An overview of STRUCTURE: applications, parameter settings, and supporting software
---
paper_title: The computer program STRUCTURE does not reliably identify the main genetic clusters within species: simulations and implications for human population structure

paper_content:

One of the primary goals of population genetics is to succinctly describe genetic relationships among populations, and the computer program STRUCTURE is one of the most frequently used tools for doing so. The mathematical model used by STRUCTURE was designed to sort individuals into Hardy–Weinberg populations, but the program is also frequently used to group individuals from a large number of populations into a small number of clusters that are supposed to represent the main genetic divisions within species. In this study, I used computer simulations to examine how well STRUCTURE accomplishes this latter task. Simulations of populations that had a simple hierarchical history of fragmentation showed that when there were relatively long divergence times within evolutionary lineages, the clusters created by STRUCTURE were frequently not consistent with the evolutionary history of the populations. These difficulties can be attributed to forcing STRUCTURE to place individuals into too few clusters. Simulations also showed that the clusters produced by STRUCTURE can be strongly influenced by variation in sample size. In some circumstances, STRUCTURE simply put all of the individuals from the largest sample in the same cluster. A reanalysis of human population structure suggests that the problems I identified with STRUCTURE in simulations may have obscured relationships among human populations—particularly genetic similarity between Europeans and some African populations.
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paper_title: Bayesian analysis of genetic differentiation between populations.

paper_content:

We introduce a Bayesian method for estimating hidden population substructure using multilocus molecular markers and geographical information provided by the sampling design. The joint posterior distribution of the substructure and allele frequencies of the respective populations is available in an analytical form when the number of populations is small, whereas an approximation based on a Markov chain Monte Carlo simulation approach can be obtained for a moderate or large number of populations. Using the joint posterior distribution, posteriors can also be derived for any evolutionary population parameters, such as the traditional fixation indices. A major advantage compared to most earlier methods is that the number of populations is treated here as an unknown parameter. What is traditionally considered as two genetically distinct populations, either recently founded or connected by considerable gene flow, is here considered as one panmictic population with a certain probability based on marker data and prior information. Analyses of previously published data on the Moroccan argan tree (Argania spinosa) and of simulated data sets suggest that our method is capable of estimating a population substructure, while not artificially enforcing a substructure when it does not exist. The software (BAPS) used for the computations is freely available from http://www.rni.helsinki.fi/~mjs.
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paper_title: Inference of population structure using multilocus genotype data: dominant markers and null alleles

paper_content:

Dominant markers such as amplified fragment length polymorphisms (AFLPs) provide an economical way of surveying variation at many loci. However, the uncertainty about the underlying genotypes presents a problem for statistical analysis. Similarly, the presence of null alleles and the limitations of genotype calling in polyploids mean that many conventional analysis methods are invalid for many organisms. Here we present a simple approach for accounting for genotypic ambiguity in studies of population structure and apply it to AFLP data from whitefish. The approach is implemented in the program structure version 2.2, which is available from http://pritch.bsd.uchicago.edu/structure.html.
---
paper_title: Human Evolutionary Genetics: Origins, Peoples and Disease.

paper_content:

This is an absolutely superb book! I have been recommending it enthusiastically to professional colleagues, graduate students, and even the occasional highly motivated undergraduate student ever since it was published last year, and the response to the book has been overwhelmingly positive. Not only is the book unique in terms of topical coverage, but it is also extremely well executed. In fact, it is one of the best textbooks on any subject that I have read. It belongs on the shelves of everyone interested in the genetic aspects of human evolution. There is also much of value in it for paleoanthropologists, historical linguists, archaeologists, and human biologists (biological anthropologists), as well as for geneticists with various complementary specialties and interests.
---
paper_title: Inference of population structure using multilocus genotype data.

paper_content:

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
---
paper_title: What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity

paper_content:

We review commonly used population definitions under both the ecological paradigm (which emphasizes demographic cohesion) and the evolutionary paradigm (which emphasizes reproductive cohesion) and find that none are truly operational. We suggest several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered 'populations'. Units for these criteria are migration rate (m) for the ecological paradigm and migrants per generation (Nm) for the evolutionary paradigm. These criteria are then evaluated by applying analytical methods to simulated genetic data for a finite island model. Under the standard parameter set that includes L = 20 High mutation (microsatellite-like) loci and samples of S = 50 individuals from each of n = 4 subpopulations, power to detect departures from panmixia was very high ( approximately 100%; P < 0.001) even with high gene flow (Nm = 25). A new method, comparing the number of correct population assignments with the random expectation, performed as well as a multilocus contingency test and warrants further consideration. Use of Low mutation (allozyme-like) markers reduced power more than did halving S or L. Under the standard parameter set, power to detect restricted gene flow below a certain level X (H(0): Nm < X) can also be high, provided that true Nm < or = 0.5X. Developing the appropriate test criterion, however, requires assumptions about several key parameters that are difficult to estimate in most natural populations. Methods that cluster individuals without using a priori sampling information detected the true number of populations only under conditions of moderate or low gene flow (Nm < or = 5), and power dropped sharply with smaller samples of loci and individuals. A simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations even with Nm = 25 but requires more rigorous statistical evaluation. The ecological paradigm remains challenging for evaluations using genetic markers, because the transition from demographic dependence to independence occurs in a region of high migration where genetic methods have relatively little power. Some recent theoretical developments and continued advances in computational power provide hope that this situation may change in the future.
---
paper_title: Population Structure and Cryptic Relatedness in Genetic Association Studies

paper_content:

We review the problem of confounding in genetic association studies, which arises principally because of population structure and cryptic relatedness. Many treatments of the problem consider only a simple ``island'' model of population structure. We take a broader approach, which views population structure and cryptic relatedness as different aspects of a single confounder: the unobserved pedigree defining the (often distant) relationships among the study subjects. Kinship is therefore a central concept, and we review methods of defining and estimating kinship coefficients, both pedigree-based and marker-based. In this unified framework we review solutions to the problem of population structure, including family-based study designs, genomic control, structured association, regression control, principal components adjustment and linear mixed models. The last solution makes the most explicit use of the kinships among the study subjects, and has an established role in the analysis of animal and plant breeding studies. Recent computational developments mean that analyses of human genetic association data are beginning to benefit from its powerful tests for association, which protect against population structure and cryptic kinship, as well as intermediate levels of confounding by the pedigree.
---
paper_title: Mapping Human Genetic Diversity in Asia

paper_content:

Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.
---
paper_title: Inference of population structure using multilocus genotype data.

paper_content:

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
---
paper_title: Standardized subsets of the HGDPCEPH Human Genome Diversity Cell Line Panel, accounting for atypical and duplicated samples and pairs of close relatives

paper_content:

Summary The HGDP-CEPH Human Genome Diversity Cell Line Panel is a widely-used resource for studies of human genetic variation. Here, pairs of close relatives that have been included in the panel are identified. Together with information on atypical and duplicated samples, the inferred relative pairs suggest standardized subsets of the panel for use in future population-genetic studies.
---
paper_title: Using ancestry-informative markers to define populations and detect population stratification

paper_content:

A serious problem with case-control studies is that population subdivision, recent admixture and sampling variance can lead to spurious associations between a phenotype and a marker locus, or indeed may mask true associations. This is also a concern in therapeutics since drug response may differ by ethnicity. Population stratification can occur if cases and controls have different frequencies of ethnic groups or in admixed populations, different fractions of ancestry, and when phenotypes of interest such as disease, drug response or drug metabolism, also differ between ethnic groups. Although most genetic variation is inter-individual, there is also significant inter-ethnic variation. The International HapMap Project has provided allele frequencies for approximately three million single nucleotide polymorphisms (SNPs) in Africans, Europeans and East Asians. SNP variation is greatest in Africans. Statistical methods for the detection and correction of population stratification, principally Structured Association and Genomic Control, have recently become freely available. These methods use marker loci spread throughout the genome that are unlinked to the candidate locus to estimate the ancestry of individuals within a sample, and to test for and adjust the ethnic matching of cases and controls. To date, few case-control association studies have incorporated testing for population stratification. This paper will focus on the debate about the quantity and methods for selection of highly informative marker loci required to characterize populations that vary in substructure or the degree of admixture, and will discuss how these theoretically desirable approaches can be effectively put into practice.
---
paper_title: Examination of ancestry and ethnic affiliation using highly informative diallelic DNA markers: application to diverse and admixed populations and implications for clinical epidemiology and forensic medicine

paper_content:

We and others have identified several hundred ancestry informative markers (AIMs) with large allele frequency differences between different major ancestral groups. For this study, a panel of 199 widely distributed AIMs was used to examine a diverse set of 796 DNA samples including self-identified European Americans, West Africans, East Asians, Amerindians, African Americans, Mexicans, Mexican Americans, Puerto Ricans and South Asians. Analysis using a Bayesian clustering algorithm (STRUCTURE) showed grouping of individuals with similar ethnic identity without any identifier other than the AIMs genotyping and showed admixture proportions that clearly distinguished different individuals of mixed ancestry. Additional analyses showed that, for the majority of samples, the predicted ethnic identity corresponded with the self-identified ethnicity at high probability (P > 0.99). Overall, the study demonstrates that AIMs can provide a useful adjunct to forensic medicine, pharmacogenomics and disease studies in which major ancestry or ethnic affiliation might be linked to specific outcomes.
---
paper_title: Inferring Genetic Ancestry: Opportunities, Challenges, and Implications

paper_content:

Increasing public interest in direct-to-consumer (DTC) genetic ancestry testing has been accompanied by growing concern about issues ranging from the personal and societal implications of the testing to the scientific validity of ancestry inference. The very concept of “ancestry” is subject to misunderstanding in both the general and scientific communities. What do we mean by ancestry? How exactly is ancestry measured? How far back can such ancestry be defined and by which genetic tools? How do we validate inferences about ancestry in genetic research? What are the data that demonstrate our ability to do this correctly? What can we say and what can we not say from our research findings and the test results that we generate? This white paper from the American Society of Human Genetics (ASHG) Ancestry and Ancestry Testing Task Force builds upon the 2008 ASHG Ancestry Testing Summary Statement in providing a more in-depth analysis of key scientific and non-scientific aspects of genetic ancestry inference in academia and industry. It culminates with recommendations for advancing the current debate and facilitating the development of scientifically based, ethically sound, and socially attentive guidelines concerning the use of these continually evolving technologies.
---
paper_title: A panel of ancestry informative markers for estimating individual biogeographical ancestry and admixture from four continents: utility and applications

paper_content:

Autosomal ancestry informative markers (AIMs) are useful for inferring individual biogeographical ancestry (I-BGA) and admixture. Ancestry estimates obtained from Y and mtDNA are useful for reconstructing population expansions and migrations in our recent past but individual genomic admixture estimates are useful to test for association of admixture with phenotypes, as covariate in association studies to control for stratification and, in forensics, to estimate certain overt phenotypes from ancestry. We have developed a panel of 176 autosomal AIMs that can effectively distinguish I-BGA and admixture proportions from four continental ancestral populations: Europeans, West Africans, Indigenous Americans, and East Asians. We present allele frequencies for these AIMs in all four ancestral populations and use them to assess the global apportionment of I-BGA and admixture diversity among some extant populations. We observed patterns of apportionment similar to those described previously using sex and autosomal markers, such as European admixture for African Americans (14.3%) and Mexicans (43.2%), European (65.5%) and East Asian affiliation (27%) for South Asians, and low levels of African admixture (2.8-10.8%) mirroring the distribution of Y E3b haplogroups among various Eurasian populations. Using simulation studies and pedigree analysis we show that I-BGA estimates obtained using this panel and a four-population model has a high degree of precision (average root mean square error [RMSE]=0.026). Using ancestry-phenotype associations we demonstrate that a large and informative AIM panel such as this can help reduce false-positive and false-negative associations between phenotypes and admixture proportions, which may result when using a smaller panel of less informative AIMs.
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paper_title: Information on ancestry from genetic markers.

paper_content:

It is possible to estimate the proportionate contributions of ancestral populations to admixed individuals or populations using genetic markers, but different loci and alleles vary considerably in the amount of information that they provide. Conventionally, the allele frequency difference between parental populations (delta) has been used as the criterion to select informative markers. However, it is unclear how to use delta for multiallelic loci, or populations formed by the mixture of more than two groups. Moreover, several other factors, including the actual ancestral proportions and the relative genetic diversities of the parental populations, affect the information provided by genetic markers. We demonstrate here that using delta as the sole criterion for marker selection is inadequate, and we propose, instead, to use Fisher's information, which is the inverse of the variance of the estimated ancestral contributions. This measure is superior because it is directly related to the precision of ancestry estimates. Although delta is related to Fisher's information, the relationship is neither linear nor simple, and the information can vary widely for markers with identical deltas. Fortunately, Fisher's information is easily computed and formally extends to the situation of multiple alleles and/or parental populations. We examined the distribution of information for SNP and microsatellite loci available in the public domain for a variety of model admixed populations. The information, on average, is higher for microsatellite loci, but exceptional SNPs exceed the best microsatellites. Despite the large number of genetic markers that have been identified for admixture analysis, it appears that information for estimating admixture proportions is limited, and estimates will typically have wide confidence intervals.
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paper_title: Inferring ancestral origin using a single multiplex assay of ancestry-informative marker SNPs.

