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使用DISCO平台重新发现公开可用的单细胞数据。

Rediscovering publicly available single-cell data with the DISCO platform.

作者信息

Li Mengwei, Ang Kok Siong, Teo Brian, Rom Uddamvathanak, Nguyen Minh N, Maurer-Stroh Sebastian, Chen Jinmiao

机构信息

Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore.

Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore.

出版信息

Nucleic Acids Res. 2025 Jan 6;53(D1):D932-D938. doi: 10.1093/nar/gkae1108.

Abstract

Single-cell RNA sequencing (scRNA-seq) has emerged as the key technique for studying transcriptomics at the single-cell level. In our previous work, we presented the DISCO database (https://www.immunesinglecell.org/) that integrates publicly available human scRNA-seq data. We now introduce an enhanced version of DISCO, which has expanded fourfold to include >100 million cells from >17 thousand samples. It provides uniformly realigned read count tables, curated metadata, integrated tissue and phenotype specific atlases, and harmonized cell type annotations. It also hosts a single-cell enhanced knowledgebase of cell type ontology and gene signatures relating to cell types and phenotypes. Lastly, it offers a suite of tools for data retrieval, integration, annotation, and mapping, allowing users to construct customized atlases and perform integrated analysis with their own data. These tools are also available in a standalone R package for offline analysis.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c5f/11701519/ddebba8dd05c/gkae1108figgra1.jpg

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