Determining the sample size for adequate power to detect statistical significance is a crucial step at the design stage for high-throughput experiments. Even though a number of methods and tools are available for sample size calculation for microarray and RNA-seq in the context of differential expression (DE), this topic in the field of single-cell RNA sequencing is understudied. Moreover, the unique data characteristics present in scRNA-seq such as sparsity and heterogeneity increase the challenge.

中文翻译：

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单细胞RNA序列的仿真，功效评估和样本量推荐。

在高通量实验的设计阶段，确定样本大小以具有足够的能力检测统计显着性是至关重要的一步。即使在差异表达（DE）的情况下，有许多方法和工具可用于微阵列和RNA-seq的样本量计算，单细胞RNA测序领域的这一主题仍未得到充分研究。此外，scRNA-seq中存在的独特数据特征（例如稀疏性和异质性）也增加了挑战。