标杆管理
计算机科学
计算生物学
计算模型
生物
数据科学
人工智能
业务
营销
作者
Brian Hie,Joshua Peters,Sarah K. Nyquist,Alex K. Shalek,Bonnie Berger,Bryan Bryson
出处
期刊:Annual review of biomedical data science
[Annual Reviews]
日期:2020-07-20
卷期号:3 (1): 339-364
被引量:70
标识
DOI:10.1146/annurev-biodatasci-012220-100601
摘要
Single-cell RNA sequencing (scRNA-seq) has provided a high-dimensional catalog of millions of cells across species and diseases. These data have spurred the development of hundreds of computational tools to derive novel biological insights. Here, we outline the components of scRNA-seq analytical pipelines and the computational methods that underlie these steps. We describe available methods, highlight well-executed benchmarking studies, and identify opportunities for additional benchmarking studies and computational methods. As the biochemical approaches for single-cell omics advance, we propose coupled development of robust analytical pipelines suited for the challenges that new data present and principled selection of analytical methods that are suited for the biological questions to be addressed.
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