Lamere Alicia T, Li Jun
Mathematics Department, Bryant University, Smithfield, RI, USA.
Applied and Computational Mathematics and Statistics Department, University of Notre Dame, Notre Dame, IN, USA.
Methods Mol Biol. 2019;1935:141-153. doi: 10.1007/978-1-4939-9057-3_10.
Single-cell RNA-Sequencing is a pioneering extension of bulk-based RNA-Sequencing technology. The "guilt-by-association" heuristic has led to the use of gene co-expression networks to identify genes that are believed to be associated with a common cellular function. Many methods that were developed for bulk-based RNA-Sequencing data can continue to be applied to single-cell data, and several of the most widely used methods are explored. Several methods for leveraging the novel time information contained in single-cell data when constructing gene co-expression networks, which allows for the incorporation of directed associations, are also discussed.
单细胞RNA测序是基于整体样本的RNA测序技术的一项开创性扩展。“关联有罪”启发法已导致使用基因共表达网络来识别被认为与共同细胞功能相关的基因。许多为基于整体样本的RNA测序数据开发的方法可以继续应用于单细胞数据,本文还探讨了几种最广泛使用的方法。本文还讨论了在构建基因共表达网络时利用单细胞数据中包含的新时间信息的几种方法,这允许纳入定向关联。