Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper.
Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper.
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使用 EcoTyper 以单细胞分辨率和规模分析细胞生态系统。
DOI：
10.1007/978-1-0716-2986-4_4
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Newman,AaronM
中科院分区：
文献类型：
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作者：
Steen,ChloéB;Luca,BogdanA;Alizadeh,AshA;Gentles,AndrewJ;Newman,AaronM
组织由不同的细胞类型和细胞状态组成，它们组织成具有专门功能的独特生态系统。EcoTyper是一个机器学习工具的集合，用于从大量，单细胞和空间分辨的基因表达数据中大规模描绘细胞生态系统及其组成细胞状态。在这一章中，我们提供了一个引物EcoTyper和展示其用于发现和恢复健康和患病组织标本的细胞状态和生态系统。
Tissues are composed of diverse cell types and cellular states that organize into distinct ecosystems with specialized functions. EcoTyper is a collection of machine learning tools for the large-scale delineation of cellular ecosystems and their constituent cell states from bulk, single-cell, and spatially resolved gene expression data. In this chapter, we provide a primer on EcoTyper and demonstrate its use for the discovery and recovery of cell states and ecosystems from healthy and diseased tissue specimens.