1023:
983:
146:
982:
1482:, which seek to isolate and estimate the contribution of genetics to a trait by summing the effects of many individual genetic variants. To construct a score, researchers first enroll participants in an association study to estimate the contribution of each genetic variant. Then, they can use the estimated contributions of each genetic variant to calculate a score for the trait for an individual who was not in the original association study. If structure in the study population is correlated with environmental variation, then the polygenic score is no longer measuring the genetic component alone.
137:, or homogeneity in an ancestral population. Misspecification of such models, for instance by not taking into account the existence of structure in an ancestral population, can give rise to heavily biased parameter estimates. Simulation studies show that historical population structure can even have genetic effects that can easily be misinterpreted as historical changes in population size, or the existence of admixture events, even when no such events occurred.
4086:
1411:(UMAP) can visualize continental and subcontinental structure in human data. With larger datasets, UMAP better captures multiple scales of population structure; fine-scale patterns can be hidden or split with other methods, and these are of interest when the range of populations is diverse, when there are admixed populations, or when examining relationships between genotypes, phenotypes, and/or geography.
1532:. If environmental effects are related to a variant that exists in only one specific region (for example, a pollutant is found in only one city), it may not be possible to correct for this population structure effect at all. For many traits, the role of structure is complex and not fully understood, and incorporating it into genetic studies remains a challenge and is an active area of research.
976:, but rather an approximation considered useful for a given question. They are sensitive to sampling strategies, sample size, and close relatives in data sets; there may be no discrete populations at all; and there may be hierarchical structure where subpopulations are nested. Clusters may be admixed themselves, and may not have a useful interpretation as source populations.
60:) population, allele frequencies are expected to be roughly similar between groups. However, mating tends to be non-random to some degree, causing structure to arise. For example, a barrier like a river can separate two groups of the same species and make it difficult for potential mates to cross; if a
1026:
A map of the locations of genetic samples of several
African populations (left) and principal components 1 and 2 of the data superimposed on the map (right). The principal coordinate plane has been rotated 16.11° to align with the map. It corresponds to the east–west and north–south distributions of
1435:. By exploiting this fact and matching shared haplotype chunks from individuals within a genetic dataset, researchers may trace and date the origins of population admixture and reconstruct historic events such as the rise and fall of empires, slave trades, colonialism, and population expansions.
1463:
as the genetic variant is simply more common in Asians than in
Europeans. Also, actual genetic findings may be overlooked if the locus is less prevalent in the population where the case subjects are chosen. For this reason, it was common in the 1990s to use family-based data where the effect of
132:
Population structure is a complex phenomenon and no single measure captures it entirely. Understanding a population's structure requires a combination of methods and measures. Many statistical methods rely on simple population models in order to infer historical demographic changes, such as the
67:
Genetic variants do not necessarily cause observable changes in organisms, but can be correlated by coincidence because of population structure—a variant that is common in a population that has a high rate of disease may erroneously be thought to cause the disease. For this reason, population
953:. Since then, algorithms (such as ADMIXTURE) have been developed using other estimation techniques. Estimated proportions can be visualized using bar plots — each bar represents an individual, and is subdivided to represent the proportion of an individual's genetic ancestry from one of the
1527:
PCA and LMMs have become the most common methods to control for confounding from population structure. Though they are likely sufficient for avoiding false positives in association studies, they are still vulnerable to overestimating effect sizes of marginally associated variants and can
173:. The scale is important — an individual with both parents born in the United Kingdom is not inbred relative to that country's population, but is more inbred than two humans selected from the entire world. This motivates the derivation of Wright's
1375:
PCA transforms data to maximize variance; given enough data, when each individual is visualized as point on a plot, discrete clusters can form. Individuals with admixed ancestries will tend to fall between clusters, and when there is homogenous
124:, random chance, and (in humans) cultural factors. Even in lieu of these factors, individuals tend to stay close to where they were born, which means that alleles will not be distributed at random with respect to the full range of the species.
989:
900:
is 0, then the allele frequencies between populations are identical, suggesting no structure. The theoretical maximum value of 1 is attained when an allele reaches total fixation, but most observed maximum values are far lower.
2703:
Sakaue S, Hirata J, Kanai M, Suzuki K, Akiyama M, Lai Too C, Arayssi T, Hammoudeh M, Al Emadi S, Masri BK, Halabi H, Badsha H, Uthman IW, Saxena R, Padyukov L, Hirata M, Matsuda K, Murakami Y, Kamatani Y, Okada Y (March 2020).
891:
1388:
for pairs of individuals, making PCA useful for inference about the population histories of groups in a given sample. PCA cannot, however, distinguish between different processes that lead to the same mean coalescent times.
1370:
908:
is one of the most common measures of population structure and there are several different formulations depending on the number of populations and the alleles of interest. Although it is sometimes used as a
3148:
Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, et al. (February 2006). "A unified mixed-model method for association mapping that accounts for multiple levels of relatedness".
636:
555:
314:
992:
A study of population structure of humans in
Northern Africa and neighboring populations modelled using ADMIXTURE and assuming K=2,4,6,8 populations (Figure B, top to bottom). Varying
972:
will partition populations into finer subgroups. Though clustering methods are popular, they are open to misinterpretation: for non-simulated data, there is never a "true" value of
3105:
Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (August 2006). "Principal components analysis corrects for stratification in genome-wide association studies".
937:
discrete clusters of populations. Each cluster is defined by the frequencies of its genotypes, and the contribution of a cluster to an individual's genotypes is measured via an
712:
165:
within subpopulations, especially if the subpopulations are small or have been isolated for long periods. This reduction in heterozygosity can be thought of as an extension of
444:
404:
1275:
1170:
762:
208:
1249:
1202:
344:
2237:
Henn BM, Botigué LR, Gravel S, Wang W, Brisbin A, Byrnes JK, Fadhlaoui-Zid K, Zalloua PA, Moreno-Estrada A, Bertranpetit J, Bustamante CD, Comas D (January 2012).
1222:
1137:
1117:
1097:
1077:
732:
659:
464:
364:
248:
228:
104:
should be similar between groups. Population structure commonly arises from physical separation by distance or barriers, like mountains and rivers, followed by
1000:=2, 80% of the inferred ancestry for most North Africans is assigned to cluster that is common to Basque, Tuscan, and Qatari Arab individuals (in purple). At
3924:
3455:
770:
153:
can result in a loss of heterozygosity. In this hypothetical population, an allele has become fixed after the population repeatedly dropped from 10 to 3.
3295:
Sohail M, Maier RM, Ganna A, Bloemendal A, Martin AR, Turchin MC, et al. (March 2019). Nordborg M, McCarthy MI, Barton NH, Hermisson J (eds.).
1415:
can generate artificial genotypes with structure representative of the input data, though they do not recreate linkage disequilibrium patterns.
3412:
1408:
1022:
2441:
Novembre J, Johnson T, Bryc K, Kutalik Z, Boyko AR, Auton A, Indap A, King KS, Bergmann S, Nelson MR, Stephens M, Bustamante CD (2008).
