Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions

Methods Mol Biol. 2018;1849:227-242. doi: 10.1007/978-1-4939-8728-3_15.

Abstract

Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g., mammals and microbes) using diverse types of data.

Keywords: Causal relationships; Network analysis; Omics; Transkingdom.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Animals
  • Computational Biology / methods*
  • Gene Regulatory Networks*
  • Host Microbial Interactions*
  • Humans
  • Microbiota*
  • Systems Biology / methods*