Scope+：一种用于样本和细胞水平单细胞RNA测序图谱的开源通用架构。

Scope+: an open source generalizable architecture for single-cell RNA-seq atlases at sample and cell levels.

作者信息

Yin Danqing, Cao Yue, Chen Junyi, Mak Candice L Y, Yu Ken H O, Zhang Jiaxuan, Li Jia, Lin Yingxin, Ho Joshua W K, Yang Jean Y H

机构信息

Laboratory of Data Discovery for Health Limited (D24H), Pak Shek Kok, Hong Kong SAR, 999077, China.

School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, 999077, China.

出版信息

Bioinformatics. 2024 Dec 26;41(1). doi: 10.1093/bioinformatics/btae727.

DOI:10.1093/bioinformatics/btae727

PMID:39705183

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11755096/

Abstract

SUMMARY

With the recent advancement in single-cell RNA-sequencing technologies and the increased availability of integrative tools, challenges arise in easy and fast access to large collections of cell atlas. Existing cell atlas portals rarely are open sourced and adaptable, and do not support meta-analysis at cell level. Here, we present an open source, highly optimized and scalable architecture, named Scope+, to allow quick access, meta-analysis and cell-level selection of the atlas data. We applied this architecture to our well-curated 5 million COVID-19 blood and immune cells, as a portal called Covidscope. We achieved efficient access to atlas-scale data via three strategies, such as cell-as-unit data modelling, novel database optimization techniques and innovative software architectural design. Scope+ serves as an open source architecture for researchers to build on with their own atlas.

AVAILABILITY AND IMPLEMENTATION

The COVID-19 web portal, data and meta-analysis are available on Covidscope (https://covidsc.d24h.hk/). User tutorials on how to implement Scope+ architecture with their atlases can be found at https://hiyin.github.io/scopeplus-user-tutorial/. Scope+ source code can be found at https://doi.org/10.5281/zenodo.14174632 and https://github.com/hiyin/scopeplus.

摘要

随着单细胞RNA测序技术的最新进展以及整合工具可用性的提高，在轻松快速访问大量细胞图谱集合方面出现了挑战。现有的细胞图谱门户很少是开源且可适应的，并且不支持细胞水平的荟萃分析。在这里，我们提出了一种名为Scope+的开源、高度优化且可扩展的架构，以允许对图谱数据进行快速访问、荟萃分析和细胞水平选择。我们将此架构应用于我们精心整理的500万个新冠病毒血液和免疫细胞，作为一个名为Covidscope的门户。我们通过三种策略实现了对图谱规模数据的高效访问，例如以细胞为单位的数据建模、新颖的数据库优化技术和创新的软件架构设计。Scope+作为一种开源架构，供研究人员基于自己的图谱进行构建。