Alan Yue Yang Teo, Jordan W. Squair, Gregoire Courtine, Michael A. Skinnider
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引用次数: 0
Abstract
Differential accessibility (DA) analysis of single-cell epigenomics data enables the discovery of regulatory programs that establish cell type identity and steer responses to physiological and pathophysiological perturbations. While many statistical methods to identify DA regions have been developed, the principles that determine the performance of these methods remain unclear. As a result, there is no consensus on the most appropriate statistical methods for DA analysis of single-cell epigenomics data. Here, we present a systematic evaluation of statistical methods that have been applied to identify DA regions in single-cell ATAC-seq (scATAC-seq) data. We leverage a compendium of scATAC-seq experiments with matching bulk ATAC-seq or scRNA-seq in order to assess the accuracy, bias, robustness, and scalability of each statistical method. The structure of our experiments also provides the opportunity to define best practices for the analysis of scATAC-seq data beyond DA itself. We leverage this understanding to develop an R package implementing these best practices.
通过对单细胞表观基因组学数据进行差异可及性(DA)分析,可以发现建立细胞类型特征并引导对生理和病理生理扰动做出反应的调控程序。虽然已经开发出了许多识别DA区域的统计方法,但决定这些方法性能的原理仍不明确。因此,对于单细胞表观基因组学数据 DA 分析的最合适统计方法还没有达成共识。在此,我们对已用于识别单细胞 ATAC-seq (scATAC-seq)数据中的 DA 区域的统计方法进行了系统评估。我们利用与大量 ATAC-seq 或 scRNA-seq 相匹配的 scATAC-seq 实验汇编来评估每种统计方法的准确性、偏差、稳健性和可扩展性。我们的实验结构还提供了一个机会,可借以定义 DA 本身之外的 scATAC-seq 数据分析最佳实践。我们利用这一认识开发了一个实现这些最佳实践的 R 软件包。
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.