DVsc: An Automated Framework for Efficiently Detecting Viral Infection from Single-Cell Transcriptomics Data

IF 11.5 2区生物学 Q1 GENETICS & HEREDITY Genomics, Proteomics & Bioinformatics Pub Date : 2024-01-10 DOI:10.1093/gpbjnl/qzad007

Fei Leng, Song Mei, Xiaolin Zhou, Xuanshi Liu, Yefeng Yuan, Wenjian Xu, Chongyi Hao, Ruolan Guo, Chanjuan Hao, Wei Li, Peng Zhang

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Abstract Single-cell RNA sequencing (scRNA-seq) has emerged as a valuable tool for studying cellular heterogeneity in various fields, particularly in virological research. By studying the viral and cellular transcriptomes, the dynamics of viral infection can be investigated at a single-cell resolution. However, limited studies have been conducted to investigate whether RNA transcripts from clinical samples contain substantial amounts of viral RNAs, and a specific computational framework for efficiently detecting viral reads based on scRNA-seq data has not been developed. Hence, we introduce DVsc, an open-source framework for precise quantitative analysis of viral infection from single-cell transcriptomics data. When applied to approximately 200 diverse clinical samples that were infected by more than 10 different viruses, DVsc demonstrated high accuracy in systematically detecting viral infection across a wide array of cell types. This innovative bioinformatics pipeline could be crucial for addressing the potential effects of surreptitiously invading viruses on certain illnesses, as well as for designing novel medicines to target viruses in specific host cell subsets and evaluating the efficacy of treatment. DVsc supports the FASTQ format as an input and is compatible with multiple single-cell sequencing platforms. Moreover, it could also be applied to sequences from bulk RNA-sequencing data. DVsc is available at http://62.234.32.33:5000/DVsc.

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DVsc：从单细胞转录组学数据中高效检测病毒感染的自动化框架

摘要单细胞 RNA 测序（scRNA-seq）已成为各领域，特别是病毒学研究中研究细胞异质性的重要工具。通过研究病毒和细胞转录组，可以在单细胞分辨率下研究病毒感染的动态变化。然而，目前对临床样本中的 RNA 转录本是否含有大量病毒 RNA 的研究还很有限，基于 scRNA-seq 数据有效检测病毒读数的特定计算框架也尚未开发出来。因此，我们引入了 DVsc，这是一个开源框架，用于从单细胞转录组学数据中对病毒感染进行精确的定量分析。DVsc 应用于约 200 个不同的临床样本，这些样本受到 10 多种不同病毒的感染，DVsc 在系统检测各种细胞类型的病毒感染方面表现出很高的准确性。这一创新的生物信息学管道对于研究偷偷入侵的病毒对某些疾病的潜在影响、设计针对特定宿主细胞亚群病毒的新型药物以及评估治疗效果至关重要。DVsc 支持将 FASTQ 格式作为输入，并与多种单细胞测序平台兼容。此外，它还可应用于大容量 RNA 测序数据的序列。DVsc可在http://62.234.32.33:5000/DVsc。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry

CiteScore

14.30

自引率

4.20%

发文量

844

审稿时长

61 days

期刊介绍： Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.