Welcome

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You are reading the online book, Orchestrating Microbiome Analysis with R and Bioconductor (Lahti et al. 2021), where we walk through common strategies and workflows in microbiome data science.

The book shows through concrete examples how you can take advantage of the latest developments in R/Bioconductor for the manipulation, analysis, and reproducible reporting of hierarchical and heterogeneous microbiome profiling data sets. The book was borne out of necessity, while updating microbiome analysis tools to work with Bioconductor classes that provide support for multi-modal data collections. Many of these techniques are generic and widely applicable in other contexts as well.

This work has been heavily influenced by other similar resources, in particular the Orchestrating Single-Cell Analysis with Bioconductor (R. A. Amezquita et al. 2020), phyloseq tutorials (B. J. Callahan et al. 2016) and microbiome tutorials (Shetty and Lahti 2019). This book extends these resources to teach the grammar of Bioconductor workflows in the context of microbiome data science. As such, it supports the adoption of general skills in the analysis of large, hierarchical, and multi-modal data collections. We focus on microbiome analysis tools, including entirely new, partially updated as well as previously established methods.

This online resource and its associated ecosystem of microbiome data science tools are a result of a community-driven development process, and welcoming new contributors. Several individuals have contributed methods, workflows and improvements as acknowledged in the Introduction. You can find more information on how to find us online and join the developer community through the project homepage at microbiome.github.io. This online resource has been written in RMarkdown with the bookdown R package. The material is free to use with the Creative Commons Attribution-NonCommercial 3.0 License.


Bibliography

Amezquita, Robert A., Aaron T. L. Lun, Etienne Becht, Vince J. Carey, Lindsay N. Carpp, Ludwig Geistlinger, Federico Marini, et al. 2020. “Orchestrating Single-Cell Analysis with Bioconductor.” Nature Methods 17: 137–45. https://doi.org/10.1038/s41592-019-0654-x.
Callahan, Ben J., Kris Sankaran, Julia A. Fukuyama, Paul J. McMurdie, and Susan P. Holmes. 2016. “Bioconductor Workflow for Microbiome Data Analysis: From Raw Reads to Community Analyses [Version 2; Peer Review: 3 Approved].” F1000Research 5: 1492. https://doi.org/10.12688/f1000research.8986.2.
Lahti, Leo, Sudarshan Shetty, Felix M Ernst, et al. 2021. Orchestrating Microbiome Analysis with Bioconductor [Beta Version]. microbiome.github.io/oma/.
Shetty, Sudarshan, and Leo Lahti. 2019. “Microbiome Data Science.” Journal of Biosciences 44: 115. https://doi.org/10.1007/s12038-019-9930-2.