paper_content:

Tests that infer the ancestral origin of a DNA sample have considerable potential in the development of forensic tools that can help to guide crime investigation. We have developed a single-tube 34-plex SNP assay for the assignment of ancestral origin by choosing ancestry-informative markers (AIMs) exhibiting highly contrasting allele frequency distributions between the three major population-groups. To predict ancestral origin from the profiles obtained, a classification algorithm was developed based on maximum likelihood. Sampling of two populations each from African, European and East Asian groups provided training sets for the algorithm and this was tested using the CEPH Human Genome Diversity Panel. We detected negligible theoretical and practical error for assignments to one of the three groups analyzed with consistently high classification probabilities, even when using reduced subsets of SNPs. This study shows that by choosing SNPs exhibiting marked allele frequency differences between population-groups a practical forensic test for assigning the most likely ancestry can be achieved from a single multiplexed assay.
---
paper_title: Inference of population structure using multilocus genotype data.

paper_content:

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
---
paper_title: Using ancestry-informative markers to define populations and detect population stratification

paper_content:

A serious problem with case-control studies is that population subdivision, recent admixture and sampling variance can lead to spurious associations between a phenotype and a marker locus, or indeed may mask true associations. This is also a concern in therapeutics since drug response may differ by ethnicity. Population stratification can occur if cases and controls have different frequencies of ethnic groups or in admixed populations, different fractions of ancestry, and when phenotypes of interest such as disease, drug response or drug metabolism, also differ between ethnic groups. Although most genetic variation is inter-individual, there is also significant inter-ethnic variation. The International HapMap Project has provided allele frequencies for approximately three million single nucleotide polymorphisms (SNPs) in Africans, Europeans and East Asians. SNP variation is greatest in Africans. Statistical methods for the detection and correction of population stratification, principally Structured Association and Genomic Control, have recently become freely available. These methods use marker loci spread throughout the genome that are unlinked to the candidate locus to estimate the ancestry of individuals within a sample, and to test for and adjust the ethnic matching of cases and controls. To date, few case-control association studies have incorporated testing for population stratification. This paper will focus on the debate about the quantity and methods for selection of highly informative marker loci required to characterize populations that vary in substructure or the degree of admixture, and will discuss how these theoretically desirable approaches can be effectively put into practice.
---
paper_title: Examination of ancestry and ethnic affiliation using highly informative diallelic DNA markers: application to diverse and admixed populations and implications for clinical epidemiology and forensic medicine

paper_content:

We and others have identified several hundred ancestry informative markers (AIMs) with large allele frequency differences between different major ancestral groups. For this study, a panel of 199 widely distributed AIMs was used to examine a diverse set of 796 DNA samples including self-identified European Americans, West Africans, East Asians, Amerindians, African Americans, Mexicans, Mexican Americans, Puerto Ricans and South Asians. Analysis using a Bayesian clustering algorithm (STRUCTURE) showed grouping of individuals with similar ethnic identity without any identifier other than the AIMs genotyping and showed admixture proportions that clearly distinguished different individuals of mixed ancestry. Additional analyses showed that, for the majority of samples, the predicted ethnic identity corresponded with the self-identified ethnicity at high probability (P > 0.99). Overall, the study demonstrates that AIMs can provide a useful adjunct to forensic medicine, pharmacogenomics and disease studies in which major ancestry or ethnic affiliation might be linked to specific outcomes.
---
paper_title: Inferring Genetic Ancestry: Opportunities, Challenges, and Implications

paper_content:

Increasing public interest in direct-to-consumer (DTC) genetic ancestry testing has been accompanied by growing concern about issues ranging from the personal and societal implications of the testing to the scientific validity of ancestry inference. The very concept of “ancestry” is subject to misunderstanding in both the general and scientific communities. What do we mean by ancestry? How exactly is ancestry measured? How far back can such ancestry be defined and by which genetic tools? How do we validate inferences about ancestry in genetic research? What are the data that demonstrate our ability to do this correctly? What can we say and what can we not say from our research findings and the test results that we generate? This white paper from the American Society of Human Genetics (ASHG) Ancestry and Ancestry Testing Task Force builds upon the 2008 ASHG Ancestry Testing Summary Statement in providing a more in-depth analysis of key scientific and non-scientific aspects of genetic ancestry inference in academia and industry. It culminates with recommendations for advancing the current debate and facilitating the development of scientifically based, ethically sound, and socially attentive guidelines concerning the use of these continually evolving technologies.
---
paper_title: SPSmart: adapting population based SNP genotype databases for fast and comprehensive web access

paper_content:

BackgroundIn the last five years large online resources of human variability have appeared, notably HapMap, Perlegen and the CEPH foundation. These databases of genotypes with population information act as catalogues of human diversity, and are widely used as reference sources for population genetics studies. Although many useful conclusions may be extracted by querying databases individually, the lack of flexibility for combining data from within and between each database does not allow the calculation of key population variability statistics.ResultsWe have developed a novel tool for accessing and combining large-scale genomic databases of single nucleotide polymorphisms (SNPs) in widespread use in human population genetics: SPSmart (SNPs for Population Studies). A fast pipeline creates and maintains a data mart from the most commonly accessed databases of genotypes containing population information: data is mined, summarized into the standard statistical reference indices, and stored into a relational database that currently handles as many as 4 × 109 genotypes and that can be easily extended to new database initiatives. We have also built a web interface to the data mart that allows the browsing of underlying data indexed by population and the combining of populations, allowing intuitive and straightforward comparison of population groups. All the information served is optimized for web display, and most of the computations are already pre-processed in the data mart to speed up the data browsing and any computational treatment requested.ConclusionIn practice, SPSmart allows populations to be combined into user-defined groups, while multiple databases can be accessed and compared in a few simple steps from a single query. It performs the queries rapidly and gives straightforward graphical summaries of SNP population variability through visual inspection of allele frequencies outlined in standard pie-chart format. In addition, full numerical description of the data is output in statistical results panels that include common population genetics metrics such as heterozygosity, Fst and In.
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paper_title: Geography and genography: prediction of continental origin using randomly selected single nucleotide polymorphisms

paper_content:

Recent studies have shown that when individuals are grouped on the basis of genetic similarity, group membership corresponds closely to continental origin. There has been considerable debate about the implications of these findings in the context of larger debates about race and the extent of genetic variation between groups. Some have argued that clustering according to continental origin demonstrates the existence of significant genetic differences between groups and that these differences may have important implications for differences in health and disease. Others argue that clustering according to continental origin requires the use of large amounts of genetic data or specifically chosen markers and is indicative only of very subtle genetic differences that are unlikely to have biomedical significance. We used small numbers of randomly selected single nucleotide polymorphisms (SNPs) from the International HapMap Project to train naïve Bayes classifiers for prediction of ancestral continent of origin. Predictive accuracy was tested on two independent data sets. Genetically similar groups should be difficult to distinguish, especially if only a small number of genetic markers are used. The genetic differences between continentally defined groups are sufficiently large that one can accurately predict ancestral continent of origin using only a minute, randomly selected fraction of the genetic variation present in the human genome. Genotype data from only 50 random SNPs was sufficient to predict ancestral continent of origin in our primary test data set with an average accuracy of 95%. Genetic variations informative about ancestry were common and widely distributed throughout the genome. Accurate characterization of ancestry is possible using small numbers of randomly selected SNPs. The results presented here show how investigators conducting genetic association studies can use small numbers of arbitrarily chosen SNPs to identify stratification in study subjects and avoid false positive genotype-phenotype associations. Our findings also demonstrate the extent of variation between continentally defined groups and argue strongly against the contention that genetic differences between groups are too small to have biomedical significance.
---
paper_title: Mapping Human Genetic Diversity in Asia

paper_content:

Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.
---
paper_title: Human Evolutionary Genetics: Origins, Peoples and Disease.

paper_content:

This is an absolutely superb book! I have been recommending it enthusiastically to professional colleagues, graduate students, and even the occasional highly motivated undergraduate student ever since it was published last year, and the response to the book has been overwhelmingly positive. Not only is the book unique in terms of topical coverage, but it is also extremely well executed. In fact, it is one of the best textbooks on any subject that I have read. It belongs on the shelves of everyone interested in the genetic aspects of human evolution. There is also much of value in it for paleoanthropologists, historical linguists, archaeologists, and human biologists (biological anthropologists), as well as for geneticists with various complementary specialties and interests.
---
paper_title: Inference of population structure using multilocus genotype data.

paper_content:

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
---
paper_title: Worldwide human relationships inferred from genome-wide patterns of variation.

paper_content:

Human genetic diversity is shaped by both demographic and biological factors and has fundamental implications for understanding the genetic basis of diseases. We studied 938 unrelated individuals from 51 populations of the Human Genome Diversity Panel at 650,000 common single-nucleotide polymorphism loci. Individual ancestry and population substructure were detectable with very high resolution. The relationship between haplotype heterozygosity and geography was consistent with the hypothesis of a serial founder effect with a single origin in sub-Saharan Africa. In addition, we observed a pattern of ancestral allele frequency distributions that reflects variation in population dynamics among geographic regions. This data set allows the most comprehensive characterization to date of human genetic variation.
---
paper_title: Using ancestry-informative markers to define populations and detect population stratification

paper_content:

A serious problem with case-control studies is that population subdivision, recent admixture and sampling variance can lead to spurious associations between a phenotype and a marker locus, or indeed may mask true associations. This is also a concern in therapeutics since drug response may differ by ethnicity. Population stratification can occur if cases and controls have different frequencies of ethnic groups or in admixed populations, different fractions of ancestry, and when phenotypes of interest such as disease, drug response or drug metabolism, also differ between ethnic groups. Although most genetic variation is inter-individual, there is also significant inter-ethnic variation. The International HapMap Project has provided allele frequencies for approximately three million single nucleotide polymorphisms (SNPs) in Africans, Europeans and East Asians. SNP variation is greatest in Africans. Statistical methods for the detection and correction of population stratification, principally Structured Association and Genomic Control, have recently become freely available. These methods use marker loci spread throughout the genome that are unlinked to the candidate locus to estimate the ancestry of individuals within a sample, and to test for and adjust the ethnic matching of cases and controls. To date, few case-control association studies have incorporated testing for population stratification. This paper will focus on the debate about the quantity and methods for selection of highly informative marker loci required to characterize populations that vary in substructure or the degree of admixture, and will discuss how these theoretically desirable approaches can be effectively put into practice.
---
paper_title: Population Structure and Cryptic Relatedness in Genetic Association Studies

paper_content:

We review the problem of confounding in genetic association studies, which arises principally because of population structure and cryptic relatedness. Many treatments of the problem consider only a simple ``island'' model of population structure. We take a broader approach, which views population structure and cryptic relatedness as different aspects of a single confounder: the unobserved pedigree defining the (often distant) relationships among the study subjects. Kinship is therefore a central concept, and we review methods of defining and estimating kinship coefficients, both pedigree-based and marker-based. In this unified framework we review solutions to the problem of population structure, including family-based study designs, genomic control, structured association, regression control, principal components adjustment and linear mixed models. The last solution makes the most explicit use of the kinships among the study subjects, and has an established role in the analysis of animal and plant breeding studies. Recent computational developments mean that analyses of human genetic association data are beginning to benefit from its powerful tests for association, which protect against population structure and cryptic kinship, as well as intermediate levels of confounding by the pedigree.
---
paper_title: Logistic regression protects against population structure in genetic association studies.

paper_content:

We conduct an extensive simulation study to compare the merits of several methods for using null (unlinked) markers to protect against false positives due to cryptic substructure in population-based genetic association studies. The more sophisticated "structured association" methods perform well but are computationally demanding and rely on estimating the correct number of subpopulations. The simple and fast "genomic control" approach can lose power in certain scenarios. We find that procedures based on logistic regression that are flexible, computationally fast, and easy to implement also provide good protection against the effects of cryptic substructure, even though they do not explicitly model the population structure.
---
paper_title: Osteopontin and Systemic Lupus Erythematosus Association: A Probable Gene-Gender Interaction

paper_content:

Osteopontin (SPP1) is an important bone matrix mediator found to have key roles in inflammation and immunity. SPP1 genetic polymorphisms and increased osteopontin protein levels have been reported to be associated with SLE in small patient collections. The present study evaluates association between SPP1 polymorphisms and SLE in a large cohort of 1141 unrelated SLE patients [707 European-American (EA) and 434 African-American (AA)], and 2009 unrelated controls (1309 EA and 700 AA). Population-based case-control association analyses were performed. To control for potential population stratification, admixture adjusted logistic regression, genomic control (GC), structured association (STRAT), and principal components analysis (PCA) were applied. Combined analysis of 2 ethnic groups, showed the minor allele of 2 SNPs (rs1126616T and rs9138C) significantly associated with higher risk of SLE in males (P = 0.0005, OR = 1.73, 95% CI = 1.28-2.33), but not in females. Indeed, significant gene-gender interactions in the 2 SNPs, rs1126772 and rs9138, were detected (P = 0.001 and P = 0.0006, respectively). Further, haplotype analysis identified rs1126616T-rs1126772A-rs9138C which demonstrated significant association with SLE in general (P = 0.02, OR = 1.30, 95%CI 1.08-1.57), especially in males (P = 0.0003, OR = 2.42, 95%CI 1.51-3.89). Subgroup analysis with single SNPs and haplotypes also identified a similar pattern of gender-specific association in AA and EA. GC, STRAT, and PCA results within each group showed consistent associations. Our data suggest SPP1 is associated with SLE, and this association is especially stronger in males. To our knowledge, this report serves as the first association of a specific autosomal gene with human male lupus.
---
paper_title: Rare and Low Frequency Variant Stratification in the UK Population: Description and Impact on Association Tests

paper_content:

Although variations in allele frequencies at common SNPs have been extensively studied in different populations, little is known about the stratification of rare variants and its impact on association tests. In this paper, we used Affymetrix 500K genotype data from the WTCCC to investigate if variants in three different frequency categories (below 1%, between 1 and 5%, above 5%) show different stratification patterns in the UK population. We found that these patterns are indeed different. The top principal component extracted from the rare variant category shows poor correlations with any principal component or combination of principal components from the low frequency or common variant categories. These results could suggest that a suitable solution to avoid false positive association due to population stratification would involve adjusting for the respective PCs when testing for variants in different allele frequency categories. However, we found this was not the case both on type 2 diabetes data and on simulated data. Indeed, adjusting rare variant association tests on PCs derived from rare variants does no better to correct for population stratification than adjusting on PCs derived from more common variants. Mixed models perform slightly better for low frequency variants than PC based adjustments but less well for the rarest variants. These results call for the need of new methodological developments specifically devoted to address rare variant stratification issues in association tests.
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paper_title: Discerning the Ancestry of European Americans in Genetic Association Studies

paper_content:

European Americans are often treated as a homogeneous group, but in fact form a structured population due to historical immigration of diverse source populations. Discerning the ancestry of European Americans genotyped in association studies is important in order to prevent false-positive or false-negative associations due to population stratification and to identify genetic variants whose contribution to disease risk differs across European ancestries. Here, we investigate empirical patterns of population structure in European Americans, analyzing 4,198 samples from four genome-wide association studies to show that components roughly corresponding to northwest European, southeast European, and Ashkenazi Jewish ancestry are the main sources of European American population structure. Building on this insight, we constructed a panel of 300 validated markers that are highly informative for distinguishing these ancestries. We demonstrate that this panel of markers can be used to correct for stratification in association studies that do not generate dense genotype data.
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paper_title: Demonstrating stratification in a European American population

paper_content:

Population stratification occurs in case-control association studies when allele frequencies differ between cases and controls because of ancestry. Stratification may lead to false positive associations, although this issue remains controversial. Empirical studies have found little evidence of stratification in European-derived populations, but potentially significant levels of stratification could not be ruled out. We studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. But a SNP in the gene LCT that varies widely in frequency across Europe was strongly associated with height (P < 10(-6)). This apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. The failure of standard methods to detect this stratification indicates that new methods may be required.
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paper_title: Association mapping in structured populations

paper_content:

The use, in association studies, of the forthcoming dense genomewide collection of single-nucleotide polymorphisms (SNPs) has been heralded as a potential breakthrough in the study of the genetic basis of common complex disorders. A serious problem with association mapping is that population structure can lead to spurious associations between a candidate marker and a phenotype. One common solution has been to abandon case-control studies in favor of family-based tests of association, such as the transmission/disequilibrium test (TDT), but this comes at a considerable cost in the need to collect DNA from close relatives of affected individuals. In this article we describe a novel, statistically valid, method for case-control association studies in structured populations. Our method uses a set of unlinked genetic markers to infer details of population structure, and to estimate the ancestry of sampled individuals, before using this information to test for associations within subpopulations. It provides power comparable with the TDT in many settings and may substantially outperform it if there are conflicting associations in different subpopulations.
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paper_title: Confounding from Cryptic Relatedness in Case-Control Association Studies

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Case-control association studies are widely used in the search for genetic variants that contribute to human diseases. It has long been known that such studies may suffer from high rates of false positives if there is unrecognized population structure. It is perhaps less widely appreciated that so-called "cryptic relatedness" (i.e., kinship among the cases or controls that is not known to the investigator) might also potentially inflate the false positive rate. Until now there has been little work to assess how serious this problem is likely to be in practice. In this paper, we develop a formal model of cryptic relatedness, and study its impact on association studies. We provide simple expressions that predict the extent of confounding due to cryptic relatedness. Surprisingly, these expressions are functions of directly observable parameters. Our analytical results show that, for well-designed studies in outbred populations, the degree of confounding due to cryptic relatedness will usually be negligible. However, in contrast, studies where there is a sampling bias toward collecting relatives may indeed suffer from excessive rates of false positives. Furthermore, cryptic relatedness may be a serious concern in founder populations that have grown rapidly and recently from a small size. As an example, we analyze the impact of excess relatedness among cases for six phenotypes measured in the Hutterite population.
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paper_title: Inference of population structure using multilocus genotype data.

paper_content:

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
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paper_title: Robustness of Bayesian multilocus association models to cryptic relatedness.

paper_content:

Population-based association analyses are more powerful than within-family analyses in identifying genetic loci associated with a phenotype of interest. However, if the population or sample structure is omitted from the model, population stratification and cryptic relatedness may lead to false positive and negative signals caused by relatedness between individuals, rather than association due to close linkage of the marker and the trait loci. Therefore it is important to correct or account for these confounders in population-based association analyses. However, there is cumulative evidence that when fitting a multilocus association model, the genetic relationships between the individuals can be captured by the markers themselves, bringing about a possibility to use the models without an additional correction for the population or sample structure. In this work we have further investigated this possibility in the Bayesian multilocus association model context using the extended Bayesian LASSO and the indicator-based variable selection. In particular, we have studied whether these multilocus models benefit from an insertion of an additional polygenic term representing the genetic variation not captured by the markers and taking account of the residual dependencies between the individuals. We have found that although the models may benefit from the insertion of the polygenic component, omitting the component does not damage the model performance severely.
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paper_title: Analysis and Application of European Genetic Substructure Using 300 K SNP Information

paper_content:

European population genetic substructure was examined in a diverse set of >1,000 individuals of European descent, each genotyped with >300 K SNPs. Both STRUCTURE and principal component analyses (PCA) showed the largest division/principal component (PC) differentiated northern from southern European ancestry. A second PC further separated Italian, Spanish, and Greek individuals from those of Ashkenazi Jewish ancestry as well as distinguishing among northern European populations. In separate analyses of northern European participants other substructure relationships were discerned showing a west to east gradient. Application of this substructure information was critical in examining a real dataset in whole genome association (WGA) analyses for rheumatoid arthritis in European Americans to reduce false positive signals. In addition, two sets of European substructure ancestry informative markers (ESAIMs) were identified that provide substantial substructure information. The results provide further insight into European population genetic substructure and show that this information can be used for improving error rates in association testing of candidate genes and in replication studies of WGA scans.
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paper_title: Differential confounding of rare and common variants in spatially structured populations

paper_content:

