We present pipeComp ( https://github.com/plger/pipeComp ), a flexible R framework for pipeline comparison handling interactions between analysis steps and relying on multi-level evaluation metrics. We apply it to the benchmark of single-cell RNA-sequencing analysis pipelines using simulated and real datasets with known cell identities, covering common methods of filtering, doublet detection, normalization, feature selection, denoising, dimensionality reduction, and clustering. pipeComp can easily integrate any other step, tool, or evaluation metric, allowing extensible benchmarks and easy applications to other fields, as we demonstrate through a study of the impact of removal of unwanted variation on differential expression analysis.

中文翻译：

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pipeComp 是一个用于评估计算管道的通用框架，它揭示了高性能的单细胞 RNA-seq 预处理工具

我们提出了 pipeComp ( https://github.com/plger/pipeComp )，这是一个灵活的 R 框架，用于管道比较处理分析步骤之间的交互并依赖于多级评估指标。我们使用具有已知细胞身份的模拟和真实数据集将其应用于单细胞 RNA 测序分析管道的基准测试，涵盖过滤、双峰检测、归一化、特征选择、去噪、降维和聚类的常用方法。pipeComp 可以轻松集成任何其他步骤、工具或评估指标，允许可扩展的基准测试并轻松应用于其他领域，正如我们通过研究去除不需要的变化对差异表达分析的影响所证明的那样。