Orchestrating an optimized next-generation sequencing-based cloud workflow for robust viral identification during pandemics

Hendrick Gao Min Lim, Shih Hsin Hsiao, Yuan Chii Gladys Lee

研究成果: 雜誌貢獻文章同行評審

摘要

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become a novel pandemic event following the swine flu that occurred in 2009, which was caused by the influenza A virus (H1N1 subtype). The accurate identification of the huge number of samples during a pandemic still remains a challenge. In this study, we integrate two technologies, next-generation sequencing and cloud computing, into an optimized workflow version that uses a specific identification algorithm on the designated cloud platform. We use 182 samples (92 for COVID-19 and 90 for swine flu) with short-read sequencing data from two open-access datasets to represent each pandemic and evaluate our workflow performance based on an index specifically created for SARS-CoV-2 or H1N1. Results show that our workflow could differentiate cases between the two pandemics with a higher accuracy depending on the index used, especially when the index that exclusively represented each dataset was used. Our workflow substantially outperforms the original complete identification workflow available on the same platform in terms of time and cost by preserving essential tools internally. Our workflow can serve as a powerful tool for the robust identification of cases and, thus, aid in controlling the current and future pandemics.

原文英語
文章編號1023
期刊Biology
10
發行號10
DOIs
出版狀態已發佈 - 十月 2021

ASJC Scopus subject areas

  • 生物化學、遺傳與分子生物學 (全部)
  • 免疫學與微生物學 (全部)
  • 農業與生物科學 (全部)

指紋

深入研究「Orchestrating an optimized next-generation sequencing-based cloud workflow for robust viral identification during pandemics」主題。共同形成了獨特的指紋。

引用此