3949:
1283:
1807:"The IICR and the non-stationary structured coalescent: towards demographic inference with arbitrary changes in population structure"
17:
133:
presence of population bottlenecks, admixture events or population divergence times. Often these methods rely on the assumption of
2706:"Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction"
4071:
3705:
3563:
1427:. Events like migrations and interactions between groups leave a genetic imprint on populations. Admixed populations will have
64:
occurs, over many generations it can spread and become common in one subpopulation while being completely absent in the other.
3460:
145:
3929:
1460:
563:
1595:
3773:
180:(also called "fixation indices"), which measure inbreeding through observed versus expected heterozygosity. For example,
3944:
3738:
469:
3297:"Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies"
3405:
1868:
256:
2145:
Novembre J, Ramachandran S (2011). "Perspectives on human population structure at the cusp of the sequencing era".
1465:
3505:
1455:
could be incorrect. As an example, in a study population of
Europeans and East Asians, an association study of
162:
4110:
1444:
77:
4120:
4030:
3435:
3398:
1509:
1400:
1040:
1059:) and normalizing the values, PCA could be applied at the level of individuals. One formulation considers
1055:
for populations, though later it was found that by coding SNPs as integers (for example, as the number of
3480:
1517:
1032:
2290:"A quantitative comparison of the similarity between genes and geography in worldwide human populations"
3778:
2339:
Menozzi P, Piazza A, Cavalli-Sforza L (1978). "Synthetic maps of human gene frequencies in
Europeans".
1475:
1048:
921:. It also depends on within-population diversity, which makes interpretation and comparison difficult.
664:
1474:(measurable traits), such as height or risk for heart disease, are the product of some combination of
4115:
3934:
3919:
3601:
3475:
1459:
usage may "discover" a gene in the Asian individuals that leads to chopstick use. However, this is a
1548:
Cardon LR, Palmer LJ (February 2003). "Population stratification and spurious allelic association".
3939:
3758:
3653:
1490:
1392:
1036:
946:
1399:
have been used to study differentiation, population assignment, and to analyze genetic distances.
3465:
1412:
409:
369:
3348:"Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity?"
2654:"UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts"
3731:
3450:
1498:
1254:
950:
170:
968:
for the entire human population will subdivide people roughly by continent, while using large
4066:
3900:
3865:
3692:
3586:
3581:
3485:
1805:
RodrĂguez W, Mazet O, Grusea S, Arredondo A, Corujo JM, Boitard S, Chikhi L (December 2018).
1432:
1396:
1377:
1142:
942:
150:
121:
113:
2912:"Use of unlinked genetic markers to detect population stratification in association studies"
2614:
Li W, Cerise JE, Yang Y, Han H (August 2017). "Application of t-SNE to human genetic data".
737:
183:
3965:
3783:
3538:
3346:
Lawson DJ, Davies NM, Haworth S, Ashraf B, Howe L, Crawford A, et al. (January 2020).
2823:
2717:
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2348:
1644:
1448:
1227:
1175:
918:
322:
93:
69:
8:
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4035:
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3768:
3763:
3682:
3558:
3445:
3421:
2810:
Hellenthal G, Busby GB, Band G, Wilson JF, Capelli C, Falush D, Myers S (February 2014).
1758:"Did Our Species Evolve in Subdivided Populations across Africa, and Why Does It Matter?"
1756:
Scerri EM, Thomas MG, Manica A, Gunz P, Stock JT, Stringer C, et al. (August 2018).
1508:
subpopulations, which are assumed to be unstructured. More recent approaches make use of
1424:
914:
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2721:
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2158:
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4005:
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1999:
1966:
1905:
1831:
1806:
1782:
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1738:
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1632:
1573:
1207:
1122:
1102:
1082:
1062:
717:
644:
449:
349:
233:
213:
101:
3197:"Efficient Bayesian mixed-model analysis increases association power in large cohorts"
1561:
4089:
4020:
4010:
4000:
3834:
3724:
3663:
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3596:
3523:
3515:
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2529:
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2423:
2372:
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2321:
2270:
2219:
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2120:
2102:
2063:
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2004:
1986:
1917:
1909:
1874:
1864:
1836:
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1730:
1722:
1717:
1700:
1678:
1660:
1565:
1385:
930:
2600:
1742:
1577:
886:{\displaystyle F_{ST}=1-{\frac {H_{S}}{H_{T}}}=1-{\frac {2p_{S}q_{S}}{2p_{T}q_{T}}}}
4050:
4025:
3622:
3533:
3367:
3359:
3318:
3308:
3267:
3257:
3216:
3208:
3177:
3157:
3134:
3114:
3077:
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3042:
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2931:
2923:
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2839:
2831:
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2725:
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2665:
2623:
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2519:
2478:
2462:
2413:
2403:
2356:
2311:
2301:
2260:
2250:
2209:
2193:
2154:
2110:
2094:
2053:
2035:
1994:
1978:
1901:
1826:
1818:
1777:
1769:
1712:
1668:
1652:
1557:
1056:
910:
81:
73:
45:
3910:
3440:
3192:
2670:
2524:
2408:
2306:
2255:
2040:
1486:
1479:
1052:
2778:
2197:
1485:
Several methods can at least partially control for this confounding effect. The
1431:
chunks from their ancestral groups, which gradually shrink over time because of
4040:
3980:
3880:
3687:
3677:
3591:
3470:
3363:
3246:"Demographic history mediates the effect of stratification on polygenic scores"
3013:
Devlin B, Roeder K (December 1999). "Genomic control for association studies".
2729:
1773:
1656:
1602:
1501:
1494:
1044:
158:
117:
100:
between groups: if all individuals within a population mate randomly, then the
3244:
Zaidi AA, Mathieson I (November 2020). Perry GH, Turchin MC, Martin P (eds.).
2627:
1982:
1822:
80:(GWAS). By tracing the origins of structure, it is also possible to study the
4104:
3627:
3617:
3573:
2533:
2474:
2368:
2205:
2106:
2049:
1990:
1913:
1726:
1664:
1452:
105:
97:
2835:
2652:
Diaz-Papkovich A, Anderson-Trocmé L, Ben-Eghan C, Gravel S (November 2019).
2651:
1878:
1464:
population structure can easily be controlled for using methods such as the
1008:=6, opposite clines of Near Eastern (Qatari) ancestry appear (in green). At
3990:
3870:
3643:
3495:
3381:
3332:
3281:
3230:
3169:
3126:
3091:
3034:
2999:
2945:
2888:
2853:
2796:
2747:
2689:
2635:
2592:
2551:
2492:
2427:
2360:
2325:
2274:
2223:
2166:
2124:
2067:
2008:
1921:
1840:
1791:
1734:
1682:
1633:"A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots"
1569:
1529:
174:
2880:
2098:
3970:
2583:
2566:
2376:
1858:
1521:
1513:
1381:
3313:
3262:
2980:
2466:
210:
measures the inbreeding coefficient at a single locus for an individual
3975:
3844:
3824:
3799:
2239:"Genomic ancestry of North Africans supports back-to-Africa migrations"
1591:
1380:
in the data, the top PC vectors will reflect geographic variation. The
964:
can illustrate different scales of population structure; using a small
166:
76:
studies, and accounting for and controlling its effect is important in
49:
3390:
1863:(3rd ed.). Sunderland, MA: Sinauer Associates. pp. 111–163.
