Floating Feature Selection for multiloci association of quantitative traits in sib-pairs analysis

Finding association between genotypic differences and disease traits has become one of the main objectives in current genetic research. It has been published that some of the underlying factors in the dynamics of the coagulation process have a genetic compound, showing significant hereditability. This is the case of the Factor VII. In this work, we propose a method for selecting sets of Single Nucleotide Polymorphisms (SNPs) of the F7 gene that are significantly related with the phenotype (Factor VII levels). The methodology is applied to the sib pairs from the GAIT project sample. The method consists of an adapted Sequential Floating Feature Selection (SFFS) algorithm. This algorithm is applied with two relevance criteria, one linear and one non linear. The SNPs sets found with linear models are included in the sets found with non linear techniques. The results fit in with previous results in clinical area.