Individual SNP allele reconstruction from informative markers selected by a non-linear Gauss-type algorithm.
OBJECTIVE
In view of the linkage disequilibrium structure of the genome, the selection of maximally informative SNP markers is a fundamental issue in the design of association studies. Currently used selection methods rely on pairwise marker correlation or informativity measures for subsets of markers. Nevertheless, the selected markers do not provide a completely satisfactory description of the individual remaining markers. The number of tag markers can be further reduced by using haplotypic information, but then the results of association analysis are difficult to interpret.


RESULTS
We propose a non-linear Gauss-type algorithm selecting a subset of markers which is optimal with respect to the informativity measures and allows an explicit reconstruction of all other known markers, thus permitting direct inference of allelic association. The selection is based on the haplotype distribution in the population, but can be adapted to work with unphased genotypes directly.


CONCLUSIONS
The proposed algorithm provides a rational methodology of informative marker selection, allowing for control and optimisation of information content and full marker reconstruction. Moreover, the reconstruction step can also be applied to tag markers selected using a different method at the stage of study design, identifying those markers which cannot be uniquely recovered from the chosen tags.
Moskvina
Valentina
V
Department of Psychological Medicine, College of Medicine, Cardiff University, Cardiff, UK. MoskvinaV1@cardiff.ac.uk
Schmidt
Karl Michael
KM
D000465:Algorithms; D000483:Alleles; D016022:Case-Control Studies; D005819:Genetic Markers; D006239:Haplotypes / Q000235:genetics; D006801:Humans; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D020641:Polymorphism, Single Nucleotide
D005819:Genetic Markers