Mapping by Admixture Linkage Disequilibrium (MALD) is an economical and powerful approach for the identification of genomic regions harboring disease susceptibility genes in recently admixed populations.     The MALD method screens through the genome of either affected or both affected and healthy admixed individuals, looking for chromosomal segments with an unusually high representation of the high-risk ancestry population for the disease.


  We developed an information theory based measure, called EMI (expected mutual information), that computes the impact of a set of markers on the ability to infer ancestry at each chromosomal location. Using a simple and effective algorithm for the selection of markers, we constructed panels that strive to maximize the EMI score. We demonstrate via well established simulation tools that our panels provide considerably more power and accuracy for inferring disease gene loci via the MALD method in comparison to previous methods.


  The approach used for panel construction also applies to the second phase of MALD where ancestry is inferred. This second step has several implementations that employ a Markov chain model which assigns the most probable ancestry for each location given the model parameters and marker data. Based on our model assumptions, the posterior probability of ancestry given the observed markers can be efficiently computed as well.
We present a novel framework for the inference of ancestry at each chromosomal location. The uniqueness of our method stems from the ability to incorporate complex probability models that account for linkage-disequilibrium in the ancestral populations.


Sivan Bercovici, Dan Geiger, Liran Shlush, Karl Skorecki and Alan Templeton. "Panel Construction for Mapping in Admixed Populations via Expected Mutual Information". Genome Research 18, 661-667, and in the proceedings of the 12th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2008.

Sivan Bercovici and Dan Geiger. "Inferring Ancestries Efficiently in Admixed Populations with Linkage Disequilibrium". Journal of Computational Biology 16, 2009.

Related Work

Smith et. al. "A high-density admixture map for disease gene discovery in african americans." The American Journal of Human Genetics, 74(5):1001-1013, May 2004.

Patterson et. al. "Methods for high-density admixture mapping of disease genes." The American Journal of Human Genetics, 74(5):979-1000, May 2004.

Tian et. al. "A genomewide single-nucleotide-polymorphism panel with high ancestry information for african american admixture mapping." The American Journal of Human Genetics, (79):640-649, 2006.