Genetic ancestry estimation software tools | Population genetics data analysis

Offers four statistical tests that have been used in studies of admixed populations. MIXSCORE is a method for combining single nucleotide polymorphism (SNP) association and admixture association statistics to increase power in genome-wide association study (GWAS) in admixed populations. The MIXSCORE approach requires local-ancestry estimates as input, which can be estimated by any method.

A program to estimate individual ancestry by directly analyzing shotgun sequence reads without calling genotypes. LASER uses principal components analysis (PCA) and Procrustes analysis to analyze sequence reads of each sample and place the sample into a reference PCA space constructed using genotypes of a set of reference individuals. With an appropriate reference panel, the estimated coordinates of the sequence samples reflect their ancestral background and can be used to correct for population stratification in association studies. LASER can accurately estimate ancestry even with modest amounts of data, such as the off-target sequence data generated by targeted sequencing experiments. LASER can be used to improve case-control matching in genetic association studies and to reduce the risk of spurious findings due to population structure.

A software tool for maximum likelihood estimation of individual ancestries from multilocus SNP genotype datasets.

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.

Implements a Bayesian Analysis of Molecular Variance and different likelihood models for three different types of molecular data (including two models for high throughput sequence data). This model will facilitate the population genetic analysis of a wide range of organisms on the basis of next-generation sequence data.

Finds skews in ancestry that are potentially associated with disease genes in recently mixed populations like African Americans.

A program suitable for genome-scale data which uses a “Markov-hidden Markov model” to estimate local ancestry.

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.

Intends to estimate relatedness in samples from structured populations with admixed ancestry. REAP measures autosomal kinship coefficients and identity-by-descent (IBD) sharing probabilities from single nucleotide polymorphism (SNP) genotype data. The application integrates functionalities allowing users to specify a subset of individuals to include in the relatedness estimation analysis as well as an inbreeding-coefficient estimator.

Takes advantage of off-targeted sequence reads from exome/targeted sequencing experiments for accurate local ancestry inference. Before running SEQMIX, it is important to LD prune your data so that pairs of sites in high LD (r^2 > 0.1) are identified and only the one with a higher sequence depth are included into the model. As the sequence depth distribution is sample dependent, it is necessary to prune the sequence data for each individual.

A software package for the inference of locus-specific ancestry in recently admixed populations.

A practical tool that allows visualization of samples sequenced by second-generation sequencing when compared with a reference panel of individuals (usually genotypes) using a multidimensional scaling algorithm.

Provides a lower bound on errors in the local ancestry estimates. MILANC is a method developed to observe in simulations underestimate the rate observed in real data and varies substantially across the genome. The MILANC rate provides a real data-based evaluation of local ancestry estimates as opposed to simulations that cannot measure systematic inaccuracies arising from violations of model assumptions.

A software package for inferring genome-wide genetic ancestry using SNP weights precomputed from large external reference panels.

Allows users to calculate admixture proportions and perform principal component analysis (PCA) from next generation sequencing (NGS) data of a single individual. The analysis of fastNGSadmix is rested on a set of predefined reference populations and genotype likelihoods of the input sample. This method corrects the biases introduced by small reference populations, and is useful including for low sequencing depth.

Infers global ancestry, population covariances, and constructs population trees using Gaussian models. The Ohana tool suite includes the following innovations: (i) An optimization method for STRUCTURE-style modeling for inferring admixture in a maximum likelihood estimate (MLE) framework. This method is applicable both to called genotypes and to next generation sequencing (NGS) data with uncertainty regarding the true genotypes. The method solves the sequential quadratic programming (QP) problem based on the Active Set algorithm, and tends to find higher maximum likelihood values than ADMIXTURE in similar computational time. (ii) A method for estimating population relationships from ancestry components using a Gaussian approximation. Ohana estimates the best covariance matrix compatible with a tree, thereby estimating a tree, and provides simple algorithms and visualization tools to obtain the evolutionary trees.

Estimates ancestry-specific allele frequencies for bi-allelic markers. We derived an EM algorithm to estimate ancestry-specific allele frequencies given data on a 3-way admixed population. The major advantage of ASAFE over alternative ancestry-specific allele frequency estimation approaches is that ASAFE is applicable to markers in the admixed sample that are absent from a reference panel. Furthermore, ASAFE takes advantage of linkage-disequilibrium based information by using local ancestry calls.

Explores and fits admixture graphs. admixturegraph allows to visualize goodness of fit and to evaluate the relative goodness of fit between different graphs. It can be used for brute-force search on the graph topologies or for a heuristic approach generalizing the sequential one. It allows to make genetic lineages. The tool provides functionality for exploring the space of possible topologies. It computes Bayes factors between graphs for comparing them.

An application for accurately inferring chromosomal segments of distinct ancestry in admixed populations, using dense genetic data.

A method for inferring an individual's ancestry that takes the uncertainty introduced in next generation sequencing data into account. This is achieved by working directly with genotype likelihoods that contain all relevant information of the unobserved genotypes.

Estimates individual ancestry coefficients. sNMF is based on theoretical connections between likelihood approaches, principal component analysis (PCA), and nonnegative matrix factorization (NMF) methods. It was used to compute least-squares estimates of ancestry coefficients for worldwide human population samples and for European populations of the plant species Arabidopsis thaliana. This tool uses an alternating algorithm based on a block principal pivoting method.

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.

