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使用 Illumina 短读测序数据快速对靶向病毒样本进行基因分型。

Rapid genotyping of targeted viral samples using Illumina short-read sequencing data.

机构信息

Department of Metagenomics, University of Debrecen, Debrecen, Hungary.

Department of Laboratory Medicine, University of Pécs, Pécs, Hungary.

出版信息

PLoS One. 2022 Sep 16;17(9):e0274414. doi: 10.1371/journal.pone.0274414. eCollection 2022.

Abstract

The most important information about microorganisms might be their accurate genome sequence. Using current Next Generation Sequencing methods, sequencing data can be generated at an unprecedented pace. However, we still lack tools for the automated and accurate reference-based genotyping of viral sequencing reads. This paper presents our pipeline designed to reconstruct the dominant consensus genome of viral samples and analyze their within-host variability. We benchmarked our approach on numerous datasets and showed that the consensus genome of samples could be obtained reliably without further manual data curation. Our pipeline can be a valuable tool for fast identifying viral samples. The pipeline is publicly available on the project's GitHub page (https://github.com/laczkol/QVG).

摘要

微生物最重要的信息可能是其准确的基因组序列。利用当前的下一代测序方法,测序数据可以以前所未有的速度生成。然而,我们仍然缺乏用于自动化和准确基于参考的病毒测序读段基因分型的工具。本文介绍了我们设计的用于重建病毒样本优势共识基因组并分析其宿主内变异性的流水线。我们在众多数据集上对我们的方法进行了基准测试,结果表明,无需进一步的手动数据整理,就可以可靠地获得样本的共识基因组。我们的流水线可以成为快速识别病毒样本的有价值工具。该流水线在项目的 GitHub 页面(https://github.com/laczkol/QVG)上公开可用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a98/9481040/f51230612fad/pone.0274414.g001.jpg

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