3648:
1471:
1456:
1428:
945:
introduced the STRUCTURE algorithm to estimate these proportions via
938:
109:
3212:
714:
allowing us to compute the expected heterozygosity of subpopulation
4015:
3985:
3829:
3819:
3747:
3190:
3161:
3118:
3073:
2927:
161:. When populations split, alleles have a higher chance of reaching
134:
61:
53:
3055:
2083:"Fast model-based estimation of ancestry in unrelated individuals"
2024:"Inference of Population Structure Using Multilocus Genotype Data"
169:, with individuals in subpopulations being more likely to share a
27:
Stratification of a genetic population based on allele frequencies
1365:{\displaystyle {\frac {g_{i,l}-2p_{l}}{\sqrt {2p_{l}(1-p_{l})}}}}
3056:
Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (July 2000).
2867:
Hamer D, Sirota L (January 2000). "Beware the chopsticks gene".
2763:"Visualizing population structure with variational autoencoders"
2508:"A Genealogical Interpretation of Principal Components Analysis"
1423:
Population structure is an important aspect of evolutionary and
1384:
generated by PCA can be explicitly written in terms of the mean
1004:=4, clines of North African ancestry appear (in light blue). At
3839:
3814:
42:
3104:
1804:
1504:
to estimate each individual's ancestry proportions from some
1404:
157:
One of the results of population structure is a reduction in
2567:"Genetic markers in the playground of multivariate analysis"
1520:(also called a kinship matrix) and including it in a linear
446:, it is expected that under random mating the subpopulation
3716:
2338:
2182:"Pritchard, Stephens, and Donnelly on Population Structure"
2140:
2138:
2136:
2134:
1892:
Wright S (1949). "The
Genetical Structure of Populations".
1528:
substantially bias estimates of polygenic scores and trait
3294:
2440:
1451:, where the association between the trait of interest and
1043:(PCA) was first applied in population genetics in 1978 by
3809:
3804:
3345:
2964:"How well can we separate genetics from the environment?"
2809:
2021:
1701:"Assessing population structure:FST and related measures"
2131:
1051:. Initially PCA was used on allele frequencies at known
1012:=8, Tunisian Berbers appear as a cluster (in dark blue).
3147:
2702:
1967:"FST and the triangle inequality for biallelic markers"
366:
that are heterozygous. Assuming there are two alleles,
3191:
Loh PR, Tucker G, Bulik-Sullivan BK, Vilhjálmsson BJ,
2080:
1755:
2236:
2074:
2015:
1958:
1694:
1692:
1286:
1257:
1230:
1210:
1178:
1145:
1125:
1105:
1085:
1065:
773:
740:
720:
667:
647:
631:{\displaystyle F_{IS}=1-{\frac {H_{I}}{2p_{S}q_{S}}}}
566:
472:
452:
412:
372:
352:
325:
259:
236:
216:
186:
2647:
2645:
2564:
2287:
2144:
1630:
1626:
1624:
1622:
949:, modelling allele frequencies at each locus with a
913:
between populations, it does not always satisfy the
2434:
2389:
2909:
1689:
1489:method was introduced in 1999 and is a relatively
1364:
1269:
1243:
1216:
1196:
1164:
1131:
1111:
1091:
1071:
885:
756:
726:
706:
653:
630:
549:
458:
438:
398:
358:
338:
308:
242:
222:
202:
3006:
2760:
2642:
2332:
1964:
1619:
550:{\displaystyle H_{S}=2p_{S}(1-p_{S})=2p_{S}q_{S}}
4102:
2390:Patterson N, Price AL, Reich D (December 2006).
346:is the fraction of individuals in subpopulation
41:) is the presence of a systematic difference in
3058:"Association mapping in structured populations"
2761:Battey CJ, Coffing GC, Kern AD (January 2021).
2613:
2288:Wang C, Zöllner S, Rosenberg NA (August 2012).
1698:
1438:
1172:is the number of non-reference alleles (one of
929:An individual's genotype can be modelled as an
309:{\displaystyle F_{IS}=1-{\frac {H_{I}}{H_{S}}}}
3243:
2803:
2565:Jombart T, Pontier D, Dufour AB (April 2009).
3732:
3406:
2022:Pritchard JK, Stephens M, Donnelly P (2000).
1409:uniform manifold approximation and projection
1039:techniques can capture population structure.
3012:
2957:
2955:
2812:"A genetic atlas of human admixture history"
2607:
2173:
1852:
1850:
1547:
1277:matrix of normalized genotypes has entries:
2866:
2558:
1405:t-distributed stochastic neighbor embedding
1017:
92:The basic cause of population structure in
3739:
3725:
3413:
3399:
3339:
3288:
2754:
2696:
2499:
2081:Alexander DH, Novembre J, Lange K (2009).
1945:
1943:
1941:
1939:
1937:
1935:
1933:
1931:
1856:
1443:Population structure can be a problem for
3371:
3322:
3312:
3271:
3261:
3237:
3220:
3081:
2989:
2979:
2961:
2952:
2935:
2843:
2786:
2737:
2679:
2669:
2582:
2541:
2523:
2482:
2417:
2407:
2315:
2305:
2264:
2254:
2213:
2114:
2057:
2039:
1998:
1885:
1847:
1830:
1781:
1716:
1672:
2910:Pritchard JK, Rosenberg NA (July 1999).
2392:"Population structure and eigenanalysis"
2281:
2230:
2179:
1631:Lawson DJ, van Dorp L, Falush D (2018).
1493:method for controlling the inflation of
1418:
1021:
144:
4072:List of genetics research organizations
3420:
1928:
14:
4103:
3706:Index of evolutionary biology articles
3195:, Salem RM, et al. (March 2015).
2505:
2443:"Genes mirror geography within Europe"
1891:
1590:
1478:. These traits can be predicted using
924:
3720:
3394:
1099:bi-allelic SNPs. For each individual
406:that occur at respective frequencies
1952:Population and Quantitative Genetics
1949:
996:changes the scale of clustering. At
641:Similarly, for the total population
2159:10.1146/annurev-genom-090810-183123
466:will have a heterozygosity rate of
24:
3062:American Journal of Human Genetics
2962:Blanc J, Berg JJ (December 2020).
2916:American Journal of Human Genetics
1965:Arbisser IM, Rosenberg NA (2020).
