RevPert: predicting candidate drivers of transcriptomic state transitions via gallery-native reverse perturbation
RevPert is a gallery-native reverse perturbation model that predicts candidate drivers from a fixed genetic catalog for a query contrast ΔY ⋆ = YB −YA by combining signed Pearson connectivity with a learned residual, and couples within-screen reverse prediction to a screen-external signed-geometry check.