MOSCATO

This code executes the Multi-Omic Single-Cell Analysis using TensOr regression (MOSCATO) method which uses multi-omic, single-cell data with two data types, X and G, and a univariate outcome which follows an exponential family distribution. In summary, it will estimate the similarity and perform tensor regression using the similarity as the predictor tensor. The features will be selected by applying an elastic net constraint on the coefficient vectors, and any non-zero coefficients will correspond to the features selected. In addition to applying MOSCATO, code to simulate multi-omic, single-cell data is also provided.