1906:10.1111/j.1469-1809.1949.tb02451.x
25:
4132:
1860:Principles of population genetics
1762:Trends in Ecology & Evolution
1516:and colleagues, or by deriving a
1047:and colleagues and resurged with
707:{\displaystyle H_{T}=2p_{T}q_{T}}
140:
4085:
4084:
3027:10.1111/j.0006-341X.1999.00997.x
1718:10.1111/j.1755-0998.2010.02927.x
1699:Meirmans PG, Hedrick PW (2010).
1466:transmission disequilibrium test
981:
3184:
3141:
3098:
3049:
2903:
2860:
2383:
230:relative to some subpopulation
78:genome wide association studies
3506:Constructive neutral evolution
1971:Theoretical Population Biology
1798:
1749:
1584:
1541:
1356:
1337:
1204:). If the allele frequency at
518:
499:
87:
13:
1:
1562:10.1016/S0140-6736(03)12520-2
1535:
1497:. It is also possible to use
4031:Missing heritability problem
3746:
3456:Fisher's fundamental theorem
2671:10.1371/journal.pgen.1008432
2525:10.1371/journal.pgen.1000686
2409:10.1371/journal.pgen.0020190
2307:10.1371/journal.pgen.1002886
2256:10.1371/journal.pgen.1002397
1510:principal component analysis
1439:Role in genetic epidemiology
1041:Principal component analysis
7:
3481:Coefficient of relationship
2198:10.1534/genetics.116.195164
2147:Annu Rev Genomics Hum Genet
1857:Hartl DL, Clark AG (1997).
1705:Molecular Ecology Resources
1518:genetic relationship matrix
439:{\displaystyle p_{S},q_{S}}
399:{\displaystyle A_{1},A_{2}}
127:
84:of groups and individuals.
10:
4137:
3364:10.1007/s00439-019-02014-8
2730:10.1038/s41467-020-15194-z
2041:10.1093/genetics/155.2.945
1774:10.1016/j.tree.2018.05.005
1657:10.1038/s41467-018-05257-7
1512:(PCA), as demonstrated by
1049:high-throughput sequencing
4080:
4059:
3958:
3909:
3853:
3792:
3754:
3701:
3636:
3610:
3572:
3547:
3514:
3476:Coefficient of inbreeding
3428:
2779:10.1093/g3journal/jkaa036
2628:10.1142/S0219720017500172
1983:10.1016/j.tpb.2019.05.003
1823:10.1038/s41437-018-0148-0
1270:{\displaystyle N\times S}
39:population stratification
18:Population stratification
3654:Evolutionary game theory
3436:Hardy–Weinberg principle
1413:Variational autoencoders
1393:Multidimensional scaling
1037:dimensionality reduction
1018:Dimensionality reduction
947:Markov chain Monte Carlo
3466:Shifting balance theory
2836:10.1126/science.1243518
2616:J Bioinform Comput Biol
1165:{\displaystyle g_{i,l}}
108:. Other causes include
3451:Linkage disequilibrium
2361:10.1126/science.356262
1596:"Population Structure"
1366:
1271:
1245:
1218:
1198:
1166:
1133:
1113:
1093:
1073:
1028:
951:Dirichlet distribution
887:
758:
757:{\displaystyle F_{ST}}
728:
708:
655:
632:
551:
460:
440:
400:
360:
340:
310:
244:
224:
204:
203:{\displaystyle F_{IS}}
171:recent common ancestor
154:
114:population bottlenecks
68:structure is a common
4067:List of genetic codes
3693:Quantitative genetics
3602:Balding–Nichols model
3587:Population bottleneck
3582:Small population size
3486:Selection coefficient
2881:10.1038/sj.mp.4000662
2099:10.1101/gr.094052.109
1637:Nature Communications
1476:genes and environment
1461:spurious relationship
1419:Demographic inference
1397:discriminant analysis
1378:isolation by distance
1367:
1272:
1251:, then the resulting
1246:
1244:{\displaystyle p_{l}}
1219:
1199:
1197:{\displaystyle 0,1,2}
1167:
1134:
1119:, the value at locus
1114:
1094:
1074:
1057:non-reference alleles
1025:
943:Jonathan K. Pritchard
888:
759:
729:
709:
656:
633:
552:
461:
441:
401:
361:
341:
339:{\displaystyle H_{I}}
311:
245:
225:
205:
151:population bottleneck
148:
122:evolutionary pressure
4111:Genetic epidemiology
3966:Behavioural genetics
3564:Background selection
3551:on genomic variation
3549:Effects of selection
3501:Population structure
2869:Molecular Psychiatry
2584:10.1038/hdy.2008.130
1449:case-control studies
1284:
1255:
1228:
1208:
1176:
1143:
1123:
1103:
1083:
1063:
771:
738:
718:
665:
645:
564:
470:
450:
410:
370:
350:
323:
257:
234:
214:
184:
94:sexually reproducing
70:confounding variable
31:Population structure
4121:Population genetics
4046:Population genomics
4036:Molecular evolution
3996:Genetic engineering
3683:Population genomics
3559:Genetic hitchhiking
3446:Identity by descent
3422:Population genetics
3314:10.7554/eLife.39702
3263:10.7554/eLife.61548
2981:10.7554/eLife.64948
2828:2014Sci...343..747H
2722:2020NatCo..11.1569S
2467:10.1038/nature07331
2459:2008Natur.456...98N
2353:1978Sci...201..786M
2180:Novembre J (2016).
1649:2018NatCo...9.3258L
1445:association studies
1425:population genetics
925:Admixture inference
915:triangle inequality
4006:Genetic monitoring
3669:Landscape genetics
1894:Annals of Eugenics
1401:Neighborhood graph
1362:
1267:
1241:
1214:
1194:
1162:
1129:
1109:
1089:
1069:
1029:
917:and thus is not a
883:
754:
724:
704:
651:
628:
547:
456:
436:
396:
356:
336:
306:
240:
220:
200:
155:
102:allele frequencies
4098:
4097:
4021:He Jiankui affair
4011:Genetic genealogy
4001:Genetic diversity
3930:the British Isles
3835:Genetic variation
3714:
3713:
3664:Genetic genealogy
3659:Fitness landscape
2822:(6172): 747–751.
2506:McVean G (2009).
2347:(4358): 786–792.
1954:. pp. 22–44.
1556:(9357): 598–604.
1360:
1359:
1217:{\displaystyle l}
1132:{\displaystyle l}
1112:{\displaystyle i}
1092:{\displaystyle S}
1072:{\displaystyle N}
1031:Genetic data are
881:
818:
727:{\displaystyle S}
654:{\displaystyle T}
626:
459:{\displaystyle S}
359:{\displaystyle S}
304:
243:{\displaystyle S}
223:{\displaystyle I}
112:from migrations,
98:non-random mating
35:genetic structure
16:(Redirected from
4128:
4116:Medical genetics
4088:
4087:
4051:Reverse genetics
4026:Medical genetics
3741:
3734:
3727:
3718:
3717:
3623:J. B. S. Haldane
3415:
3408:
3401:
3392:
3391:
3386:
3385:
3375:
3343:
3337:
3336:
3326:
3316:
3292:
3286:
3285:
3275:
3265:
3241:
3235:
3234:
3224:
3188:
3182:
3181:
3145:
3139:
3138:
3102:
3096:
3095:
3085:
3053:
3047:
3046:
3010:
3004:
3003:
2993:
2983:
2959:
2950:
2949:
2939:
2907:
2901:
2900:
2864:
2858:
2857:
2847:
2807:
2801:
2800:
2790:
2758:
2752:
2751:
2741:
2700:
2694:
2693:
2683:
2673:
2664:(11): e1008432.
