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Ramirez A, Orcutt-Jahns BT, Pascoe S, Abraham A, Remigio B, Thomas N, Meyer AS. Integrative, high-resolution analysis of single cells across experimental conditions with PARAFAC2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.29.605698. [PMID: 39131377 PMCID: PMC11312543 DOI: 10.1101/2024.07.29.605698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Effective tools for exploration and analysis are needed to extract insights from large-scale single-cell measurement data. However, current techniques for handling single-cell studies performed across experimental conditions (e.g., samples, perturbations, or patients) require restrictive assumptions, lack flexibility, or do not adequately deconvolute condition-to-condition variation from cell-to-cell variation. Here, we report that the tensor decomposition method PARAFAC2 (Pf2) enables the dimensionality reduction of single-cell data across conditions. We demonstrate these benefits across two distinct contexts of single-cell RNA-sequencing (scRNA-seq) experiments of peripheral immune cells: pharmacologic drug perturbations and systemic lupus erythematosus (SLE) patient samples. By isolating relevant gene modules across cells and conditions, Pf2 enables straightforward associations of gene variation patterns across specific patients or perturbations while connecting each coordinated change to certain cells without pre-defining cell types. The theoretical grounding of Pf2 suggests a unified framework for many modeling tasks associated with single-cell data. Thus, Pf2 provides an intuitive universal dimensionality reduction approach for multi-sample single-cell studies across diverse biological contexts.
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Affiliation(s)
- Andrew Ramirez
- Department of Bioengineering, University of California, Los Angeles (UCLA), CA, USA
| | | | - Sean Pascoe
- Department of Bioengineering, University of California, Los Angeles (UCLA), CA, USA
- Department of Molecular Biosciences, Northwestern University, Evanston, IL, USA
| | - Armaan Abraham
- Department of Bioengineering, University of California, Los Angeles (UCLA), CA, USA
| | | | | | - Aaron S. Meyer
- Department of Bioengineering, University of California, Los Angeles (UCLA), CA, USA
- Jonsson Comprehensive Cancer Center, UCLA, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, UCLA, CA, USA
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Höglund P, Ljunggren H, Jonsson R. Nobel 2022: An extraordinary achievement relevant to immunity. Scand J Immunol 2022. [DOI: 10.1111/sji.13234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Petter Höglund
- Center for Hematology and Regenerative Medicine (HERM), Department of Medicine Huddinge Karolinska Institutet Stockholm Sweden
| | - Hans‐Gustaf Ljunggren
- Center for Infectious Medicine (CIM), Department of Medicine Huddinge Karolinska Institutet Stockholm Sweden
| | - Roland Jonsson
- Broegelmann Research Laboratory, Department of Clinical Science, Faculty of Medicine University of Bergen Bergen Norway
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Xu Z, Ismanto HS, Zhou H, Saputri DS, Sugihara F, Standley DM. Advances in antibody discovery from human BCR repertoires. FRONTIERS IN BIOINFORMATICS 2022; 2:1044975. [PMID: 36338807 PMCID: PMC9631452 DOI: 10.3389/fbinf.2022.1044975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022] Open
Abstract
Antibodies make up an important and growing class of compounds used for the diagnosis or treatment of disease. While traditional antibody discovery utilized immunization of animals to generate lead compounds, technological innovations have made it possible to search for antibodies targeting a given antigen within the repertoires of B cells in humans. Here we group these innovations into four broad categories: cell sorting allows the collection of cells enriched in specificity to one or more antigens; BCR sequencing can be performed on bulk mRNA, genomic DNA or on paired (heavy-light) mRNA; BCR repertoire analysis generally involves clustering BCRs into specificity groups or more in-depth modeling of antibody-antigen interactions, such as antibody-specific epitope predictions; validation of antibody-antigen interactions requires expression of antibodies, followed by antigen binding assays or epitope mapping. Together with innovations in Deep learning these technologies will contribute to the future discovery of diagnostic and therapeutic antibodies directly from humans.
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Affiliation(s)
- Zichang Xu
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Hendra S. Ismanto
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Hao Zhou
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Dianita S. Saputri
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Fuminori Sugihara
- Core Instrumentation Facility, Immunology Frontier Research Center, Osaka University, Suita, Japan
| | - Daron M. Standley
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
- Department Systems Immunology, Immunology Frontier Research Center, Osaka University, Suita, Japan
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