A novel gene mapping algorithm based on independent component analysis

Identifying the causal genetic markers responsible for complex diseases is a main aim in human genetics. In the context of complex diseases, which are believed to have multiple causal loci of largely unknown effect and position, there is a need to develop advanced methods for gene mapping. In this work, we propose a novel algorithm based on independent component analysis for gene mapping. To apply the algorithm, we model the intra-cellular interactions as a mixing process of multiple sources. Results prove the superiority of the proposed algorithm over conventional statistical based methods, and demonstrate yet another successful application of a well known signal processing technique to an important problem in the field of human genetics.