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1038\/s41576-018-0088-9","article-title":"Challenges in unsupervised clustering of single-cell RNA-seq data[J]","volume":"20","author":"Kiselev","year":"2019","journal-title":"Nat Rev Genet"},{"issue":"1","key":"2024031710053184500_ref17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-017-1382-0","article-title":"SCANPY: large-scale single-cell gene expression data analysis[J]","volume":"19","author":"Wolf","year":"2018","journal-title":"Genome Biol"},{"issue":"1","key":"2024031710053184500_ref18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-019-1898-6","article-title":"Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis[J]","volume":"20","author":"Sun","year":"2019","journal-title":"Genome Biol"},{"issue":"Supplement_1","key":"2024031710053184500_ref19","doi-asserted-by":"crossref","first-page":"i317","DOI":"10.1093\/bioinformatics\/btab303","article-title":"SAILER: scalable and accurate invariant representation learning for single-cell ATAC-seq processing and integration[J]","volume":"37","author":"Cao","year":"2021","journal-title":"Bioinformatics"},{"issue":"3","key":"2024031710053184500_ref20","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1093\/biostatistics\/kxu001","article-title":"Variable selection for generalized canonical correlation analysis[J]","volume":"15","author":"Tenenhaus","year":"2014","journal-title":"Biostatistics"},{"issue":"5","key":"2024031710053184500_ref21","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1038\/s41592-022-01461-y","article-title":"NEAT-seq: simultaneous profiling of intra-nuclear proteins, chromatin accessibility and gene expression in single cells[J]","volume":"19","author":"Chen","year":"2022","journal-title":"Nat Methods"},{"issue":"10","key":"2024031710053184500_ref22","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1038\/s41587-021-00927-2","article-title":"Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells[J]","volume":"39","author":"Mimitou","year":"2021","journal-title":"Nat Biotechnol"},{"issue":"1","key":"2024031710053184500_ref23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-021-02480-2","article-title":"Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference construction[J]","volume":"22","author":"Ma","year":"2021","journal-title":"Genome Biol"},{"issue":"5","key":"2024031710053184500_ref24","doi-asserted-by":"crossref","first-page":"bbab034","DOI":"10.1093\/bib\/bbab034","article-title":"Accurate feature selection improves single-cell RNA-seq cell clustering[J]","volume":"22","author":"Su","year":"2021","journal-title":"Brief Bioinform"},{"issue":"2","key":"2024031710053184500_ref25","doi-asserted-by":"crossref","first-page":"btad043","DOI":"10.1093\/bioinformatics\/btad043","article-title":"Adversarial dense graph convolutional networks for single-cell classification [J]","volume":"39","author":"Wang","year":"2023","journal-title":"Bioinformatics"},{"issue":"1","key":"2024031710053184500_ref26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-019-1874-1","article-title":"Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression[J]","volume":"20","author":"Hafemeister","year":"2019","journal-title":"Genome Biol"},{"issue":"1","key":"2024031710053184500_ref27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-019-1861-6","article-title":"Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model[J]","volume":"20","author":"Townes","year":"2019","journal-title":"Genome Biol"},{"key":"2024031710053184500_ref28","doi-asserted-by":"crossref","first-page":"658352","DOI":"10.3389\/fgene.2021.658352","article-title":"Enhancement and imputation of peak signal enables accurate cell-type classification in scATAC-seq[J]","volume":"12","author":"Cui","year":"2021","journal-title":"Front Genet"},{"issue":"6","key":"2024031710053184500_ref29","doi-asserted-by":"crossref","first-page":"e1009064","DOI":"10.1371\/journal.pcbi.1009064","article-title":"Couple CoC+: an information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data[J]","volume":"17","author":"Zeng","year":"2021","journal-title":"PLoS Comput Biol"},{"issue":"1","key":"2024031710053184500_ref30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-018-04629-3","article-title":"Unsupervised clustering and epigenetic classification of single cells[J]","volume":"9","author":"Zamanighomi","year":"2018","journal-title":"Nat Commun"},{"issue":"1","key":"2024031710053184500_ref31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-019-1854-5","article-title":"Assessment of computational methods for the analysis of single-cell ATAC-seq data[J]","volume":"20","author":"Chen","year":"2019","journal-title":"Genome Biol"},{"issue":"21","key":"2024031710053184500_ref32","doi-asserted-by":"crossref","first-page":"e1800583","DOI":"10.1002\/mnfr.201800583","article-title":"Metabotypes related to meat and vegetable intake reflect microbial, lipid and amino acid metabolism in healthy people[J]","volume":"62","author":"Wei","year":"2018","journal-title":"Mol Nutr Food