Detects possible genetic relationships between individuals while linking genetically related individuals. GAGA is an application which allows users to highlight substructures in a given genetic population. It is based on the diminishment of the within-population variance by exploiting a method leaning on a distance matrix transformation. This program does not require a priori knowledge on studied (sub)populations and can be applied to any type of genetic data.

A tool to objectively analyse the nature of structure revealed in Bayesian ancestry profiles using established statistical methods.

Retrieves Ancestry Informative Markers (AIMs) from genomic data sets. AncestrySNPminer links these informative markers to genes and ontological annotation classes. It includes an automated and simple “scripting at the click of a button” functionality that enables researchers to perform various population genomics statistical analyses methods with user friendly querying and filtering of data sets across various populations through a single web interface.

A statistical method to estimate local ancestry frequencies in admixed populations when ongoing gene flow from source populations is rare or absent, but before genome stabilization is complete. Popanc combines discriminant analysis with a continuous correlated beta process model to jointly estimate local ancestry within individuals and local ancestry frequencies at the population-level. I then assess the accuracy of the method by applying it and a traditional HMM approach to simulated data sets. The reliability and utility of the method is further demonstrated by using it to analyze genetic ancestry in an admixed human population (Uyghur), and three admixed populations from a house mouse hybrid zone.

An efficient and versatile method for estimating the admixture proportions for an individual's ancestry using genotype or sequence data and population allele frequencies from a set of parental/reference populations. The method can work with genotype data or sequence data (aligned sequence reads in a BAM file) derived from low-coverage whole-genome sequencing, exome-sequencing or even targeted sequencing experiments.

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.

Compiles several local ancestry inference softwares. LAIT allows users to preprocess, clean, and format PLINK files for being processed in four ancestry software packages (LAMP, LAMP-LD, HAPMIX, ELAI). The software also has the ability to convert the software’s outputs into a standardized form and, subsequently, to perform comparisons among all supported software.

Assigns ancestry along the genome in admixed individuals. PCAdmix uses phased genotype data, making it valuable for identifying ancestry patterns that were inherited on the same chromosome. It can utilize shorter windows of single-nucleotide polymorphism (SNP) for fine scale ancestry assignment. It also employs a Hidden Markov Model (HMM) to model the ancestry in each window probabilistically. This method is applicable for admixture from two or more populations.

A comprehensive set of computational tools for evolutionary analysis of whole-genome alignments consisting of multiple individuals, from multiple populations or species. POPBAM works directly from BAM-formatted assembly files, calls variant sites, and calculates a variety of commonly used evolutionary sequence statistics. POPBAM is designed primarily to perform analyses in sliding windows across chromosomes or scaffolds. POPBAM accurately measures nucleotide diversity, population divergence, linkage disequilibrium, and the frequency spectrum of mutations from two or more populations. POPBAM can also produce phylogenetic trees of all samples in a BAM file.

Provides a modification of the method diCal for the inference of complex demographic histories. diCal-admix is a model-based method that can be used to efficiently detect tracts of introgressed Neanderthal DNA. It is based on a hidden Markov model (HMM) approach that explicitly accounts for the underlying demographic history relating modern human and Neanderthal populations, including the introgression event.

Assists in modeling admixture and decomposing systematic variation due to population structure. ALStructure is a computationally efficient and statistically accurate method that estimates the low-dimensional linear subspace of the population admixture components. It then searches for a model within this subspace that is consistent with the admixture model’s natural probabilistic constraints. This application was developed as a unification of likelihood-based and PCA-based methods.

Provides a method to predict an individual's ancestry or DNA use. SPAMIX was developed to preview the geographical origins of multiple recent ancestors for individuals with recent mixed ancestry. It leverages the spatial structure of genetic variation, using hidden Markov models (HMMs) for the admixture process to achieve accuracy in localizing the recent ancestry of a given individual on a geographical map.

Allows users to perform haplotype phasing and local ancestry inference (LAI). Loter is a python package that supplies a parameter-free and rapid software without specifications of statistical or biological parameters to allow LAI processing for a wide range of species. The software is not based on a probabilistic formulation and aims to will make more accessible genomic studies about admixture processes.

Optimizes the global minimal genetic distance in a given population. MITOMIX employs the shared haplogroup distance (SHD) method to differentiate closely related and/or admixing populations. It can recognize all traces and the extent of admixture, offering a substitute to whole genome admixture analysis. This tool can be employed to explain the observed mtDNA haplogroup (mt Hg) distributions of any studied population.

Detects ancient ancestry informative markers (aAIMs). PCA-derived-aAIMs underlines the fact that a principal component analysis (PCA)-based method can capture accurately ancient population structure. It provides a framework designed to assess established and novel AIMs-finding methods and can compare performances of AIMs. The aim is to exploit aAIMs to refine ancient population structure models.

Developed on the original ipPCA framework including additional functions that result in improved population assignment accuracy.

Simulates chromosome admixture of various populations.

Provides computationally efficient tools for modeling genetic ancestry based in the SNP information.

Uses continental-specific variants for accurate local ancestry inference. Lanc-CSV is an approach for local ancestry inference in fully sequenced recently admixed individuals. This method makes use of alleles that are found to be present only in individuals from a given continental group (continent-specific variants, CSVs). This approach can reliably infer local ancestry in very large sequenced cohorts at a fraction of the computational cost of existing approaches.

Selects proxy ancestry for recently admixed populations in multi-way admixed populations. PROXYANC 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. It implements two algorithms on population genetic differentiation and optimal quadratic programming.