ArticleGenome biology2022
Bi-order multimodal integration of single-cell data.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- ARCADIA reveals spatially dependent transcriptional programs through integration of scRNA-seq and spatial proteomics.Bioinformatics (Oxford, England) · 2026Article
- Specificity-driven cell-gene graph learning identifies rare cell states in single-cell and spatial transcriptomic data.Advanced biotechnology · 2026Article
- SIVA: diagonal integration of spatial multi-omics data via spatially informed variational autoencoders and anchor guidance.Bioinformatics (Oxford, England) · 2026Article
- Robust integration of single-cell datasets with imbalanced modality composition.Nature communications · 2026Article
- Quantifying Cross-Modal Association Confidence for Single-Cell RNA-ATAC Integration.bioRxiv : the preprint server for biology · 2026Article
- CAPTAIN: a multimodal foundation model pretrained on co-assayed single-cell RNA and protein.Nature communications · 2026Article
- SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration.Nature communications · 2026Article
- Benchmarking component choices for unpaired single cell RNA and epigenomic integration.Genome biology · 2026Article
- A comprehensive benchmarking study on computational tools for cross-omics label transfer from single-cell RNA to ATAC data.G3 (Bethesda, Md.) · 2026Article
- Cell neighborhood topology directs rare cell population identification.Nature communications · 2026Article
- Orthogonal disentanglement of single-cell multi-omics reveals private and shared drivers of tissue development and pathogenesis.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Explainable graph learning for multimodal single-cell data integration.BMC bioinformatics · 2026Article
- Bridging unpaired single-cell multimodal data for integrative analyses with SuperMap.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- BiCLUM: Bilateral contrastive learning for unpaired single-cell multi-omics integration.PLoS computational biology · 2026Article
- MOMHCA-SG: a multi-head cross-attention and similar graph convolutional network framework for Alzheimer's disease cell type classification.Frontiers in neuroscience · 2026Article
- SCOT+: a comprehensive software suite for single-cell alignment using optimal transport.Bioinformatics advances · 2026Article
- Computational Analyses and Challenges of Single-cell ATAC-seq.Genomics, proteomics & bioinformatics · 2025Review
- Article
- ARCADIA Reveals Spatially Dependent Transcriptional Programs through Integration of scRNA-seq and Spatial Proteomics.bioRxiv : the preprint server for biology · 2025Article
- Benchmarking single-cell multi-modal data integrations.Nature methods · 2025Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Integration of single-cell multiomics profiles generated by different single-cell technologies from the same biological sample is still challenging. Previous approaches based on shared features have only provided approximate solutions. Here, we present a novel mathematical solution named bi-order canonical correlation analysis (bi-CCA), which extends the widely used CCA approach to iteratively align the rows and the columns between data matrices. Bi-CCA is generally applicable to combinations of any two single-cell modalities. Validations using co-assayed ground truth data and application to a CAR-NK study and a fetal muscle atlas demonstrate its capability in generating accurate multimodal co-embeddings and discovering cellular identity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.