Bioinformatics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.
School of Biosciences, Faculty of Science, University of Melbourne, Melbourne, Victoria, Australia.
PLoS Comput Biol. 2018 Jun 25;14(6):e1006245. doi: 10.1371/journal.pcbi.1006245. eCollection 2018 Jun.
As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the number of tools designed to analyse these data has dramatically increased. Navigating the vast sea of tools now available is becoming increasingly challenging for researchers. In order to better facilitate selection of appropriate analysis tools we have created the scRNA-tools database (www.scRNA-tools.org) to catalogue and curate analysis tools as they become available. Our database collects a range of information on each scRNA-seq analysis tool and categorises them according to the analysis tasks they perform. Exploration of this database gives insights into the areas of rapid development of analysis methods for scRNA-seq data. We see that many tools perform tasks specific to scRNA-seq analysis, particularly clustering and ordering of cells. We also find that the scRNA-seq community embraces an open-source and open-science approach, with most tools available under open-source licenses and preprints being extensively used as a means to describe methods. The scRNA-tools database provides a valuable resource for researchers embarking on scRNA-seq analysis and records the growth of the field over time.
随着单细胞 RNA 测序 (scRNA-seq) 数据集的广泛应用,用于分析这些数据的工具数量也大幅增加。对于研究人员来说,现在要在众多可用工具中进行选择变得越来越具有挑战性。为了更好地促进合适的分析工具的选择,我们创建了 scRNA-tools 数据库(www.scRNA-tools.org),以对分析工具进行编目和管理,以便在它们可用时进行收录。我们的数据库收集了每个 scRNA-seq 分析工具的一系列信息,并根据它们执行的分析任务对其进行分类。对该数据库的探索使我们深入了解 scRNA-seq 数据分析方法的快速发展领域。我们发现许多工具专门执行 scRNA-seq 分析任务,特别是细胞聚类和排序。我们还发现,scRNA-seq 社区采用了开源和开放科学的方法,大多数工具都可以通过开源许可证获得,预印本也被广泛用作描述方法的手段。scRNA-tools 数据库为开始进行 scRNA-seq 分析的研究人员提供了有价值的资源,并记录了该领域随时间的发展。