The admixture mapping tools include a suite of tools for use on multi-way admixed populations to overcome the limitation of existing tools, which tend to work best with 2- or 3-way admixed populations only. The admixture tools included in this project are:
1.    Tool for selecting the best proxy ancestral populations for an admixed population
2.    Tool for inferring local ancestry in admixed populations

The first tool is an important precursor for the second as identifying the correct ancestral populations is crucial to be able to accurately infer local ancestry. A prototype for this first tool has already been developed in the group. PROXYANC has two novel algorithms including the correlation between observed linkage disequilibrium in an admixed population and population genetic differentiation in ancestral populations, and an optimal quadratic programming based on the linear combination of population genetic distances (FST). PROXYANC was evaluated against other methods, such as the f3 statistic using a simulated 5-way admixed population as well as real data for the local South African Coloured (SAC) population, which is also 5-way admixed. The simulation results showed that PROXYANC was a significant improvement on existing methods for multi-way admixed populations.

For the second tool, we have evaluated some of the existing methods for inferring local ancestry (or locus-specific ancestry) and determining the date of admixture on multi-way admixed populations including the SAC and simulated data. These methods include HapMix, ROLLOFF and a PCA-based method, StepPCO for dating admixture, and WinPOP and LampLD for local-ancestry. All three of the dating tools gave quite different predictions of the date of admixture events, showing the lack of accuracy of existing methods and need for a better one


PROXYANC implements an approach to select the best proxy ancestral populations for admixed populations. It searches for the best combination of reference populations that can minimize the genetic distance between the admixed population and all possible synthetic populations, consisting of a linear combination from reference populations. PROXYANC also computes a proxy-ancestry score by regressing a statistic for LD (at short distance < 0.25 Morgan) between a pair of SNPs in the admixed population against a weighted ancestral allele frequency differentiation. Download PROXYANC.

PROXYANANC can select AIMs based on the relationship between the observed local multi-locus linkage disequilibrium in a recently admixed population and ancestral population difference in allele frequency and based on the Kernel principal component analysis (Kernel-PCA), which is the extension of the linear PCA.

PROXYANC can identify possible unusual difference in allele frequency between pair-wise popualtions, as signal of natural selection.

PROXYANC compute the expected maximun admixture LD from proxy ancestral populations of the admixed population.

PROXYANC compute population pair-wise Fst (Genetic distance).



ancGWAS is an algebraic graph-based method to identify the most significant sub-network underlying ethnic difference in complex diseases risk in a recently admixed population. This approach integrates the association signal from a GWAS data set, the local ancestry, and SNP pair-wise linkage disequilibrium from the admixed population into the PPI network.



ancMETA is an application for leveraging cross-population Gene/Sub-network Meta-analysis to recover Disease Association Signal (DAS) risk in a homogenous or recently admixed population. This approach integrates the association signal from a GWAS data set, the local ancestry, and SNP pair-wise linkage disequilibrium into both the PPI and Protein-functional network.