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Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host-microbiota and
Nolan K Newman1, Matthew S Macovsky1, Richard R Rodrigues2,3
1College of Pharmacy, Oregon State University, Corvallis, OR, USA.
Nature Protocols
|March 13, 2024
Summary
Transkingdom Network Analysis (TkNA) is a novel framework for analyzing host-microbiota interactions. It establishes causality in multi-omics data, identifying key players in disease without large sample sizes.
Area of Science:
- Systems biology
- Computational biology
- Microbiome research
Background:
- Understanding complex host-microbiota interactions is crucial for disease research.
- Existing multi-omics approaches often identify associations rather than causality.
- A need exists for robust, user-friendly tools to analyze integrated omics data.
Purpose of the Study:
- To introduce Transkingdom Network Analysis (TkNA), a causal-inference framework.
- To provide a holistic view of biological systems by integrating diverse omics data.
- To decipher key players and mechanisms in host-microbiota interactions.
Main Methods:
- TkNA integrates data from multiple cohorts and omics types.
- It reconstructs a statistical network model of biological relationships.
- Causality-sensitive metrics, thresholds, and topological criteria determine network edges.
Main Results:
- TkNA identifies robust, reproducible patterns across cohorts.
- It pinpoints key nodes controlling subnetworks and inter-kingdom communication.
- Network reconstruction is computationally efficient, often taking minutes.
Conclusions:
- TkNA establishes causality in multi-omics data, overcoming limitations of association studies.
- The framework is efficient, user-friendly, and does not require large sample sizes.
- TkNA offers a powerful approach for studying complex biological interactions in health and disease.
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