Recent advances in single-cell biotechnologies have resulted in high-dimensional datasets with increased complexity, making feature selection an essential technique for single-cell data analysis. Here, we revisit feature selection techniques and summarise recent developments. We review their application to a range of single-cell data types generated from traditional cytometry and imaging technologies and the latest array of single-cell omics technologies. We highlight some of the challenges and future directions and finally consider their scalability and make general recommendations on each type of feature selection method. We hope this review stimulates future research and application of feature selection in the single-cell era.

中文翻译：

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单细胞时代重新审视特征选择

单细胞生物技术的最新进展导致高维数据集的复杂性增加，使特征选择成为单细胞数据分析的基本技术。在这里，我们重新审视特征选择技术并总结最近的发展。我们回顾了它们在由传统细胞计数和成像技术以及最新的单细胞组学技术产生的一系列单细胞数据类型中的应用。我们强调了一些挑战和未来的方向，最后考虑了它们的可扩展性，并对每种类型的特征选择方法提出了一般性建议。我们希望这篇综述能激发未来单细胞时代特征选择的研究和应用。