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arxiv: 1709.05701 · v1 · pith:PIJYKL4Dnew · submitted 2017-09-17 · 🧬 q-bio.MN · q-bio.GN

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

classification 🧬 q-bio.MN q-bio.GN
keywords dataapproachbiologycausalhigh-throughputidentifynumbersystems
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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.

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