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RNA 去卷积方法及其应用的全面概述。

A Comprehensive Overview of RNA Deconvolution Methods and Their Application.

机构信息

School of Biological Sciences, Seoul National University, Seoul 08826, Korea.

Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands.

出版信息

Mol Cells. 2023 Feb 28;46(2):99-105. doi: 10.14348/molcells.2023.2178.

Abstract

Tumors are surrounded by a variety of tumor microenvironmental cells. Profiling individual cells within the tumor tissues is crucial to characterize the tumor microenvironment and its therapeutic implications. Since single-cell technologies are still not cost-effective, scientists have developed many statistical deconvolution methods to delineate cellular characteristics from bulk transcriptome data. Here, we present an overview of 20 deconvolution techniques, including cutting-edge techniques recently established. We categorized deconvolution techniques by three primary criteria: characteristics of methodology, use of prior knowledge of cell types and outcome of the methods. We highlighted the advantage of the recent deconvolution tools that are based on probabilistic models. Moreover, we illustrated two scenarios of the common application of deconvolution methods to study tumor microenvironments. This comprehensive review will serve as a guideline for the researchers to select the appropriate method for their application of deconvolution.

摘要

肿瘤周围环绕着各种肿瘤微环境细胞。对肿瘤组织内的单个细胞进行分析对于描绘肿瘤微环境及其治疗意义至关重要。由于单细胞技术仍然不具有成本效益,因此科学家们开发了许多统计去卷积方法,以便从批量转录组数据中描绘细胞特征。在这里,我们概述了 20 种去卷积技术,包括最近建立的前沿技术。我们根据三个主要标准对去卷积技术进行分类:方法的特点、细胞类型的先验知识的使用以及方法的结果。我们强调了基于概率模型的最新去卷积工具的优势。此外,我们还说明了两种常见的去卷积方法在研究肿瘤微环境中的应用场景。本综述将为研究人员提供指导,帮助他们选择适合自己应用的去卷积方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/961f/9982058/c362f47d7f2c/molce-46-2-99-f1.jpg

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