FastPop is an efficient R package that fills the gap between Structure and Eigenstrat. It can: 1, generate PCA scores that identify ancestral origins and can be used for multiple studies; 2, infer ancestry information for data arising from two or more intercontinental origins.
CCH (Combinatorial Conflicting Homozygosity) uses dense Single Nucleotide Polymorphism (SNP) genotypes to identify regions of the genome inherited from a common ancestor among any or all subsets of a group. Analysis is rapid and can identify loci containing genes for dominant traits. CCH is robust to the presence of phenocopies and can detect undisclosed shared common ancestry.
LAMP (Local Ancestry in adMixed Populations) is a software for the inference of locus-specific ancestry in recently admixed populations. LAMP computes the ancestry structure for overlapping windows of contiguous SNPs and combines the results with a majority vote.
LAMP-LD is a software package for the inference of locus-specific ancestry in recently admixed populations.
hindex calculates a hybrid index for individuals of unknown ancestry. The index is based on information from molecular markers and uses maximum-likelihood to estimate the proportion of alleles that were inherited from one of two hybridizing parental species.
ANCESTRYMAP finds skews in ancestry that are potentially associated with disease genes in recently mixed populations like African Americans. Admixture mapping is a method for localizing disease causing genetic variants that differ in frequency across populations. It is most advantageous to apply this approach to populations that have descended from a recent mix of two ancestral groups that have been geographically isolated for many tens of thousands of years: for example, African Americans have both West African and European American ancestry. The approach assumes that near a disease causing gene there will be enhanced ancestry from the population that has greater risk of getting the disease. Thus if one can calculate the ancestry along the genome for an admixed sample set, one could use that to identify disease causing gene variants. The figure below shows a schematic of how a disease locus would appear in an admixture scan of patients and controls.