Equally, it is critical with any iPSC disease model to pinpoint a cell type in which the disease manifests, to be able to differentiate effectively into these cells, and to identify a molecular or cellular phenotypic readout of the disease state. Differentiation protocols are now available to efficiently generate a large variety of lineages, and many others are being developed using cocktails of small molecule inhibitors or transcription factor overexpression (Cohen and Melton 2011; Mertens et al. 2016; Murry and Keller 2008). Although such protocols often result in a mixed population, purification of the desired cells by for example fluorescence-activated cell sorting (FACS) using an appropriate marker or reporter gene can be used to enrich for the population of interest (Horikiri et al. 2017; Wu et al. 2016a, b). Perhaps more critical to the success of any cellular disease model is the identification of a molecular or cellular phenotype that correlates with the disease state. In many cases, this can be identified through global gene expression profiling of patient and control samples (at the RNA or protein level), and identification
