![]() In recent years, single‐cell RNA sequencing (scRNA‐seq) has significantly advanced our knowledge of biological systems. This review will serve as a workflow tutorial for new entrants into the field, and help established users update their analysis pipelines. Our documented case study can be found at. 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. ![]() We formulate current best‐practice recommendations for these steps based on independent comparison studies. 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. 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. The promise of this technology is attracting a growing user base for single‐cell analysis methods. ![]() Single‐cell RNA‐seq has enabled gene expression to be studied at an unprecedented resolution. ![]()
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