Best practices for single-cell analysis across modalities

single-cell
multiomics
best practices
review
Authors

Lukas Heumos

Anna C. Schaar

Christopher Lance

Anastasia Litinetskaya

Felix Drost

Luke Zappia

Malte D. Lücken

Daniel C. Strobl

Juan Henao

Fabiola Curion

Single-cell Best Practices Consortium

Herbert B. Schiller

Fabian J. Theis

Date

March 31, 2023

Links
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Abstract

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.

Citation

BibTeX citation:
@article{heumos2023,
  author = {Heumos, Lukas and C. Schaar, Anna and Lance, Christopher and
    Litinetskaya, Anastasia and Drost, Felix and Zappia, Luke and D.
    Lücken, Malte and C. Strobl, Daniel and Henao, Juan and Curion,
    Fabiola and Best Practices Consortium, Single-cell and B. Schiller,
    Herbert and J. Theis, Fabian},
  title = {Best Practices for Single-Cell Analysis Across Modalities},
  journal = {Nature reviews genetics},
  pages = {1-23},
  date = {2023-03-31},
  url = {https://lazappi.id.au/publications/2023-heumos-best-practices/},
  doi = {10.1038/s41576-023-00586-w},
  issn = {1471-0056},
  langid = {en},
  abstract = {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.}
}
For attribution, please cite this work as:
Heumos, Lukas, Anna C. Schaar, Christopher Lance, Anastasia Litinetskaya, Felix Drost, Luke Zappia, Malte D. Lücken, et al. 2023. “Best Practices for Single-Cell Analysis Across Modalities.” Nature Reviews Genetics, March, 1–23. https://doi.org/10.1038/s41576-023-00586-w.