We have developed of a general framework of distributed learning (also known as collaborative learning) methods with novel inferential procedures that integrate sensitive biomedical data (e.g., EHR data and biobank data) across multiple institutes. We refer to this framework as PDA:Privacy-preserving Distributed Algorithms. Our algorithms are communication-efficient, which only require the collaborating sites to send aggregated information to the coordinating site once.