2649:
2640:
2639:
2611:
2605:
2604:
2586:
2571:Heredity (Edinb)
2562:
2556:
2555:
2545:
2527:
2518:(10): e1000686.
2503:
2497:
2496:
2486:
2453:(7218): 98–101.
2438:
2432:
2431:
2421:
2411:
2387:
2381:
2380:
2336:
2330:
2329:
2319:
2309:
2285:
2279:
2278:
2268:
2258:
2234:
2228:
2227:
2217:
2177:
2171:
2170:
2142:
2129:
2128:
2118:
2093:(9): 1655–1664.
2078:
2072:
2071:
2061:
2043:
2019:
2013:
2012:
2002:
1962:
1956:
1955:
1947:
1926:
1925:
1889:
1883:
1882:
1854:
1845:
1844:
1834:
1802:
1796:
1795:
1785:
1753:
1747:
1746:
1720:
1696:
1687:
1686:
1676:
1628:
1617:
1616:
1614:
1613:
1607:
1601:. Archived from
1600:
1588:
1582:
1581:
1545:
1480:polygenic scores
1403:approaches like
1386:coalescent times
1371:
1369:
1368:
1363:
1361:
1355:
1354:
1336:
1335:
1323:
1322:
1321:
1320:
1305:
1304:
1288:
1276:
1274:
1273:
1268:
1250:
1248:
1247:
1242:
1240:
1239:
1223:
1221:
1220:
1215:
1203:
1201:
1200:
1195:
1171:
1169:
1168:
1163:
1161:
1160:
1138:
1136:
1135:
1130:
1118:
1116:
1115:
1110:
1098:
1096:
1095:
1090:
1079:individuals and
1078:
1076:
1075:
1070:
1033:high dimensional
1027:the populations.
985:
911:genetic distance
892:
890:
889:
884:
882:
880:
879:
878:
869:
868:
855:
854:
853:
844:
843:
830:
819:
817:
816:
807:
806:
797:
786:
785:
763:
761:
760:
755:
753:
752:
733:
731:
730:
725:
713:
711:
710:
705:
703:
702:
693:
692:
677:
676:
661:, we can define
660:
658:
657:
652:
637:
635:
634:
629:
627:
625:
624:
623:
614:
613:
600:
599:
590:
579:
578:
556:
554:
553:
548:
546:
545:
536:
535:
517:
516:
498:
497:
482:
481:
465:
463:
462:
457:
445:
443:
442:
437:
435:
434:
422:
421:
405:
403:
402:
397:
395:
394:
382:
381:
365:
363:
362:
357:
345:
343:
342:
337:
335:
334:
315:
313:
312:
307:
305:
303:
302:
293:
292:
283:
272:
271:
249:
247:
246:
241:
229:
227:
226:
221:
209:
207:
206:
201:
199:
198:
116:and expansions,
82:genetic ancestry
74:medical genetics
21:
4136:
4135:
4131:
4130:
4129:
4127:
4126:
4125:
4101:
4100:
4099:
4094:
4076:
4055:
3954:
3945:the Middle East
3911:Archaeogenetics
3905:
3849:
3788:
3750:
3745:
3715:
3710:
3697:
3632:
3606:
3568:
3552:
3550:
3543:
3510:
3441:Genetic linkage
3424:
3419:
3389:
3344:
3340:
3293:
3289:
3242:
3238:
3213:10.1038/ng.3190
3201:Nature Genetics
3189:
3185:
3150:Nature Genetics
3146:
3142:
3107:Nature Genetics
3103:
3099:
3054:
3050:
3021:(4): 997–1004.
3011:
3007:
2960:
2953:
2908:
2904:
2865:
2861:
2808:
2804:
2759:
2755:
2701:
2697:
2650:
2643:
2612:
2608:
2563:
2559:
2504:
2500:
2439:
2435:
2388:
2384:
2337:
2333:
2300:(8): e1002886.
2286:
2282:
2249:(1): e1002397.
2235:
2231:
2178:
2174:
2143:
2132:
2087:Genome Research
2079:
2075:
2020:
2016:
1963:
1959:
1950:Coop G (2019).
1948:
1929:
1890:
1886:
1871:
1855:
1848:
1803:
1799:
1754:
1750:
1697:
1690:
1629:
1620:
1611:
1609:
1605:
1598:
1589:
1585:
1546:
1542:
1538:
1502:genetic markers
1495:test statistics
1487:genomic control
1441:
1421:
1350:
1346:
1331:
1327:
1316:
1312:
1294:
1290:
1289:
1287:
1285:
1282:
1281:
1256:
1253:
1252:
1235:
1231:
1229:
1226:
1225:
1209:
1206:
1205:
1177:
1174:
1173:
1150:
1146:
1144:
1141:
1140:
1124:
1121:
1120:
1104:
1101:
1100:
1084:
1081:
1080:
1064:
1061:
1060:
1053:genetic markers
1020:
1015:
1014:
1013:
991:
986:
927:
906:
874:
870:
864:
860:
856:
849:
845:
839:
835:
831:
829:
812:
808:
802:
798:
796:
778:
774:
772:
769:
768:
745:
741:
739:
736:
735:
719:
716:
715:
698:
694:
688:
684:
672:
668:
666:
663:
662:
646:
643:
642:
619:
615:
609:
605:
601:
595:
591:
589:
571:
567:
565:
562:
561:
541:
537:
531:
527:
512:
508:
493:
489:
477:
473:
471:
468:
467:
451:
448:
447:
430:
426:
417:
413:
411:
408:
407:
390:
386:
377:
373:
371:
368:
367:
351:
348:
347:
330:
326:
324:
321:
320:
298:
294:
288:
284:
282:
264:
260:
258:
255:
254:
235:
232:
231:
215:
212:
211:
191:
187:
185:
182:
181:
143:
130:
118:founder effects
90:
54:randomly mating
28:
23:
22:
15:
12:
11:
5:
4134:
4124:
4123:
4118:
4113:
4096:
4095:
4093:
4092:
4081:
4078:
4077:
4075:
4074:
4069:
4063:
4061:
4057:
4056:
4054:
4053:
4048:
4043:
4041:Plant genetics
4038:
4033:
4028:
4023:
4018:
4013:
4008:
4003:
3998:
3993:
3988:
3983:
3981:Genome editing
3978:
3973:
3968:
3962:
3960:
3959:Related topics
3956:
3955:
3953:
3952:
3947:
3942:
3937:
3932:
3927:
3922:
3916:
3914:
3907:
3906:
3904:
3903:
3898:
3893:
3888:
3883:
3881:Immunogenetics
3878:
3873:
3868:
3863:
3857:
3855:
3851:
3850:
3848:
3847:
3842:
3837:
3832:
3827:
3822:
3817:
3812:
3807:
3802:
3796:
3794:
3793:Key components
3790:
3789:
3787:
3786:
3781:
3776:
3771:
3766:
3761:
3755:
3752:
3751:
3744:
3743:
3736:
3729:
3721:
3712:
3711:
3709:
3708:
3702:
3699:
3698:
3696:
3695:
3690:
3688:Phylogeography
3685:
3680:
3678:Microevolution
3675:
3666:
3661:
3656:
3651:
3646:
3640:
3638:
3637:Related topics
3634:
3633:
3631:
3630:
3625:
3620:
3614:
3612:
3608:
3607:
3605:
3604:
3599:
3594:
3592:Founder effect
3589:
3584:
3578:
3576:
3570:
3569:
3567:
3566:
3561:
3555:
3553:
3548:
3545:
3544:
3542:
3541:
3536:
3531:
3526:
3520:
3518:
3512:
3511:
3509:
3508:
3503:
3498:
3493:
3488:
3483:
3478:
3473:
3471:Price equation
3468:
3463:
3461:Neutral theory
3458:
3453:
3448:
3443:
3438:
3432:
3430:
3426:
3425:
3418:
3417:
3410:
3403:
3395:
3388:
3387:
3352:Human Genetics
3338:
3287:
3236:
3183:
3162:10.1038/ng1702
3140:
3119:10.1038/ng1847
3097:
3074:10.1086/302959
3048:
3005:
2951:
2928:10.1086/302449
2902:
2859:
2802:
2753:
2695:
2641:
2622:(4): 1750017.
