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STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization

delete2023-11-11
delete36
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OA
AI
Z
Zhicheng Xu
W
Weiwen Wang
T
Tao Yang
李玲 cover
李玲 (Ling Li)
X
Xizheng Ma
陈晶 (Jing Chen)
J
Jieyu Wang
Y
Yan Huang
J
Joshua Gould
H
Huifang Lü
W
Wensi Du
S
Sunil Kumar Sahu
F
Fan Yang
Z
Zhiyong Li
Q
Qingjiang Hu
C
Cong Hua
S
Shoujie Hu
Y
Yiqun Liu
J
Jia Cai
L
Lijin You
Y
Yong Zhang
Y
Yuxiang Li
W
Wenjun Zeng
A
Ao Chen
汪波 cover
汪波 (Bo Wang)
L
Longqi Liu
F
Fengzhen Chen
K
Kailong Ma
X
Xun Xu *
X
Xiaofeng Wei *
DOI:10.1093/nar/gkad933delete
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Abstract

Abstract

En 中文
Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing dedicated sub-databases in STOmicsDB for researchers, assisting them in visualizing their spatial transcriptomic analyses. We believe that STOmicsDB could contribute to research insights in the spatial transcriptomics field, including data archiving, sharing, visualization and analysis. STOmicsDB is freely accessible at https://db.cngb.org/stomics/. Graphical Abstract
Keywords:
SINGLE-CELL
GENE-EXPRESSION
ATLAS
SCALE
SEQ
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Journal

Nucleic Acids Research cover
Nucleic Acids Research
IF:
13.1
Papers:
3.6W
Citations:
29.0W

Organization

H
Harvard University
Scholars:
26.2W
Papers: 21.9W
Citations: 28.7W
B
beijing genomics institute (bgi)
Scholars:
5.2K
Papers: 2.1K
Citations: 7