Gil McVean and Iain Mathieson report an analysis of the differential effects of population stratification on rare and common variants within association studies. They find that rare variants may show stronger stratification in some situations and that this is not corrected for by current structure methods, suggesting the need for the development of new statistical methods.
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paper_title: New approaches to population stratification in genome-wide association studies

paper_content:

Genome-wide association (GWA) studies are an effective approach for identifying genetic variants associated with disease risk. GWA studies can be confounded by population stratification--systematic ancestry differences between cases and controls--which has previously been addressed by methods that infer genetic ancestry. Those methods perform well in data sets in which population structure is the only kind of structure present but are inadequate in data sets that also contain family structure or cryptic relatedness. Here, we review recent progress on methods that correct for stratification while accounting for these additional complexities.
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paper_title: CoAIMs: A Cost-Effective Panel of Ancestry Informative Markers for Determining Continental Origins

paper_content:

BACKGROUND ::: Genetic ancestry is known to impact outcomes of genotype-phenotype studies that are designed to identify risk for common diseases in human populations. Failure to control for population stratification due to genetic ancestry can significantly confound results of disease association studies. Moreover, ancestry is a critical factor in assessing lifetime risk of disease, and can play an important role in optimizing treatment. As modern medicine moves towards using personal genetic information for clinical applications, it is important to determine genetic ancestry in an accurate, cost-effective and efficient manner. Self-identified race is a common method used to track and control for population stratification; however, social constructs of race are not necessarily informative for genetic applications. The use of ancestry informative markers (AIMs) is a more accurate method for determining genetic ancestry for the purposes of population stratification. ::: ::: ::: METHODOLOGY/PRINCIPAL FINDINGS ::: Here we introduce a novel panel of 36 microsatellite (MSAT) AIMs that determines continental admixture proportions. This panel, which we have named Continental Ancestry Informative Markers or CoAIMs, consists of MSAT AIMs that were chosen based upon their measure of genetic variance (F(st)), allele frequencies and their suitability for efficient genotyping. Genotype analysis using CoAIMs along with a Bayesian clustering method (STRUCTURE) is able to discern continental origins including Europe/Middle East (Caucasians), East Asia, Africa, Native America, and Oceania. In addition to determining continental ancestry for individuals without significant admixture, we applied CoAIMs to ascertain admixture proportions of individuals of self declared race. ::: ::: ::: CONCLUSION/SIGNIFICANCE ::: CoAIMs can be used to efficiently and effectively determine continental admixture proportions in a sample set. The CoAIMs panel is a valuable resource for genetic researchers performing case-control genetic association studies, as it can control for the confounding effects of population stratification. The MSAT-based approach used here has potential for broad applicability as a cost effective tool toward determining admixture proportions.
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paper_title: The HIrisPlex system for simultaneous prediction of hair and eye colour from DNA

paper_content:

Recently, the field of predicting phenotypes of externally visible characteristics (EVCs) from DNA genotypes with the final aim of concentrating police investigations to find persons completely unknown to investigating authorities, also referred to as Forensic DNA Phenotyping (FDP), has started to become established in forensic biology. We previously developed and forensically validated the IrisPlex system for accurate prediction of blue and brown eye colour from DNA, and recently showed that all major hair colour categories are predictable from carefully selected DNA markers. Here, we introduce the newly developed HIrisPlex system, which is capable of simultaneously predicting both hair and eye colour from DNA. HIrisPlex consists of a single multiplex assay targeting 24 eye and hair colour predictive DNA variants including all 6 IrisPlex SNPs, as well as two prediction models, a newly developed model for hair colour categories and shade, and the previously developed IrisPlex model for eye colour. The HIrisPlex assay was designed to cope with low amounts of template DNA, as well as degraded DNA, and preliminary sensitivity testing revealed full DNA profiles down to 63 pg input DNA. The power of the HIrisPlex system to predict hair colour was assessed in 1551 individuals from three different parts of Europe showing different hair colour frequencies. Using a 20% subset of individuals, while 80% were used for model building, the individual-based prediction accuracies employing a prediction-guided approach were 69.5% for blond, 78.5% for brown, 80% for red and 87.5% for black hair colour on average. Results from HIrisPlex analysis on worldwide DNA samples imply that HIrisPlex hair colour prediction is reliable independent of bio-geographic ancestry (similar to previous IrisPlex findings for eye colour). We furthermore demonstrate that it is possible to infer with a prediction accuracy of >86% if a brown-eyed, black-haired individual is of non-European (excluding regions nearby Europe) versus European (including nearby regions) bio-geographic origin solely from the strength of HIrisPlex eye and hair colour probabilities, which can provide extra intelligence for future forensic applications. The HIrisPlex system introduced here, including a single multiplex test assay, an interactive tool and prediction guide, and recommendations for reporting final outcomes, represents the first tool for simultaneously establishing categorical eye and hair colour of a person from DNA. The practical forensic application of the HIrisPlex system is expected to benefit cases where other avenues of investigation, including STR profiling, provide no leads on who the unknown crime scene sample donor or the unknown missing person might be.
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paper_title: Ancestry Analysis in the 11-M Madrid Bomb Attack Investigation

paper_content:

The 11-M Madrid commuter train bombings of 2004 constituted the second biggest terrorist attack to occur in Europe after Lockerbie, while the subsequent investigation became the most complex and wide-ranging forensic case in Spain. Standard short tandem repeat (STR) profiling of 600 exhibits left certain key incriminatory samples unmatched to any of the apprehended suspects. A judicial order to perform analyses of unmatched samples to differentiate European and North African ancestry became a critical part of the investigation and was instigated to help refine the search for further suspects. Although mitochondrial DNA (mtDNA) and Y-chromosome markers routinely demonstrate informative geographic differentiation, the populations compared in this analysis were known to show a proportion of shared mtDNA and Y haplotypes as a result of recent gene-flow across the western Mediterranean, while any two loci can be unrepresentative of the ancestry of an individual as a whole. We based our principal analysis on a validated 34plex autosomal ancestry-informative-marker single nucleotide polymorphism (AIM-SNP) assay to make an assignment of ancestry for DNA from seven unmatched case samples including a handprint from a bag containing undetonated explosives together with personal items recovered from various locations in Madrid associated with the suspects. To assess marker informativeness before genotyping, we predicted the probable classification success for the 34plex assay with standard error estimators for a naïve Bayesian classifier using Moroccan and Spanish training sets (each n = 48). Once misclassification error was found to be sufficiently low, genotyping yielded seven near-complete profiles (33 of 34 AIM-SNPs) that in four cases gave probabilities providing a clear assignment of ancestry. One of the suspects predicted to be North African by AIM-SNP analysis of DNA from a toothbrush was identified late in the investigation as Algerian in origin. The results achieved illustrate the benefit of adding specialized marker sets to provide enhanced scope and power to an already highly effective system of DNA analysis for forensic identification.
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paper_title: Analysis of global variability in 15 established and 5 new European Standard Set (ESS) STRs using the CEPH human genome diversity panel.

