Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes
by Deborah Kunkel, Peter Sørensen, Vijay Shankar, Fabio Morgante
Polygenic prediction of complex trait phenotypes has become important in human genetics, especially in the context of precision medicine. Recently, mr.mash, a flexible and computationally efficient method that models multiple phenotypes jointly and leverages sharing of effects across such phenotypes to improve prediction accuracy, was introduced. However, a drawback of mr.mash is that it requires individual-level data, which are often not publicly available. Читать дальше...
