ArticleNature communications2023
Atlas-scale single-cell multi-sample multi-condition data integration using scMerge2.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- High-Dimensional Multimodal Data Integration for Immune-Driven Diseases: A Practical Guide.Methods in molecular biology (Clifton, N.J.) · 2027Article
- COBRA: cell-type-specific orthogonal batch effect removal algorithm in single cell RNA-sequencing data.Bioinformatics (Oxford, England) · 2026Article
- Benchmarking deep learning methods for biologically conserved single-cell integration.Genome biology · 2025Article
- Article
- scCOSMIX: A Mixed-Effects Framework for Differential Coexpression and Transcriptional Interactions Modeling in Single-Cell RNA-Seq.Statistics in medicine · 2025Article
- Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics data.Briefings in bioinformatics · 2025Article
- Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics.Nature communications · 2025Article
- Capture of Totipotency in Mouse Embryonic Stem Cells in the Absence of Pdzk1.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- A Current Perspective of Medical Informatics Developments for a Clinical Translation of (Non-coding)RNAs and Single-Cell Technologies.Methods in molecular biology (Clifton, N.J.) · 2025Article
- scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq.Genome biology · 2024Article
- C-ziptf: stable tensor factorization for zero-inflated multi-dimensional genomics data.BMC bioinformatics · 2024Article
- Spatiotemporal metabolomic approaches to the cancer-immunity panorama: a methodological perspective.Molecular cancer · 2024Review
- Single-cell RNA sequencing reveals melanoma cell state-dependent heterogeneity of response to MAPK inhibitors.EBioMedicine · 2024Article
- Deep-learning methods for unveiling large-scale single-cell transcriptomes.Cancer biology & medicine · 2024Article
- Targeting tumor-stromal interactions in triple-negative breast cancer using a human vascularized micro-tumor model.Breast cancer research : BCR · 2024Article
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5 authors.
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Abstract
The recent emergence of multi-sample multi-condition single-cell multi-cohort studies allows researchers to investigate different cell states. The effective integration of multiple large-cohort studies promises biological insights into cells under different conditions that individual studies cannot provide. Here, we present scMerge2, a scalable algorithm that allows data integration of atlas-scale multi-sample multi-condition single-cell studies. We have generalized scMerge2 to enable the merging of millions of cells from single-cell studies generated by various single-cell technologies. Using a large COVID-19 data collection with over five million cells from 1000+ individuals, we demonstrate that scMerge2 enables multi-sample multi-condition scRNA-seq data integration from multiple cohorts and reveals signatures derived from cell-type expression that are more accurate in discriminating disease progression. Further, we demonstrate that scMerge2 can remove dataset variability in CyTOF, imaging mass cytometry and CITE-seq experiments, demonstrating its applicability to a broad spectrum of single-cell profiling technologies.
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