Statistical analysis of microbiome data with R

DOI10.1007/978-981-13-1534-3zbMath1407.62024OpenAlexW2894661298MaRDI QIDQ1622658

Y. Aharonov

Publication date: 19 November 2018

Published in: ICSA Book Series in Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-981-13-1534-3

zbMATH Keywords

data analysisstatistical analysisstatistical modellingbig dataecologymicrobiome data

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Applications of statistics to biology and medical sciences; meta analysis (62P10) Research exposition (monographs, survey articles) pertaining to statistics (62-02) Genetics and population dynamics (92D99)

Related Items (8)

Modeling sparse data using MLE with applications to microbiome data ⋮ Joint modeling of zero‐inflated longitudinal proportions and time‐to‐event data with application to a gut microbiome study ⋮ It's All Relative: Regression Analysis with Compositional Predictors ⋮ Assessing mediating effects of high‐dimensional microbiome measurements in dietary intervention studies ⋮ A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant ⋮ A Bayesian framework for identifying consistent patterns of microbial abundance between body sites ⋮ An R package AZIAD for analysing zero-inflated and zero-altered data ⋮ Zero-inflated models for adjusting varying exposures: a cautionary note on the pitfalls of using offset

Uses Software

• compositions
• R
• ggplot2
• vegan
• edgeR
• DEGseq
• GUniFrac
• limma
• RStudio
• robCompositions
• Phyloseq
• Voom
• DOTUR
• propr
• UrQt
• pplacer
• MDSINE
• MicrobiomeAnalyst
• MetamicrobiomeR
• HMP
• INMEX
• betapart
• NeatMap

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