paper_content:

The CEPH human genome diversity cell line panel (CEPH-HGDP) of 51 globally distributed populations was used to analyze patterns of variability in 20 core human identification STRs. The markers typed comprised the 15 STRs of Identifiler, one of the most widely used forensic STR multiplexes, plus five recently introduced European Standard Set (ESS) STRs: D1S1656, D2S441, D10S1248, D12S391 and D22S1045. From the genotypes obtained for the ESS STRs we identified rare, intermediate or off-ladder alleles that had not been previously reported for these loci. Examples of novel ESS STR alleles found were characterized by sequence analysis. This revealed extensive repeat structure variation in three ESS STRs, with D12S391 showing particularly high variability for tandem runs of AGAT and AGAC repeat units. The global geographic distribution of the CEPH panel samples gave an opportunity to study in detail the extent of substructure shown by the 20 STRs amongst populations and between their parent population groups. An assessment was made of the forensic informativeness of the new ESS STRs compared to the loci they will replace: CSF1PO, D5S818, D7S820, D13S317 and TPOX, with results showing a clear enhancement of discrimination power using multiplexes that genotype the new ESS loci. We also measured the ability of Identifiler and ESS STRs to infer the ancestry of the CEPH-HGDP samples and demonstrate that forensic STRs in large multiplexes have the potential to differentiate the major population groups but only with sufficient reliability when used with other ancestry-informative markers such as single nucleotide polymorphisms. Finally we checked for possible association by linkage between the two ESS multiplex STRs closely positioned on chromosome-12: vWA and D12S391 by examining paired genotypes from the complete CEPH data set.
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paper_title: Inferring ancestral origin using a single multiplex assay of ancestry-informative marker SNPs.

paper_content:

Tests that infer the ancestral origin of a DNA sample have considerable potential in the development of forensic tools that can help to guide crime investigation. We have developed a single-tube 34-plex SNP assay for the assignment of ancestral origin by choosing ancestry-informative markers (AIMs) exhibiting highly contrasting allele frequency distributions between the three major population-groups. To predict ancestral origin from the profiles obtained, a classification algorithm was developed based on maximum likelihood. Sampling of two populations each from African, European and East Asian groups provided training sets for the algorithm and this was tested using the CEPH Human Genome Diversity Panel. We detected negligible theoretical and practical error for assignments to one of the three groups analyzed with consistently high classification probabilities, even when using reduced subsets of SNPs. This study shows that by choosing SNPs exhibiting marked allele frequency differences between population-groups a practical forensic test for assigning the most likely ancestry can be achieved from a single multiplexed assay.
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paper_title: Inferring ethnic origin by means of an STR profile

paper_content:

We report the use of DNA profiles from six STR loci for inferring the ethnic origin of a crime stain and discuss how such inference may be used as intelligence information to reduce the expected number of interviews to resolve a case. To enable this work, databases have been created for five British ethnic groups (Caucasians, Afro-Caribbeans, Indian sub-continentals, Southeast Asians and Middle Easterners) that together comprise 99.7% of the UK population.
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paper_title: Inferring ethnicity using 15 autosomal STR loci—Comparisons among populations of similar and distinctly different physical traits

paper_content:

Abstract The forensic utility of short tandem repeat (STR) polymorphisms for ethnic inference (EI) has recently received limited attention from the research community. The large volume of population specific STR data available from public literature affords us the opportunity to assess the reliability of EIs based on STR profiles, and present significant results. We applied a binary Bayesian approach using 15 autosomal STR loci from computer-simulated and real STR profiles of Han Chinese, Japanese, Korean, American Caucasian, and a South Asian Indian aboriginal tribal group called Lodha. A correct classification rate of ≥90% was achieved via simulation for each East Asian group (Han Chinese, Japanese, and Korean) when paired with the American Caucasian or the tribal Indian group. Similar result was obtained between the Caucasian and the Indian group, while the correct classification rates among the three East Asian groups were much lower (∼70%). Results based on real profiles closely matched those achieved via simulation, establishing the credibility of our classifier performance metrics. This study shows that binary Bayesian classifier performed best for ethnic groups with distinctly different physical traits. This observation might be due to accidental differences caused by bottlenecks, genetic drift, etc. However, it could also be taken as an indication that STRs, commonly referred to as “junk” DNA, may have an effect on phenotype, a possibility that warrants further research.
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paper_title: The utility of short tandem repeat loci beyond human identification: Implications for development of new DNA typing systems

paper_content:

Since the first characterization of the population genetic properties of repeat polymorphisms, the number of short tandem repeat (STR) loci validated for forensic use has now grown to at least 13. Worldwide variations of allele frequencies at these loci have been studied, showing that variations of interpopulation diversity at these loci do not compromise the power of identification of individuals. However, data collected for validation of these loci for forensic use has utility beyond human identification; the origin and past migration history of modern humans can be reconstructed from worldwide variations at these loci. Furthermore, complex forensic cases previously unresolvable can now be investigated with the help of the validated STR loci. Here, we provide the absolute power of the validated set of 13 STR loci for addressing these issues using multilocus genotype data on 1,401 individuals belonging to seven populations (US European-American, US African-American, Jamaican, Italian, Swiss, Chinese and Apache Native-American). Genomic research is discovering new classes of polymorphic loci (such as the single nucleotide polymorphisms, SNPs) and lineage markers (such as the mitochondrial DNA and Y-chromosome markers); our aim, therefore, was to determine how many SNP loci are needed to match the power of this set of 13 STR loci. We conclude that the current set of STR loci is adequate for addressing most problems of human identification (including interpretations of DNA mixtures). However, if suitable number of SNPs are used that would match the power of the STR loci, they alone cannot resolve more complex cases unless they are supplemented by the validated STR loci.
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paper_title: Further development of forensic eye color predictive tests.

paper_content:

