Pulse Brain · Growing Health Evidence Index
Tier 4 — Narrative / commentaryPeer-reviewed

Analysis of metagenomic data

Shaopeng Liu; Judith Rodríguez; Viorel Munteanu; Cynthia Ronkowski; Nitesh Kumar Sharma; Mohammed Alser; Francesco Andreace; Ran Blekhman; Dagmara Błaszczyk; Rayan Chikhi; Keith A. Crandall; Katja Della Libera; Dallace Francis; А.В. Фролова; Abigail S. Gancz; Naomi Huntley; Pooja Jaiswal; Tomasz Kościółek; Paweł P. Łabaj; Wojciech Łabaj; Tu Luan; Christopher E. Mason; Ahmed M. Moustafa; Harihara Subrahmaniam Muralidharan; Onur Mutlu; Nika Mansouri Ghiasi; Ali Rahnavard; Fengzhu Sun; Shuchang Tian; Braden Tierney; Emily Van Syoc; Riccardo Vicedomini; Joseph P. Zackular; Alex Zelikovsky; Kinga Zielińska; Erika Ganda; Emily Davenport; Mihai Pop; David Koslicki; Serghei Mangul

Nature Reviews Methods Primers · 2025

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Summary

This Nature Reviews Methods Primers article provides a structured, authoritative primer on the analysis of metagenomic data, authored by a large international consortium of microbiome and computational biology researchers. It likely synthesises current best practices across the full metagenomic analysis workflow — from raw sequence processing through to biological interpretation — with the aim of standardising approaches across research communities. As a Methods Primer, it serves primarily as a methodological reference rather than presenting novel experimental findings.

UK applicability

The methodological guidance offered is universally applicable, including to UK-based researchers working in agricultural microbiome science, soil metagenomics, and gut health studies; UK institutions engaging in metagenomic research as part of soil health or food systems monitoring would benefit directly from the standardised workflows described.

Key measures

Computational pipeline performance metrics; taxonomic classification accuracy; functional annotation approaches; benchmarking statistics for metagenomic tools

Outcomes reported

The primer likely covers best-practice workflows for processing, analysing, and interpreting metagenomic datasets, including quality control, taxonomic profiling, functional annotation, and benchmarking of computational tools. It probably addresses common analytical challenges such as reference database selection, read classification accuracy, and reproducibility across platforms.

Theme
Measurement & metrics
Subject
Microbiome analytics & bioinformatics methods
Study type
Narrative Review
Study design
Narrative review
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Microbiome / genomics research
DOI
10.1038/s43586-024-00376-6
Catalogue ID
NRmo3f02hq-0d8

Topic tags

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