Machine Learning Microbiome with SIAMCAT
Abstract
This chapter focuses on the SIAMCAT ( S tatistical I nference of A ssociations between M icrobial C ommunities A nd host pheno T ypes) package in R. In addition to the Summary, there are three sections. Section 14.1 introduces the SIAMCAT package, including testing association and confounders, building, evaluating, and interpreting the model. Section 14.2 describes how to implement machine learning algorithms with the SIAMCAT package and shows a case using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Section 14.3 provides some remarks on SIAMCAT, including the advantages and disadvantages of using this package.
Fields of Study & Subjects
Gut microbiota and health
Statistical Methods and Inference
Microbial Community Ecology and Physiology
Publication details
- Journal / source
- Chapman & Hall/CRC eBooks
- Pages
- 455–484
- Publication date
- 17 January 2026
- Language
- EN
- Document type
- Book chapter