2606:
2557:
2498:
2433:
2382:
2331:
2280:
2229:
2192:(2): 391–393.
2172:
2130:
2073:
2034:(2): 945–959.
2014:
1957:
1927:
1900:(1): 323–354.
1884:
1869:
1846:
1817:(6): 663–678.
1797:
1768:(8): 582–594.
1748:
1688:
1618:
1583:
1539:
1537:
1534:
1440:
1437:
1420:
1417:
1373:
1372:
1358:
1353:
1349:
1345:
1342:
1339:
1334:
1330:
1326:
1319:
1315:
1311:
1308:
1303:
1300:
1297:
1293:
1266:
1263:
1260:
1238:
1234:
1213:
1193:
1190:
1187:
1184:
1181:
1159:
1156:
1153:
1149:
1128:
1108:
1088:
1068:
1045:Cavalli-Sforza
1019:
1016:
988:
987:
980:
979:
978:
926:
923:
904:
894:
893:
877:
873:
867:
863:
859:
852:
848:
842:
838:
834:
828:
825:
822:
815:
811:
805:
801:
795:
792:
789:
784:
781:
777:
751:
748:
744:
734:and the value
723:
701:
697:
691:
687:
683:
680:
675:
671:
650:
639:
638:
622:
618:
612:
608:
604:
598:
594:
588:
585:
582:
577:
574:
570:
544:
540:
534:
530:
526:
523:
520:
515:
511:
507:
504:
501:
496:
492:
488:
485:
480:
476:
455:
433:
429:
425:
420:
416:
393:
389:
385:
380:
376:
355:
333:
329:
317:
316:
301:
297:
291:
287:
281:
278:
275:
270:
267:
263:
239:
219:
197:
194:
190:
159:heterozygosity
142:
141:Heterozygosity
139:
129:
126:
89:
86:
50:subpopulations
26:
9:
6:
4:
3:
2:
4133:
4122:
4119:
4117:
4114:
4112:
4109:
4108:
4106:
4091:
4083:
4082:
4079:
4073:
4070:
4068:
4065:
4064:
4062:
4058:
4052:
4049:
4047:
4044:
4042:
4039:
4037:
4034:
4032:
4029:
4027:
4024:
4022:
4019:
4017:
4014:
4012:
4009:
4007:
4004:
4002:
3999:
3997:
3994:
3992:
3989:
3987:
3984:
3982:
3979:
3977:
3974:
3972:
3969:
3967:
3964:
3963:
3961:
3957:
3951:
3948:
3946:
3943:
3941:
3938:
3936:
3933:
3931:
3928:
3926:
3923:
3921:
3918:
3917:
3915:
3912:
3908:
3902:
3899:
3897:
3894:
3892:
3889:
3887:
3884:
3882:
3879:
3877:
3874:
3872:
3869:
3867:
3864:
3862:
3859:
3858:
3856:
3852:
3846:
3843:
3841:
3838:
3836:
3833:
3831:
3828:
3826:
3823:
3821:
3818:
3816:
3813:
3811:
3808:
3806:
3803:
3801:
3798:
3797:
3795:
3791:
3785:
3782:
3780:
3777:
3775:
3772:
3770:
3767:
3765:
3762:
3760:
3757:
3756:
3753:
3749:
3742:
3737:
3735:
3730:
3728:
3723:
3722:
3719:
3707:
3704:
3703:
3700:
3694:
3691:
3689:
3686:
3684:
3681:
3679:
3676:
3674:
3670:
3667:
3665:
3662:
3660:
3657:
3655:
3652:
3650:
3647:
3645:
3642:
3641:
3639:
3635:
3629:
3628:Sewall Wright
3626:
3624:
3621:
3619:
3616:
3615:
3613:
3609:
3603:
3600:
3598:
3595:
3593:
3590:
3588:
3585:
3583:
3580:
3579:
3577:
3575:
3574:Genetic drift
3571:
3565:
3562:
3560:
3557:
3556:
3554:
3546:
3540:
3537:
3535:
3532:
3530:
3527:
3525:
3522:
3521:
3519:
3517:
3513:
3507:
3504:
3502:
3499:
3497:
3494:
3492:
3489:
3487:
3484:
3482:
3479:
3477:
3474:
3472:
3469:
3467:
3464:
3462:
3459:
3457:
3454:
3452:
3449:
3447:
3444:
3442:
3439:
3437:
3434:
3433:
3431:
3427:
3423:
3416:
3411:
3409:
3404:
3402:
3397:
3396:
3393:
3383:
3379:
3374:
3369:
3365:
3361:
3357:
3353:
3349:
3342:
3334:
3330:
3325:
3320:
3315:
3310:
3306:
3302:
3298:
3291:
3283:
3279:
3274:
3269:
3264:
3259:
3255:
3251:
3247:
3240:
3232:
3228:
3223:
3218:
3214:
3210:
3207:(3): 284–90.
3206:
3202:
3198:
3194:
3187:
3179:
3175:
3171:
3167:
3163:
3159:
3155:
3151:
3144:
3136:
3132:
3128:
3124:
3120:
3116:
3112:
3108:
3101:
3093:
3089:
3084:
3079:
3075:
3071:
3068:(1): 170–81.
