Titlebook: Bioinformatic and Statistical Analysis of Microbiome Data; From Raw Sequences t Yinglin Xia,Jun Sun Book 2023 Springer Nature Switzerland A

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北京人起源

云狀

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https://doi.org/10.1007/978-3-8350-9661-5clustering-based OTU methods and the purposes of using OTUs and definitions of species and species-level analysis in microbiome studies. Then, it introduces the OTU-based methods that move toward single-nucleotide resolution. Third, it describes moving beyond the OTU methods. Finally, it discusses t

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Isabelle Kürschner,Astrid Nelkeiversity measures the difference between two samples or communities. Beta diversity analysis requires a distance or dissimilarity measure matrix as input. This chapter first introduces abundance-based and phylogenetic beta diversity metrics, respectively; then introduces ordination methods and ordin

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https://doi.org/10.1007/978-3-531-94352-7cribes the general nonparametric methods for multivariate analysis of variance in ecological and microbiome data. Then, it mainly introduces two statistical hypothesis tests of beta diversity: analysis of similarity (ANOSIM) and permutational MANOVA (PERMANOVA), respectively. Next, it introduces ana

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積云

Karriereziel Hochschulprofessurtreated as compositional, Aitchison simplex, challenges of analysis of compositional data, fundamental principles of CoDA, and the family of log-ratio transformations. Then, it introduces three methods/models of CoDA: ANOVA-like compositional differential abundance analysis (ALDEx2), analysis of com

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https://doi.org/10.1007/978-3-658-26093-4 Univariate analysis analyzes the change of one taxon or alpha diversity over time. Multivariate analysis directly analyzes the change of multiple taxa simultaneously or distance/dissimilarity (beta diversities) over time. This chapter introduces using the classical univariate linear mixed-effects m