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

  • Richard R. RodriguesEmail author
  • Natalia Shulzhenko
  • Andrey MorgunEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1849)


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.

Key words

Omics Transkingdom Network analysis Causal relationships 



The authors thank Karen N. D’Souza, Khiem Lam, and Dr. Xiaoxi Dong for their help in writing the book chapter. This work was supported by the NIH U01 AI109695 (AM) and R01 DK103761 (NS).

Supplementary material

340450_1_En_15_MOESM1_ESM.pdf (4.1 mb)
File_S1_Supplem_doc (PDF 4174 KB)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of PharmacyOregon State UniversityCorvallisUSA
  2. 2.College of Veterinary MedicineOregon State UniversityCorvallisUSA

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