3067:
3063:
3059:
3052:
3044:
3040:
3036:
3032:
3028:
3024:
3020:
3016:
3009:
3001:
2997:
2992:
2987:
2982:
2977:
2973:
2969:
2965:
2958:
2956:
2947:
2943:
2938:
2933:
2929:
2925:
2921:
2917:
2913:
2906:
2898:
2894:
2890:
2886:
2882:
2878:
2874:
2870:
2863:
2855:
2851:
2846:
2841:
2837:
2833:
2829:
2825:
2821:
2817:
2813:
2806:
2798:
2794:
2789:
2784:
2780:
2776:
2772:
2768:
2767:G3 (Bethesda)
2764:
2757:
2749:
2745:
2740:
2735:
2731:
2727:
2723:
2719:
2715:
2711:
2707:
2699:
2691:
2687:
2682:
2677:
2672:
2667:
2663:
2659:
2655:
2648:
2646:
2637:
2633:
2629:
2625:
2621:
2617:
2610:
2602:
2598:
2594:
2590:
2585:
2580:
2577:(4): 330–41.
2576:
2572:
2568:
2561:
2553:
2549:
2544:
2539:
2535:
2531:
2526:
2521:
2517:
2513:
2512:PLOS Genetics
2509:
2502:
2494:
2490:
2485:
2480:
2476:
2472:
2468:
2464:
2460:
2456:
2452:
2448:
2444:
2437:
2429:
2425:
2420:
2415:
2410:
2405:
2401:
2397:
2396:PLOS Genetics
2393:
2386:
2378:
2374:
2370:
2366:
2362:
2358:
2354:
2350:
2346:
2342:
2335:
2327:
2323:
2318:
2313:
2308:
2303:
2299:
2295:
2291:
2284:
2276:
2272:
2267:
2262:
2257:
2252:
2248:
2244:
2240:
2233:
2225:
2221:
2216:
2211:
2207:
2203:
2199:
2195:
2191:
2187:
2183:
2176:
2168:
2164:
2160:
2156:
2153:(1): 245–74.
2152:
2148:
2141:
2139:
2137:
2135:
2126:
2122:
2117:
2112:
2108:
2104:
2100:
2096:
2092:
2088:
2084:
2077:
2069:
2065:
2060:
2055:
2051:
2047:
2042:
2037:
2033:
2029:
2025:
2018:
2010:
2006:
2001:
1996:
1992:
1988:
1984:
1980:
1976:
1972:
1968:
1961:
1953:
1946:
1944:
1942:
1940:
1938:
1936:
1934:
1932:
1923:
1919:
1915:
1911:
1907:
1903:
1899:
1895:
1888:
1880:
1876:
1872:
1870:0-87893-306-9
1866:
1862:
1861:
1853:
1851:
1842:
1838:
1833:
1828:
1824:
1820:
1816:
1812:
1808:
1801:
1793:
1789:
1784:
1779:
1775:
1771:
1767:
1763:
1759:
1752:
1744:
1740:
1736:
1732:
1728:
1724:
1719:
1714:
1710:
1706:
1702:
1695:
1693:
1684:
1680:
1675:
1670:
1666:
1662:
1658:
1654:
1650:
1646:
1642:
1638:
1634:
1627:
1625:
1623:
1608:on 2018-11-23
1604:
1597:
1593:
1587:
1579:
1575:
1571:
1567:
1563:
1559:
1555:
1551:
1544:
1540:
1533:
1531:
1525:
1523:
1519:
1515:
1511:
1507:
1503:
1500:
1496:
1492:
1491:nonparametric
1488:
1483:
1481:
1477:
1473:
1469:
1467:
1462:
1458:
1454:
1450:
1446:
1436:
1434:
1433:recombination
1430:
1426:
1416:
1414:
1410:
1406:
1402:
1398:
1394:
1390:
1387:
1383:
1379:
1351:
1347:
1343:
1340:
1332:
1328:
1324:
1317:
1313:
1309:
1306:
1301:
1298:
1295:
1291:
1280:
1279:
1278:
1264:
1261:
1258:
1236:
1232:
1211:
1191:
1188:
1185:
1182:
1179:
1157:
1154:
1151:
1147:
1126:
1106:
1086:
1066:
1058:
1054:
1050:
1046:
1042:
1038:
1034:
1024:
1011:
1007:
1003:
999:
995:
990:
984:
977:
975:
971:
967:
963:
958:
957:populations.
956:
952:
948:
944:
940:
936:
932:
922:
920:
916:
912:
907:
899:
875:
871:
865:
861:
857:
850:
846:
840:
836:
832:
826:
823:
820:
813:
809:
803:
799:
793:
790:
787:
782:
779:
775:
767:
766:
765:
749:
746:
742:
721:
699:
695:
689:
685:
681:
678:
673:
669:
648:
620:
616:
610:
606:
602:
596:
592:
586:
583:
580:
575:
572:
568:
560:
559:
558:
542:
538:
532:
528:
524:
521:
513:
509:
505:
502:
494:
490:
486:
483:
478:
474:
453:
431:
427:
423:
418:
414:
391:
387:
383:
378:
374:
353:
331:
327:
299:
295:
289:
285:
279:
276:
273:
268:
265:
261:
253:
252:
251:
237:
217:
195:
192:
188:
179:
177:
172:
168:
164:
160:
152:
147:
138:
136:
125:
123:
119:
115:
111:
107:
106:genetic drift
103:
99:
95:
85:
83:
79:
75:
71:
65:
63:
59:
55:
51:
47:
44:
40:
36:
33:(also called
32:
19:
3991:Genetic code
3925:the Americas
3901:Quantitative
3871:Cytogenetics
3866:Conservation
3759:Introduction
3644:Biogeography
3618:R. A. Fisher
3500:
3496:Heritability
3429:Key concepts
3358:(1): 23–41.
3355:
3351:
3341:
3304:
3300:
3290:
3253:
3249:
3239:
3204:
3200:
3186:
3156:(2): 203–8.
3153:
3149:
3143:
3113:(8): 904–9.
3110:
3106:
3100:
3065:
3061:
3051:
3018:
3014:
3008:
2971:
2967:
2922:(1): 220–8.
2919:
2915:
2905:
2872:
2868:
2862:
2819:
2815:
2805:
2770:
2766:
2756:
2713:
2709:
2698:
2661:
2657:
2619:
2615:
2609:
2574:
2570:
2560:
2515:
2511:
2501:
2450:
2446:
2436:
2402:(12): e190.
