Abstract: Methods for creating a model that is a graphical representation are provided. In one aspect, a method includes including receiving a first dataset including a first variable and a third variable, and a second dataset including a second variable and the third variable. The method also includes creating graphical representations of the first and second datasets by applying conditional independence tests on them, and storing conditional independence information obtained by applying the conditional independence tests on the first and second datasets. The method also includes applying a bivariate causal discovery algorithm. The method further includes modifying the graphical representations of the first and second dataset according to the determined causal relations, and creating a set of candidate graphical representations for a third dataset including the first and second datasets. Each candidate graphical representation is consistent with the conditional independence information.

Abstract: The present application provides materials and methods for treating hemoglobinopathies. More specifically, the application provides methods for producing progenitor cells that are genetically modified via genome editing to increase the production of fetal hemoglobin (HbF), as well as modified progenitor cells (including, for example, CD34+ human hematopoietic stem cells) producing increased levels of HbF, and methods of using such cells for treating hemoglobinopathies such as sickle cell anemia and ?-thalassemia.