In forensic analysis predictive tests for external visible characteristics (or EVCs), including inference of iris color, represent a potentially useful tool to guide criminal investigations. Two recent studies, both focused on forensic testing, have analyzed single nucleotide polymorphism (SNP) genotypes underlying common eye color variation (Mengel-From et al., Forensic Sci. Int. Genet. 4:323 and Walsh et al., Forensic Sci. Int. Genet. 5:170). Each study arrived at different recommendations for eye color predictive tests aiming to type the most closely associated SNPs, although both confirmed rs12913832 in HERC2 as the key predictor, widely recognized as the most strongly associated marker with blue and brown iris colors. Differences between these two studies in identification of other eye color predictors may partly arise from varying approaches to assigning phenotypes, notably those not unequivocally blue or dark brown and therefore occupying an intermediate iris color continuum. We have developed two single base extension assays typing 37 SNPs in pigmentation-associated genes to study SNP-genotype based prediction of eye, skin, and hair color variation. These assays were used to test the performance of different sets of eye color predictors in 416 subjects from six populations of north and south Europe. The presence of a complex and continuous range of intermediate phenotypes distinct from blue and brown eye colors was confirmed by establishing eye color populations compared to genetic clusters defined using Structure software. Our study explored the effect of an expanded SNP combination beyond six markers has on the ability to predict eye color in a forensic test without extending the SNP assay excessively - thus maintaining a balance between the test's predictive value and an ability to reliably type challenging DNA with a multiplex of manageable size. Our evaluation used AUC analysis (area under the receiver operating characteristic curves) and naïve Bayesian likelihood-based classification approaches. To provide flexibility in SNP-based eye color predictive tests in forensic applications we modified an online Bayesian classifier, originally developed for genetic ancestry analysis, to provide a straightforward system to assign eye color likelihoods from a SNP profile combining additional informative markers from the predictors analyzed by our study plus those of Walsh and Mengel-From. Two advantages of the online classifier is the ability to submit incomplete SNP profiles, a common occurrence when typing challenging DNA, and the ability to handle physically linked SNPs showing independent effect, by allowing the user to input frequencies from SNP pairs or larger combinations. This system was used to include the submission of frequency data for the SNP pair rs12913832 and rs1129038: indicated by our study to be the two SNPs most closely associated to eye color.
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paper_title: Softwares and methods for estimating genetic ancestry in human populations

paper_content:

The estimation of genetic ancestry in human populations has important applications in medical genetic studies. Genetic ancestry is used to control for population stratification in genetic association studies, and is used to understand the genetic basis for ethnic differences in disease susceptibility. In this review, we present an overview of genetic ancestry estimation in human disease studies, followed by a review of popular softwares and methods used for this estimation.
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paper_title: Sensitive Detection of Chromosomal Segments of Distinct Ancestry in Admixed Populations

paper_content:

Identifying the ancestry of chromosomal segments of distinct ancestry has a wide range of applications from disease mapping to learning about history. Most methods require the use of unlinked markers; but, using all markers from genome-wide scanning arrays, it should in principle be possible to infer the ancestry of even very small segments with exquisite accuracy. We describe a method, HAPMIX, which employs an explicit population genetic model to perform such local ancestry inference based on fine-scale variation data. We show that HAPMIX outperforms other methods, and we explore its utility for inferring ancestry, learning about ancestral populations, and inferring dates of admixture. We validate the method empirically by applying it to populations that have experienced recent and ancient admixture: 935 African Americans from the United States and 29 Mozabites from North Africa. HAPMIX will be of particular utility for mapping disease genes in recently admixed populations, as its accurate estimates of local ancestry permit admixture and case-control association signals to be combined, enabling more powerful tests of association than with either signal alone.
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paper_title: CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure

paper_content:

Motivation: Clustering of individuals into populations on the basis of multilocus genotypes is informative in a variety of settings. In population-genetic clustering algorithms, such as BAPS, STRUCTURE and TESS, individual multilocus genotypes are partitioned over a set of clusters, often using unsupervised approaches that involve stochastic simulation. As a result, replicate cluster analyses of the same data may produce several distinct solutions for estimated cluster membership coefficients, even though the same initial conditions were used. Major differences among clustering solutions have two main sources: (1) ‘label switching’ of clusters across replicates, caused by the arbitrary way in which clusters in an unsupervised analysis are labeled, and (2) ‘genuine multimodality,’ truly distinct solutions across replicates. Results: To facilitate the interpretation of population-genetic clustering results, we describe three algorithms for aligning multiple replicate analyses of the same data set. We have implemented these algorithms in the computer program CLUMPP (CLUster Matching and Permutation Program). We illustrate the use of CLUMPP by aligning the cluster membership coefficients from 100 replicate cluster analyses of 600 chickens from 20 different breeds. Availability: CLUMPP is freely available at http://rosenberglab.
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paper_title: Population Structure and Eigenanalysis

paper_content:

Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general “phase change” phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like FST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.
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paper_title: Principal components analysis corrects for stratification in genome-wide association studies

paper_content:

Population stratification--allele frequency differences between cases and controls due to systematic ancestry differences-can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker's variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers.
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Title: An overview of STRUCTURE: applications, parameter settings, and supporting software

Section 1: AN OVERVIEW OF THE STRUCTURE PROGRAM
Description 1: Describe the basics and functionality of the STRUCTURE program for population analysis including the methodologies applied.

Section 2: ANCESTRY AND ALLELE FREQUENCY MODELS
Description 2: Discuss the models used in STRUCTURE for estimating ancestry and allele frequencies, including no admixture, admixture, linkage, and relevant ancestry models.

Section 3: ASSIGNMENT OF INDIVIDUALS TO A POPULATION AND CHOICE OF MARKERS
Description 3: Explain the processes and importance of assigning individuals to populations and the considerations for marker selection.

Section 4: REFERENCE SAMPLES AND VARIATION DATABASES
Description 4: Explore the role of reference samples and variation databases in population genetics studies using STRUCTURE.

Section 5: CASE-CONTROL ASSOCIATION STUDIES
Description 5: Discuss the application of STRUCTURE in designing and interpreting case-control association studies while accounting for population stratification.

Section 6: OTHER APPLICATIONS: FORENSIC ANALYSIS
Description 6: Describe how STRUCTURE can be applied in forensic analysis to infer ancestry and aid investigations.

Section 7: ALTERNATIVE POPULATION ANALYSIS APPROACHES
Description 7: Provide an overview of other population analysis programs that offer alternatives to STRUCTURE and compare their functionalities.

Section 8: THE STEP-BY-STEP GUIDE TO STRUCTURE ANALYSIS
Description 8: Provide a detailed user guide to performing STRUCTURE analysis, including creating input files, setting parameters, running simulations, and using supporting software like CLUMPP and distruct.

Section 9: CONCLUDING REMARKS
Description 9: Summarize the main points covered in the review and provide general guidance and considerations for using STRUCTURE in population genetics studies.