Here we will only mention some experimental design either accessible only via hiPSCs based models, or where hiPSCs based models offer a distinct advantage. Matched pair design is a widely used and powerful experimental design in which cases are matched to controls based on the value of one or more factors, allowing to control for confounding variables, e.g. sex, age and genetic background, in the design stage as opposed to the analysis stage. It has been successfully applied to post-mortem tissue samples 51–53, as well as to hiPSC studies 35,54. Matching is more efficient than controlling for confounding in the analysis when the sample size is small, if cost of matching is lower than cost of increasing the sample size. This is certainly true in the case of hiPSCs. On the downside, it is not always possible to find the required match, and this is especially true in the case of post-mortem tissue samples, due to the limited availability of covariates-matched tissue samples. The family design can be considered a subclass of the matched pair design, where the family (genetic)
