Pairpot: a database with real-time lasso-based analysis tailored for paired single-cell and spatial transcriptomics.

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Nucleic Acids Research Pub Date : 2024-11-04 DOI:10.1093/nar/gkae986
Zhihan Ruan, Fan Lin, Zhenjie Zhang, Jiayue Cao, Wenting Xiang, Xiaoyi Wei, Jian Liu
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Abstract

Paired single-cell and spatially resolved transcriptomics (SRT) data supplement each other, providing in-depth insights into biological processes and disease mechanisms. Previous SRT databases have limitations in curating sufficient single-cell and SRT pairs (SC-SP pairs) and providing real-time heuristic analysis, which hinder the effort to uncover potential biological insights. Here, we developed Pairpot (http://pairpot.bioxai.cn), a database tailored for paired single-cell and SRT data with real-time heuristic analysis. Pairpot curates 99 high-quality pairs including 1,425,656 spots from 299 datasets, and creates the association networks. It constructs the curated pairs by integrating multiple slices and establishing potential associations between single-cell and SRT data. On this basis, Pairpot adopts semi-supervised learning that enables real-time heuristic analysis for SC-SP pairs where Lasso-View refines the user-selected SRT domains within milliseconds, Pair-View infers cell proportions of spots based on user-selected cell types in real-time and Layer-View displays SRT slices using a 3D hierarchical layout. Experiments demonstrated Pairpot's efficiency in identifying heterogeneous domains and cell proportions.

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Pairpot:为配对单细胞和空间转录组学量身定制的基于实时套索分析的数据库。
成对的单细胞和空间分辨转录组学(SRT)数据可以相互补充,深入揭示生物过程和疾病机制。以前的SRT数据库在收集足够的单细胞和SRT配对(SC-SP配对)和提供实时启发式分析方面存在局限性,这阻碍了发现潜在生物学见解的努力。在此,我们开发了Pairpot(http://pairpot.bioxai.cn),这是一个专为单细胞和SRT数据配对而定制的数据库,并提供实时启发式分析。Pairpot 从 299 个数据集中筛选出 99 个高质量配对(包括 1,425,656 个点),并创建关联网络。它通过整合多个切片和建立单细胞与 SRT 数据之间的潜在关联来构建所策划的配对。在此基础上,Pairpot 采用半监督学习技术,可对 SC-SP 对进行实时启发式分析,其中 Lasso-View 可在几毫秒内完善用户选择的 SRT 域,Pair-View 可根据用户选择的细胞类型实时推断点的细胞比例,Layer-View 可使用三维分层布局显示 SRT 切片。实验证明了 Pairpot 在识别异质域和细胞比例方面的效率。
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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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