Best practices for single-cell analysis across modalities

Recent advances in single-cell technologies have enabled high-throughput molecular profiling of cells across modalities and locations. Single-cell transcriptomics data can now be complemented by chromatin accessibility, surface protein expression, adaptive immune receptor repertoire profiling and sp...

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Veröffentlicht in:Nature reviews. Genetics Jg. 24; H. 8; S. 550 - 572
Hauptverfasser: Heumos, Lukas, Schaar, Anna C., Lance, Christopher, Litinetskaya, Anastasia, Drost, Felix, Zappia, Luke, Lücken, Malte D., Strobl, Daniel C., Henao, Juan, Curion, Fabiola, Schiller, Herbert B., Theis, Fabian J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 01.08.2023
Nature Publishing Group
Schlagworte:
631/114/1305
631/114/794
631/1647/514/1949
631/208/191
Agriculture
Animal Genetics and Genomics
Biomedical and Life Sciences
Biomedicine
Cancer Research
Chromatin
Electrons
Expert Recommendation
Gene Expression Profiling - methods
Gene Function
Human Genetics
Proteomics
Single-Cell Analysis - methods
Transcriptomics
ISSN:1471-0056, 1471-0064, 1471-0064
Online-Zugang:Volltext
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Zusammenfassung:Recent advances in single-cell technologies have enabled high-throughput molecular profiling of cells across modalities and locations. Single-cell transcriptomics data can now be complemented by chromatin accessibility, surface protein expression, adaptive immune receptor repertoire profiling and spatial information. The increasing availability of single-cell data across modalities has motivated the development of novel computational methods to help analysts derive biological insights. As the field grows, it becomes increasingly difficult to navigate the vast landscape of tools and analysis steps. Here, we summarize independent benchmarking studies of unimodal and multimodal single-cell analysis across modalities to suggest comprehensive best-practice workflows for the most common analysis steps. Where independent benchmarks are not available, we review and contrast popular methods. Our article serves as an entry point for novices in the field of single-cell (multi-)omic analysis and guides advanced users to the most recent best practices. Practitioners in the field of single-cell omics are now faced with diverse options for analytical tools to process and integrate data from various molecular modalities. In an Expert Recommendation article, the authors provide guidance on robust single-cell data analysis, including choices of best-performing tools from benchmarking studies.
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ISSN:1471-0056
1471-0064
1471-0064
DOI:10.1038/s41576-023-00586-w