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Scope+: An open source generalizable architecture for single-cell atlases at sample and cell levels

Danqing YiniD, Yue CaoiD, Junyi CheniD, Candice L.Y. Mak, Ken H.O. Yu, Yingxin LiniD, Jiaxuan ZhangiD, Jia LiiD, Joshua W. K. HoiD, Jean Yee Hwa YangiD

PDFDOI

Abstract

With the recent advancement in single-cell 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 optimised 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, Covidscope (https://covidsc.d24h.hk/). We achieved efficient access to atlas-scale data via three strategies, such as server-side rendering, novel database optimization strategies and an innovative architectural design. Scope+ serves as an open source architecture for researchers to build on with their own atlas, and demonstrated its capability in the Covidscope portal for an effective meta-analysis to atlas data at cellular resolution for reproducible research.

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