Current best practices in single-cell RNA-seq analysis: a tutorial
Luecken MD, Theis FJ (2019)
Publication Type: Journal article, Review article
Publication year: 2019
Journal
Book Volume: 15
Article Number: e8746
Journal Issue: 6
Abstract
Single-cell RNA-seq has enabled gene expression to be studied at an unprecedented resolution. The promise of this technology is attracting a growing user base for single-cell analysis methods. As more analysis tools are becoming available, it is becoming increasingly difficult to navigate this landscape and produce an up-to-date workflow to analyse one's data. Here, we detail the steps of a typical single-cell RNA-seq analysis, including pre-processing (quality control, normalization, data correction, feature selection, and dimensionality reduction) and cell- and gene-level downstream analysis. We formulate current best-practice recommendations for these steps based on independent comparison studies. We have integrated these best-practice recommendations into a workflow, which we apply to a public dataset to further illustrate how these steps work in practice. Our documented case study can be found at https://www.github.com/theislab/single-cell-tutorial. This review will serve as a workflow tutorial for new entrants into the field, and help established users update their analysis pipelines.
Involved external institutions
Germany (DE)How to cite
APA:
Luecken, M.D., & Theis, F.J. (2019). Current best practices in single-cell RNA-seq analysis: a tutorial. Molecular Systems Biology, 15(6). https://doi.org/10.15252/msb.20188746
MLA:
Luecken, Malte D., and Fabian J. Theis. "Current best practices in single-cell RNA-seq analysis: a tutorial." Molecular Systems Biology 15.6 (2019).
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