To combine information across the high-dimensional vector of gene expression profiles, we consider linear combinations of the form β0TXi, i = 1, . . ., n. Without loss of generality, we will also assume that larger values of this linear combination corresponding to increasing likelihood of having g = 1. While the method can be easily extended to incorporate interactions between gene expression measurements, we focus on consideration of the main effects for purposes of exposition.
