Best practices for analysing microbiomes

By Rob Knight, Alison Vrbanac, Bryn C. Taylor, A. Aksenov, C. Callewaert, Justine W. Debelius, Antonio Gonzalez, T. Kościółek, Laura-Isobel McCall, Daniel McDonald and 13 more. Nature Reviews Microbiology, 2018

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Linking metagenomics to aquatic microbial ecology and biogeochemical cycles (2019, methodology): “Such diagrams are preparedmanually by inspecting gene annotations, often with assistance from software that projects predicted functions onto pathway maps, such as MetaPathways (Konwar et al. 2015) and KEGG (Kanehisa et al. 2019).”
QIIME 2 Enables Comprehensive End‐to‐End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data (2020, background): “Several points are important to consider before beginning your analysis, and have been reviewed recently to provide best practices for microbiome studies (Allaband et al., 2019; Knight et al., 2018).”
Microbiome definition re-visited: old concepts and new challenges (2020, background): “The high potential and enormous power of combining multiple “omics” techniques to analyze hostmicrobe interactions are highlighted in several reviews [17, 38].”
A practical guide to amplicon and metagenomic analysis of microbiome data (2020, background): “and standards have been evolving rapidly over the past few years (Knight et al., 2018).”
Quantitative PCR provides a simple and accessible method for quantitative microbiota profiling (2020, background): “Since the changes of components are mutually dependent, high false discovery rates occur when compositional data are analyzed using traditional statistical methods [1].”