Investigates single nucleotide polymorphism (SNP) data. DIYABC is based on a simulation algorithm allowing the treatment of multi-population datasets with large number of loci. It can take into account complex population histories including any combination of population divergence events, admixture events and changes in past population size. This tool can serve to compare competing evolutionary scenarios and quantify their relative support.
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A software tool for maximum likelihood estimation of individual ancestries from multilocus SNP genotype datasets.
An application for accurately inferring chromosomal segments of distinct ancestry in admixed populations, using dense genetic data.
Supports formal tests of whether admixture occurred. AdmixTools is a suite of methods for learning about population mixtures. This package infers admixture proportions and dates. It implements five methods: the three-population test, D-statistics, F4-ratio estimation, admixture graph fitting, and rolloff. It also computes lower and upper bounds on each admixture proportion.
Estimates individual ancestry and admixture proportion. frappe is a full likelihood based estimator of individual admixture (IA) that uses high-density single nucleotide polymorphism (SNP) data.
Finds skews in ancestry that are potentially associated with disease genes in recently mixed populations like African Americans.
A powerful discriminative modeling approach that is faster (~30x) and more accurate than existing methods. We accomplish this by using a conditional random field parameterized by random forests trained on reference panels. RFMix is capable of learning from the admixed samples themselves to boost performance and autocorrect phasing errors. RFMix shows high sensitivity and specificity in simulated Hispanics/Latinos and African Americans and admixed Europeans, Africans, and Asians.