定义单细胞分析中的开放性问题并设定基准。
Defining and benchmarking open problems in single-cell analysis.
作者信息
Luecken Malte D, Gigante Scott, Burkhardt Daniel B, Cannoodt Robrecht, Strobl Daniel C, Markov Nikolay S, Zappia Luke, Palla Giovanni, Lewis Wesley, Dimitrov Daniel, Vinyard Michael E, Magruder D S, Andersson Alma, Dann Emma, Qin Qian, Otto Dominik J, Klein Michal, Botvinnik Olga Borisovna, Deconinck Louise, Waldrant Kai, Bloom Jonathan M, Pisco Angela Oliveira, Saez-Rodriguez Julio, Wulsin Drausin, Pinello Luca, Saeys Yvan, Theis Fabian J, Krishnaswamy Smita
机构信息
Institute of computational Biology, Helmholtz Munich, Neuherberg, Germany.
Institute of Lung Health & Immunity, Helmholtz Munich; Member of the German Center for Lung Research (DZL), Munich, Germany.
出版信息
Res Sq. 2024 Apr 4:rs.3.rs-4181617. doi: 10.21203/rs.3.rs-4181617/v1.
With the growing number of single-cell analysis tools, benchmarks are increasingly important to guide analysis and method development. However, a lack of standardisation and extensibility in current benchmarks limits their usability, longevity, and relevance to the community. We present Open Problems, a living, extensible, community-guided benchmarking platform including 10 current single-cell tasks that we envision will raise standards for the selection, evaluation, and development of methods in single-cell analysis.
随着单细胞分析工具数量的不断增加，基准测试对于指导分析和方法开发变得越来越重要。然而，当前基准测试缺乏标准化和可扩展性，限制了它们的可用性、持久性以及与社区的相关性。我们提出了“开放问题”（Open Problems），这是一个活跃的、可扩展的、由社区指导的基准测试平台，其中包括10个当前的单细胞任务，我们设想这些任务将提高单细胞分析方法的选择、评估和开发标准。
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