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ASAP 2020 更新:一个用于(单细胞)组学分析的开放、可扩展和交互式的基于网络的门户。

ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses.

机构信息

Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.

Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland.

出版信息

Nucleic Acids Res. 2020 Jul 2;48(W1):W403-W414. doi: 10.1093/nar/gkaa412.

Abstract

Single-cell omics enables researchers to dissect biological systems at a resolution that was unthinkable just 10 years ago. However, this analytical revolution also triggered new demands in 'big data' management, forcing researchers to stay up to speed with increasingly complex analytical processes and rapidly evolving methods. To render these processes and approaches more accessible, we developed the web-based, collaborative portal ASAP (Automated Single-cell Analysis Portal). Our primary goal is thereby to democratize single-cell omics data analyses (scRNA-seq and more recently scATAC-seq). By taking advantage of a Docker system to enhance reproducibility, and novel bioinformatics approaches that were recently developed for improving scalability, ASAP meets challenging requirements set by recent cell atlasing efforts such as the Human (HCA) and Fly (FCA) Cell Atlas Projects. Specifically, ASAP can now handle datasets containing millions of cells, integrating intuitive tools that allow researchers to collaborate on the same project synchronously. ASAP tools are versioned, and researchers can create unique access IDs for storing complete analyses that can be reproduced or completed by others. Finally, ASAP does not require any installation and provides a full and modular single-cell RNA-seq analysis pipeline. ASAP is freely available at https://asap.epfl.ch.

摘要

单细胞组学使研究人员能够以前所未有的分辨率剖析生物系统。然而,这场分析革命也在“大数据”管理方面提出了新的要求,迫使研究人员跟上日益复杂的分析流程和快速发展的方法。为了使这些流程和方法更易于使用,我们开发了基于网络的协作门户 ASAP(自动单细胞分析门户)。我们的主要目标是使单细胞组学数据分析(scRNA-seq,最近又有 scATAC-seq)民主化。通过利用 Docker 系统来提高可重复性,以及最近为提高可扩展性而开发的新型生物信息学方法,ASAP 满足了最近的细胞图谱项目(如人类(HCA)和果蝇(FCA)细胞图谱项目)提出的具有挑战性的要求。具体来说,ASAP 现在可以处理包含数百万个细胞的数据集,集成了直观的工具,允许研究人员在同一个项目上进行同步协作。ASAP 工具是经过版本控制的,研究人员可以为存储完整分析创建唯一的访问 ID,其他人可以对其进行复制或完成。最后,ASAP 不需要任何安装,并且提供了一个完整的、模块化的单细胞 RNA-seq 分析管道。ASAP 可在 https://asap.epfl.ch 上免费获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d03/7319583/e5f699dd3af1/gkaa412fig1.jpg

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