Res"},{"issue":"6","key":"2024031710053184500_ref33","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1093\/bib\/bbx060","article-title":"A strategy for multimodal data integration: application to biomarkers identification in spinocerebellar ataxia[J]","volume":"19","author":"Garali","year":"2018","journal-title":"Brief Bioinform"},{"issue":"10","key":"2024031710053184500_ref34","doi-asserted-by":"crossref","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","article-title":"Fast unfolding of communities in large networks[J]","volume":"2008","author":"Blondel","year":"2008","journal-title":"Journal of statistical mechanics: theory and experiment"},{"key":"2024031710053184500_ref35","doi-asserted-by":"crossref","first-page":"e1525","DOI":"10.7717\/peerj.1525","article-title":"Identifying communities from multiplex biological networks[J]","volume":"3","author":"Didier","year":"2015","journal-title":"PeerJ"},{"issue":"19","key":"2024031710053184500_ref36","doi-asserted-by":"crossref","first-page":"5053","DOI":"10.1016\/j.cell.2021.07.039","article-title":"Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution","volume":"184","author":"Trevino","year":"2021","journal-title":"Cell"},{"issue":"12","key":"2024031710053184500_ref37","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1038\/s41592-018-0229-2","article-title":"Deep generative modeling for single-cell transcriptomics[J]","volume":"15","author":"Lopez","year":"2018","journal-title":"Nat Methods"},{"issue":"1","key":"2024031710053184500_ref38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-020-3482-1","article-title":"GiniClust3: a fast and memory-efficient tool for rare cell type identification[J]","volume":"21","author":"Dong","year":"2020","journal-title":"BMC bioinformatics"},{"issue":"3","key":"2024031710053184500_ref39","doi-asserted-by":"crossref","first-page":"100182","DOI":"10.1016\/j.crmeth.2022.100182","article-title":"PeakVI: a deep generative model for single-cell chromatin accessibility analysis[J]","volume":"2","author":"Ashuach","year":"2022","journal-title":"Cell reports methods"},{"issue":"1","key":"2024031710053184500_ref40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-021-25131-3","article-title":"EpiScanpy: integrated single-cell epigenomic analysis[J]","volume":"12","author":"Danese","year":"2021","journal-title":"Nat Commun"},{"issue":"12","key":"2024031710053184500_ref41","doi-asserted-by":"crossref","first-page":"1624","DOI":"10.1109\/TKDE.2005.198","article-title":"Document clustering using locality preserving indexing[J]","volume":"17","author":"Cai","year":"2005","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2024031710053184500_ref42","doi-asserted-by":"crossref","DOI":"10.1088\/1742-5468\/2005\/09\/P09008","article-title":"Comparing community structure identification","volume-title":"J Stat Mech","author":"Danon","year":"2005"},{"issue":"9","key":"2024031710053184500_ref43","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1093\/bioinformatics\/17.9.763","article-title":"Details of the adjusted Rand index and clustering algorithms, supplement to the paper an empirical study on principal component analysis for clustering gene expression data[J]","volume":"17","author":"Yeung","year":"2001","journal-title":"Bioinformatics"},{"issue":"9","key":"2024031710053184500_ref44","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1038\/nmeth.4380","article-title":"Simultaneous epitope and transcriptome measurement in single cells[J]","volume":"14","author":"Stoeckius","year":"2017","journal-title":"Nat Methods"},{"issue":"1","key":"2024031710053184500_ref45","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1080\/15476286.2022.2027151","article-title":"CITEMOXMBD: a flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells[J]","volume":"19","author":"Hu","year":"2022","journal-title":"RNA Biol"},{"issue":"1","key":"2024031710053184500_ref46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-021-02356-5","article-title":"A generalization of t-SNE and UMAP to single-cell multimodal omics[J]","volume":"22","author":"Do","year":"2021","journal-title":"Genome Biol"},{"issue":"10","key":"2024031710053184500_ref47","doi-asserted-by":"crossref","first-page":"936","DOI":"10.1038\/nbt.3973","article-title":"Multiplexed quantification of proteins and transcripts in single cells[J]","volume":"35","author":"Peterson","year":"2017","journal-title":"Nat Biotechnol"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/2\/bbae101\/56995114\/bbae101.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/2\/bbae101\/56995114\/bbae101.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,17]],"date-time":"2024-03-17T10:07:01Z","timestamp":1710670021000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbae101\/7630473"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,22]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,1,22]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbae101","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,3,1]]},"published":{"date-parts":[[2024,1,22]]},"article-number":"bbae101"}}