Efficient algorithms for multidimensional global optimization in genetic mapping of complex traits

ient algorithms for multidimensional global optimization in genetic mapping of complex traits Original Research (3182) Total Article Views Authors: Kajsa Ljungberg, Kateryna Mishchenko, Sverker Holmgren Published Date October 2010 Volume 2010:3 Pages 75 - 88 DOI: http://dx.doi.org/10.2147/AABC.S9240 Kajsa Ljungberg1, Kateryna Mishchenko2, Sverker Holmgren1 1Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden; 2Department of Mathematics and Physics, M lardalen University College, V ster s, Sweden Abstract: We present a two-phase strategy for optimizing a multidimensional, nonconvex function arising during genetic mapping of quantitative traits. Such traits are believed to be affected by multiple so called QTL, and searching for d QTL results in a d-dimensional optimization problem with a large number of local optima. We combine the global algorithm DIRECT with a number of local optimization methods that accelerate the final convergence, and adapt the algorithms to problem-specific features. We also improve the evaluation of the QTL mapping objective function to enable exploitation of the smoothness properties of the optimization landscape. Our best two-phase method is demonstrated to be accurate in at least six dimensions and up to ten times faster than currently used QTL mapping algorithms.