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Nextclade: clade assignment, mutation calling and quality control for viral genomes

📅 Published: November 30, 2021 👤 Ivan Aksamentov, Cornelius Roemer, Emma B. Hodcroft et al. 📖 The Journal of Open Source Software 📊 1,106 citations
AI-Generated Summary

The variants of concern (VoCs) of SARS-CoV-2 have highlighted the need for a global molecular surveillance of pathogens via whole genome sequencing. Nextclade aligns viral genomes to a reference sequence, calculates several quality control (QC) metrics, assigns sequences to a clade or variant, and identifies changes in the viral proteins relative to the reference sequence.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 Such sequencing, for SARS-CoV-2 and other pathogens, is performed by an ever increasing number of labs across the globe, resulting in an increased need for an easy, fast, and decentralized analysis of initial data.
  • 2 Nextclade aligns viral genomes to a reference sequence, calculates several quality control (QC) metrics, assigns sequences to a clade or variant, and identifies changes in the viral proteins relative to the reference sequence.
  • 3 Nextclade is available as a command-line tool and as a web application with completely client based processing, meaning that sequence data doesn't leave the user's browser.
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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Article Details
Source OpenAlex
Category 🤖 Artificial Intelligence
Published Nov 30, 2021
Journal The Journal of Open Source Software
DOI 10.21105/joss.03773
Citations 1,106
Authors Ivan Aksamentov, Cornelius Roemer, Emma B. Hodcroft, Richard A. Neher