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EDGE COVID-19:一个从 SARS-CoV-2 测序工作中生成可提交基因组的网络平台。

EDGE COVID-19: a web platform to generate submission-ready genomes from SARS-CoV-2 sequencing efforts.

机构信息

Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

National Center for Biotechnology Information, U.S. National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.

出版信息

Bioinformatics. 2022 May 13;38(10):2700-2704. doi: 10.1093/bioinformatics/btac176.

Abstract

SUMMARY

Genomics has become an essential technology for surveilling emerging infectious disease outbreaks. A range of technologies and strategies for pathogen genome enrichment and sequencing are being used by laboratories worldwide, together with different and sometimes ad hoc, analytical procedures for generating genome sequences. A fully integrated analytical process for raw sequence to consensus genome determination, suited to outbreaks such as the ongoing COVID-19 pandemic, is critical to provide a solid genomic basis for epidemiological analyses and well-informed decision making. We have developed a web-based platform and integrated bioinformatic workflows that help to provide consistent high-quality analysis of SARS-CoV-2 sequencing data generated with either the Illumina or Oxford Nanopore Technologies (ONT). Using an intuitive web-based interface, this workflow automates data quality control, SARS-CoV-2 reference-based genome variant and consensus calling, lineage determination and provides the ability to submit the consensus sequence and necessary metadata to GenBank, GISAID and INSDC raw data repositories. We tested workflow usability using real world data and validated the accuracy of variant and lineage analysis using several test datasets, and further performed detailed comparisons with results from the COVID-19 Galaxy Project workflow. Our analyses indicate that EC-19 workflows generate high-quality SARS-CoV-2 genomes. Finally, we share a perspective on patterns and impact observed with Illumina versus ONT technologies on workflow congruence and differences.

AVAILABILITY AND IMPLEMENTATION

https://edge-covid19.edgebioinformatics.org, and https://github.com/LANL-Bioinformatics/EDGE/tree/SARS-CoV2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

摘要

基因组学已成为监测新发传染病暴发的一项重要技术。全球实验室正在使用一系列病原体基因组富集和测序技术和策略,同时采用不同的、有时是特别的分析程序来生成基因组序列。从原始序列到确定共识基因组的完整集成分析流程对于正在进行的 COVID-19 大流行等暴发至关重要,可为流行病学分析和明智决策提供坚实的基因组基础。我们开发了一个基于网络的平台和集成的生物信息学工作流程,有助于对使用 Illumina 或牛津纳米孔技术(ONT)生成的 SARS-CoV-2 测序数据进行一致的高质量分析。该工作流程使用直观的基于网络的界面,自动执行数据质量控制、基于 SARS-CoV-2 参考的基因组变异和共识调用、谱系确定,并提供将共识序列和必要元数据提交给 GenBank、GISAID 和 INSDC 原始数据存储库的功能。我们使用真实世界的数据测试了工作流程的可用性,并使用多个测试数据集验证了变异和谱系分析的准确性,还进一步与 COVID-19 Galaxy Project 工作流程的结果进行了详细比较。我们的分析表明,EC-19 工作流程生成了高质量的 SARS-CoV-2 基因组。最后,我们分享了在 Illumina 与 ONT 技术的工作流程一致性和差异方面观察到的模式和影响的观点。

可及性和实施情况

https://edge-covid19.edgebioinformatics.org,和 https://github.com/LANL-Bioinformatics/EDGE/tree/SARS-CoV2。

补充信息

补充数据可在 Bioinformatics 在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e68/9113274/20f99f238021/btac176f1.jpg

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