Inference and Analysis of SPIEC-EASI Microbiome Networks

Henry W G Birt, Paul G Dennis

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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).

Original languageEnglish
Title of host publicationThe Plant Microbiome
Subtitle of host publicationMethods and Protocols
EditorsLilia C. Carvalhais, Paul G. Dennis
PublisherSpringer Nature
Pages155-171
Number of pages17
ISBN (Electronic)9781071610404
ISBN (Print)9781071610428, 9781071610398
DOIs
Publication statusPublished - 2021

Publication series

NameMethods in molecular biology (Clifton, N.J.)
PublisherHumana Press, Inc
Volume2232
ISSN (Print)1064-3745

Keywords

  • Algorithms
  • Computational Biology/methods
  • Humans
  • Microbiota/genetics
  • RNA, Ribosomal, 16S/genetics
  • Software

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