mbtransfer: Microbiome intervention analysis using transfer functions and mirror statistics
Fig 1
Overview of the transfer function approach to modeling microbiome interventions.
(A) A transfer function model (Eq 1) is trained to forecast future community profiles. This model leverages past community data, past and current intervention information, and static subject-level characteristics. (B) Forecasts on held-out subjects are used to evaluate model performance, potentially guiding model improvements. (C) The trained models are used to simulate counterfactual trajectories, supporting the study of hypothetical interventions. Multiple interventions can be applied concurrently, and they may be real-valued. (D) To identify taxa sensitive to the interventions, partial dependence effects from simulated trajectories are used to calculate mirror statistics.