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As an additional analysis to further verify our findings of core microbiome explainability (by prediction) of host phenotypes and experimental variables, we repeated that analysis using RF regression.

The abundances of the core microbes within each farm were used as features fed into a RF regression model (21, 22) to predict each of the traits (separately). Our approach followed a leave-one-out cross-validation methodology where, in each iteration, one sample (animal) was omitted from the entire set, and the model built from all the other animals (training set) was used to predict the trait value of the excluded sample (animal). Thereafter, the prediction R2 value between vector of actual and predicted values was calculated using R CARET package function R2.

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