Kajsa Ljungberg's home page.

QTL-mapping software

Software developed as part of thesis work.

Project description.

Evaluating the LS objective function

The objective function is the residual norm of a LS problem min ||Xb-y||, where X depends on the position in the search space. However some columns of X are constant. For efficiency we use updated QR factorizations and do not solve the complete problem since only the residual is needed, not the regression parameters b.

The updating is efficient only if the number of constant columns in X is large enough, otherwise a library QR factorization should be used. The complete LS problem should still not be solved.

K. Ljungberg, S. Holmgren and Ö. Carlborg. Efficient algorithms for quantitative trait loci mapping problems. Journal of computational biology, Vol 9, pp. 793-804, 2002. .

Global optimization

We have used the DIRECT global optimization algorithm to find point in search space with minimal value of objective function. The algorithm can be coupled with any objective function routine fulfilling given specifications.

DIRECT original reference:

D. Jones, C.D. Perttunen and B.E. Stuckman. Lipschitzian optimization without the Lipschitz constant. Journal of Optimization Theory and Application, Vol 79, pp. 157-181, 1993.

Retrieving the source code below implies that you have agreed to cite

K. Ljungberg, S. Holmgren and Ö. Carlborg.
Simultaneous search for multiple QTL using the global optimization algorithm DIRECT. Bioinformatics 2004 20: 1887-1895.

in any publication or presentation where the algorithm has been used for the work. Source Readme

The project is a collaboration between Kajsa Ljungberg and Sverker Holmgren at the Department of Scientific Computing, Örjan Carlborg, Kateryna Mishchenko at Mälardalen university college , Leif Andersson at the Department of animal breeding and genetics at SLU, Martina Persson from the Department of Mathematics, Mathematical Statistics Group at Uppsala University, and Razaw AL-Sarraj and Dietrich von Rosen from the Department of biometrics and informatics at SLU.