In this paper, we are interested in discovering genetic factors that are involved in multifactorial diseases. Therefore, experiments have been achieved by the Biological Institute of Lille and a lot of data has been generated. To exploit this data, data mining tools are required and we propose a 2-phase optimization approach using a specific genetic algorithm. During the first step, we select significant features with a specific genetic algorithm. Then, during the second step, we cluster affected individuals according to the features selected by the first phase. The paper describes the specificities of the genetic problem that we are studying and presents in details the genetic algorithm that we have developed to deal with this very large size problem of feature selection. Results on both artificial and real data are presented.