analogous 发表于 2025-3-30 09:22:09

Generalized Linear Mixed Models for Longitudinal Microbiome Data, take account for correlated observations with random effects while considering over-dispersion and zero-inflation. First, it reviews and discusses some general issues of GLMMs in microbiome research. Then, it introduces three GLMMs that model over-dispersed and zero-inflated longitudinal microbiome

百科全书 发表于 2025-3-30 12:34:02

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DAMN 发表于 2025-3-30 20:20:24

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myalgia 发表于 2025-3-30 22:03:15

Alpha Diversity,. This chapter focuses on alpha diversity analysis. First, it introduces abundance-based alpha diversity metrics and phylogenetic metrics. Then, it explores alpha diversity and abundance by some common plots. Next, it describes statistical hypothesis testing of alpha diversity using R and QIIME 2.

阻止 发表于 2025-3-31 01:53:37

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兵团 发表于 2025-3-31 08:32:18

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GRIN 发表于 2025-3-31 12:33:24

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Override 发表于 2025-3-31 15:53:40

Isabelle Kürschner,Astrid Nelkeput. This chapter first introduces abundance-based and phylogenetic beta diversity metrics, respectively; then introduces ordination methods and ordination plots. Next, it illustrates the beta diversity metrics and ordination in QIIME 2. Finally, it conducts some general remarks on ordination and clustering.

Left-Atrium 发表于 2025-3-31 17:55:44

Karriereziel Hochschulprofessur transformations. Then, it introduces three methods/models of CoDA: ANOVA-like compositional differential abundance analysis (ALDEx2), analysis of composition of microbiomes (ANCOM), analysis of composition of microbiomes-bias correction (ANCOM-BC). Next, it provides some remarks on CoDA approach.

bizarre 发表于 2025-4-1 00:52:52

OTU Methods in Numerical Taxonomy,ormation and characteristics of commonly clustering-based OTU methods, which have large impact on microbiome study in both concept and methodology. Fifth, it introduces statistical hypothesis testing of OTUs. Sixth, it describes the characteristics of clustering-based OTU methods.
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查看完整版本: Titlebook: Bioinformatic and Statistical Analysis of Microbiome Data; From Raw Sequences t Yinglin Xia,Jun Sun Book 2023 Springer Nature Switzerland A