2399:
2395:
2385:
2344:
2340:
2334:
2297:
2293:
2283:
2246:
2242:
2232:
2189:
2185:
2175:
2150:
2146:
2090:
2086:
2076:
2031:
2027:
2017:
1974:
1970:
1960:
1951:
1897:
1893:
1887:
1859:
1814:
1810:
1800:
1765:
1761:
1751:
1708:
1704:
1640:
1636:
1610:. Retrieved
1603:the original
1586:
1553:
1549:
1543:
1530:heritability
1526:
1505:
1484:
1470:
1442:
1422:
1407:(t-SNE) and
1391:
1382:eigenvectors
1374:
1030:
1009:
1005:
1001:
997:
993:
973:
969:
965:
961:
959:
954:
934:
928:
902:
897:
895:
640:
318:
175:
156:
131:
91:
66:
57:
38:
34:
30:
29:
3971:Epigenetics
3597:Coalescence
3193:Finucane HK
2875:(1): 11–3.
2716:(1): 1569.
1977:: 117–129.
1711:(1): 5–18.
1643:(1): 3258.
1522:mixed model
1514:Alkes Price
941:. In 2000,
178:-statistics
96:species is
88:Description
46:frequencies
4105:Categories
3976:Geneticist
3950:South Asia
3896:Population
3876:Ecological
3845:Amino acid
3825:Nucleotide
3800:Chromosome
3539:Ecological
3529:Artificial
3307:: e39702.
3256:: e61548.
3015:Biometrics
2974:: e64948.
2710:Nat Commun
2658:PLOS Genet
2294:PLOS Genet
2243:PLOS Genet
1612:2020-11-14
1536:References
1472:Phenotypes
1447:, such as
167:inbreeding
3891:Molecular
3886:Microbial
3861:Classical
3649:Evolution
3516:Selection
2534:1553-7404
2475:0028-0836
2369:0036-8075
2206:1943-2631
2107:1088-9051
2050:1943-2631
1991:0040-5809
1914:2050-1420
1727:1755-098X
1665:2041-1723
1457:chopstick
1429:haplotype
1344:−
1307:−
1262:×
939:estimator
931:admixture
827:−
794:−
587:−
506:−
280:−
135:panmictia
110:gene flow
58:panmictic
4090:Category
4016:Heredity
3986:Genomics
3830:Mutation
3820:Heredity
3784:Glossary
3774:Timeline
3748:Genetics
3673:genomics
3611:Founders
3382:31030318
3333:30895926
3282:33200985
3231:25642633
3170:16380716
3127:16862161
3092:10827107
3035:11315092
3000:33355092
2946:10364535
2889:10673763
2854:24531965
2797:33561250
2748:32218440
2690:31675358
2636:28718343
2601:10739417
2593:19156164
2552:19834557
2493:18758442
2428:17194218
2326:22927824
2275:22253600
2224:27729489
2186:Genetics
2167:21801023
2125:19648217
2068:10835412
2028:Genetics
2009:31132375
1922:24540312
1879:37481398
1841:30293985
1811:Heredity
1792:30007846
1743:24403040
1735:21429096
1683:30108219
1594:(2001).
1592:McVean G
1578:14255234
1570:12598158
1499:unlinked
960:Varying
933:between
557:. Then:
163:fixation
128:Measures
62:mutation
48:between
3769:History
3764:Outline
3524:Natural
3491:Fitness
3373:6942007
3324:6428571
3273:7758063
3222:4342297
3178:8507433
3135:8127858
3083:1287075
3043:6297807
2991:7758058
2937:1378093
2897:9760182
2845:4209567
2824:Bibcode
2816:Science
2788:8022710
2739:7099015
2718:Bibcode
2681:6853336
2543:2757795
2484:2735096
2455:Bibcode
2419:1713260
2349:Bibcode
2341:Science
2317:3426559
2266:3257290
2215:5068833
2116:2752134
2059:1461096
2000:8448291
1832:6221895
1783:6092560
1674:6092366
1645:Bibcode
1524:(LMM).
1468:(TDT).
52:. In a
3935:Europe
3920:Africa
3854:Fields
3840:Allele
3815:Genome
3534:Sexual
3380:
3370:
3331:
3321:
3280:
3270:
3229:
3219:
3176:
3168:
3133:
3125:
3090:
3080:
3041:
3033:
2998:
2988:
2944:
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2887:
2852:
2842:
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2785:
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2736:
2688:
2678:
2634:
2599:
2591:
2550:
2540:
2532:
2491:
2481:
2473:
2447:Nature
2426:
2416:
2377:356262
2375:
2367:
2324:
2314:
2273:
2263:
2222:
2212:
2204:
2165:
2123:
2113:
2105:
2066:
2056:
2048:
2007:
1997:
1989:
1920:
1912:
1877:
1867:
1839:
1829:
1790:
1780:
1741:
1733:
1725:
1681:
1671:
1663:
1576:
1568:
1550:Lancet
919:metric
319:Here,
43:allele
4060:Lists
3940:Italy
3779:Index
3301:eLife
3250:eLife
3174:S2CID
3131:S2CID
3039:S2CID
2968:eLife
2893:S2CID
2773:(1).
2597:S2CID
1739:S2CID
1606:(PDF)
1599:(PDF)
1574:S2CID
1453:locus
3671:and
3378:PMID
3329:PMID
3278:PMID
3227:PMID
3166:PMID
3123:PMID
3088:PMID
3031:PMID
2996:PMID
2942:PMID
2885:PMID
2850:PMID
2793:PMID
2744:PMID
2686:PMID
2632:PMID
2589:PMID
2548:PMID
2530:ISSN
2489:PMID
2471:ISSN
2424:PMID
2373:PMID
2365:ISSN
2322:PMID
2271:PMID
2220:PMID
2202:ISSN
2163:PMID
2121:PMID
2103:ISSN
2064:PMID
2046:ISSN
2005:PMID
1987:ISSN
1918:PMID
1910:ISSN
1875:OCLC
1865:ISBN
1837:PMID
1788:PMID
1731:PMID
1723:ISSN
1679:PMID
1661:ISSN
1566:PMID
1395:and
1035:and
764:as:
56:(or
37:and
3810:RNA
3805:DNA
3368:PMC
3360:doi
3356:139
3319:PMC
3309:doi
3268:PMC
3258:doi
3217:PMC
3209:doi
3158:doi
3115:doi
3078:PMC
3070:doi
3023:doi
2986:PMC
2976:doi
2932:PMC
2924:doi
2877:doi
2840:PMC
2832:doi
2820:343
2783:PMC
2775:doi
2734:PMC
2726:doi
2676:PMC
2666:doi
2624:doi
2579:doi
2575:102
2538:PMC
2520:doi
2479:PMC
2463:doi
2451:456
2414:PMC
2404:doi
2357:doi
2345:201
2312:PMC
2302:doi
2261:PMC
2251:doi
2210:PMC
2194:doi
2190:204
2155:doi
2111:PMC
2095:doi
2054:PMC
2036:doi
2032:155
1995:PMC
1979:doi
1975:133
1902:doi
1827:PMC
1819:doi
1815:121
1778:PMC
1770:doi
1713:doi
1669:PMC
1653:doi
1558:doi
1554:361
1224:is
1139:is
896:If
72:in
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2994:.
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2954:^
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