Normalizing single-cell RNA sequencing data: challenges and opportunities.

Single-cell transcriptomics is becoming an important component of the molecular biologist’s toolkit. A critical step when analyzing this type of data is normalization. However, normalization is typically performed using methods developed for bulk RNA sequencing or even microarray data, whose suitability for single-cell transcriptomics has not been assessed. In this perspective, we discuss commonly used normalization approaches and illustrate how these can lead to misleading results. Finally, we present alternative approaches and provide recommendations for single-cell RNA sequencing users.

单细胞转录组学正在成为分子生物学家工具包的一个重要组成部分。分析这类数据时的一个关键步骤是标准化。然而，标准化通常使用为大量RNA测序甚至微阵列数据开发的方法来进行，这些方法对单细胞转录组学的适用性尚未得到评估。从这个角度出发，我们讨论常用的标准化方法，并说明这些方法如何可能导致误导性的结果。最后，我们提出替代方法，并为单细胞RNA测序用户提供建议。