Comments on: ‘empirical Bayes for data integration’

Abstract We wish to congratulate the authors with this paper, as it is a nice mix of important conceptual ideas, strong theoretical results and relevant applications. The paper introduces a novel empirical Bayes framework for data integration in high-dimensional regression models, with a particular focus on variable selection. The main objective is to improve the identification of relevant variables by incorporating external information from previous studies or related sources. Such external information is referred to as meta-covariates . Others have used equivalent terms like ‘co-data’ (Neuenschwander et al. 2016; van Nee et al. 2021) or ‘features-of-features’ (Tay et al. 2023).