超过 1000 个工具揭示了单细胞 RNA-seq 分析领域的趋势。

Institute of Computational Biology, Helmholtz Zentrum München, 85764, Neuherberg, Germany.

Department of Mathematics, Technical University of Munich, 85748, Garching bei München, Germany.

Genome Biol. 2021 Oct 29;22(1):301. doi: 10.1186/s13059-021-02519-4.

Recent years have seen a revolution in single-cell RNA-sequencing (scRNA-seq) technologies, datasets, and analysis methods. Since 2016, the scRNA-tools database has cataloged software tools for analyzing scRNA-seq data. With the number of tools in the database passing 1000, we provide an update on the state of the project and the field. This data shows the evolution of the field and a change of focus from ordering cells on continuous trajectories to integrating multiple samples and making use of reference datasets. We also find that open science practices reward developers with increased recognition and help accelerate the field.

近年来，单细胞 RNA 测序（scRNA-seq）技术、数据集和分析方法发生了革命性变化。自 2016 年以来，scRNA-tools 数据库已经对分析 scRNA-seq 数据的软件工具进行了编目。随着数据库中工具数量超过 1000，我们提供了该项目和该领域的最新情况。这些数据展示了该领域的发展演变，以及研究重点从在连续轨迹上对细胞进行排序，到整合多个样本并利用参考数据集的转变。我们还发现，开放科学实践通过提高开发者的知名度来回报他们，并帮助加速该领域的发展。