Gut-host Crosstalk: Methodological and Computational Challenges
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Understanding how health-promoting microbiota are established and their beneficial interactions with the host is of critical biomedical importance. The current high throughput data acquisition technologies allow for integrating components of the gut ecosystem. The richness of data types and large number of measured variables involved underscores the critical importance of the appropriate choice of analytical and computational methods that can be used to model this complex ecosystem. This review outlines currently used approaches to perform analyses of data obtained as a result of interrogation of the gut-microbiota ecosystem and the challenges associated with these methodological and computational efforts. The problem of large dimensionality versus small numbers of samples is explained with discussions of clustering, dimensionality reduction, and statistical testing. Predictive modeling and data integration specific to the gut ecosystem are also discussed.
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