@inbook{dbd981c3d701403689d766612b86bd4c,
title = "Inference and Analysis of SPIEC-EASI Microbiome Networks",
abstract = "Network analysis facilitates examination of the interactions between different populations in a community. It can provide a range of metrics describing the social characteristics of each population and emergent structural properties of the community, which may be used to address novel ecological questions. Using a publicly available dataset, this chapter provides point-by-point code and instructions to infer and analyze a SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference) network using free, open source software (R and Gephi).",
keywords = "Algorithms, Computational Biology/methods, Humans, Microbiota/genetics, RNA, Ribosomal, 16S/genetics, Software",
author = "Birt, {Henry W G} and Dennis, {Paul G}",
year = "2021",
doi = "10.1007/978-1-0716-1040-4_14",
language = "English",
isbn = "9781071610428",
series = "Methods in molecular biology (Clifton, N.J.)",
publisher = "Springer Nature",
pages = "155--171",
editor = "Carvalhais, {Lilia C.} and Dennis, {Paul G.}",
booktitle = "The Plant Microbiome",
address = "United States",
}