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{{Distinguish|Gene cluster|Metabolic gene cluster|Cluster genealogy}}
= Human genetic clustering =▼
'''Human genetic clustering''' refers to
Clustering studies are thought to be valuable for characterizing the general structure of genetic variation among human populations, to contribute to the study of ancestral origins, evolutionary history, and precision medicine. Since the mapping of the human genome, and with the availability of increasingly powerful analytic tools, [[Cluster analysis|cluster analyses]] have revealed a range of ancestral and migratory trends among human populations and individuals.<ref name=":
== Genetic clustering algorithms and methods ==
A wide range of methods have been developed to assess the structure of human populations with the use of genetic data. Early studies of within and between-group genetic variation used physical phenotypes and blood groups, with modern genetic studies using genetic markers such as
=== [[Model-based clustering]] ===
Common [[model-based clustering]] algorithms include STRUCTURE, ADMIXTURE, and HAPMIX. These algorithms operate by finding the best fit for genetic data among an arbitrary or mathematically derived number of clusters, such that differences within clusters are minimized and differences between clusters are maximized. This clustering method is also referred to as "[[Genetic admixture|admixture]] inference," as individual genomes (or individuals within populations) can be characterized by the proportions of [[
=== Multidimensional summary statistics ===
[[File:Whole-genome based PCA and clustering of worlds ethnic groups.png|thumb|upright=1.4|A 2023 [[Whole genome sequencing|whole-genome study]] of modern-day ethnic groups in the world identified 14 genomic clusters, which do not exactly align with current categorizations of race or ethnicity. The study also found that "99.8% of whole genome is identical between two individuals". Left image shows [[Cluster analysis|clustering]] following [[principal component analysis]] with [[Three-dimensional space|three dimensions]]. Top right image shows geographical locations where samples were collected.<ref name=Kim_Choi_Kim_2023>{{cite journal |doi=10.1038/s41598-023-32325-w |title=On whole-genome demography of world's ethnic groups and individual genomic identity |date=2023 |last1=Kim |first1=Byung-Ju |last2=Choi |first2=Jaejin |last3=Kim |first3=Sung-Hou |journal=Scientific Reports |volume=13 |issue=1 |page=6316 |pmid=37072456 |pmc=10113208 |bibcode=2023NatSR..13.6316K }}</ref>]]
Where model-based clustering characterizes populations using proportions of discrete clusters, multidimensional summary statistics characterize populations on a continuous spectrum. The most common multidimensional statistical method used for genetic clustering is [[principal component analysis]] (PCA), which plots individuals by two or more axes (their "principal components") that represent aggregations of genetic markers that account for the highest variance. Clusters can then be identified by assessing the distribution of data; with larger samples of human genotypes, data tends to cluster in discrete groups as well as admixed position between groups.<ref name=":0" /><ref name=":1" /> ▼
▲Where model-based clustering characterizes populations using proportions of
=== Caveats and limitations ===
There are caveats and limitations to genetic clustering methods of any type, given the degree of admixture and relative similarity within the human population. All genetic cluster findings are [[Sampling bias|biased]] by the sampling process used to gather data, and by the quality and quantity of that data. For example, many clustering studies use data derived from populations that are geographically distinct and far apart from one another, which may present an illusion of discrete clusters where, in reality, populations are much more blended with one another when intermediary groups are included.<ref name=":
==
A number of landmark genetic cluster studies have been conducted on global human populations since 2002, including the following:
{| class="wikitable"
!Authors
!Year
!Title
!Sample size / number of populations sampled
!Sample
!Markers
|-
|Rosenberg et al.
|2002
|Genetic Structure of Human Populations<ref name=":82">{{Cite journal|last1=Rosenberg|first1=Noah A.|last2=Pritchard|first2=Jonathan K.|last3=Weber|first3=James L.|last4=Cann|first4=Howard M.|last5=Kidd|first5=Kenneth K.|last6=Zhivotovsky|first6=Lev A.|last7=Feldman|first7=Marcus W.|date=2002-12-20|title=Genetic Structure of Human Populations|journal=Science|volume=298|issue=5602|pages=2381–2385|bibcode=2002Sci...298.2381R|doi=10.1126/science.1078311|issn=0036-8075|pmid=12493913|s2cid=8127224}}</ref>
|1056 / 52
|[[Human Genome Diversity Project]] (HGDP-CEPH)
|377 STRs
|-
| rowspan="2" |Serre & Pääbo
| rowspan="2" |2004
| rowspan="2" |Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation<ref>{{Cite journal|last1=Serre|first1=David|last2=Pääbo|first2=Svante|date=September 2004|title=Evidence for gradients of human genetic diversity within and among continents|journal=Genome Research|volume=14|issue=9|pages=1679–1685|doi=10.1101/gr.2529604|issn=1088-9051|pmc=515312|pmid=15342553}}</ref>
|89 / 15
|a: HGDP
| rowspan="2" |20 STRs
|-
|90 / geographically distributed individuals
|b: Jorde 1997
|-
|Rosenberg et al.
|2005
|Clines, Clusters, and the Effect of Study Design on the Inference of Human Population Structure<ref name="rosenberg20052">{{cite journal|last1=Rosenberg|first1=NA|last2=Mahajan|first2=S|last3=Ramachandran|first3=S|last4=Zhao|first4=C|last5=Pritchard|first5=JK|display-authors=etal|year=2005|title=Clines, Clusters, and the Effect of Study Design on the Inference of Human Population Structure|url=|journal=PLOS Genet|volume=1|issue=6|page=e70|doi=10.1371/journal.pgen.0010070|pmc=1310579|pmid=16355252|authorlink5=Jonathan K. Pritchard |doi-access=free }}</ref>
|1056 / 52
|[[Human Genome Diversity Project]] (HGDP-CEPH)
|783 STRs + 210 indels
|-
|Li et al.
|2008
|Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation<ref>{{Cite journal|last1=Li|first1=Jun Z.|last2=Absher|first2=Devin M.|last3=Tang|first3=Hua|last4=Southwick|first4=Audrey M.|last5=Casto|first5=Amanda M.|last6=Ramachandran|first6=Sohini|last7=Cann|first7=Howard M.|last8=Barsh|first8=Gregory S.|last9=Feldman|first9=Marcus|last10=Cavalli-Sforza|first10=Luigi L.|last11=Myers|first11=Richard M.|date=2008-02-22|title=Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation|journal=Science|volume=319|issue=5866|pages=1100–1104|bibcode=2008Sci...319.1100L|doi=10.1126/science.1153717|issn=0036-8075|pmid=18292342|s2cid=53541133}}</ref>
|938 / 51
|[[Human Genome Diversity Project]] (HGDP-CEPH)
|650,000 SNPs
|-
|Tishkoff et al.
|2009
|The Genetic Structure and History of Africans and African Americans<ref name=":622">{{Cite journal|last1=Tishkoff|first1=Sarah A|last2=Reed|first2=Floyd A|last3=Friedlaender|first3=Françoise R|last4=Ehret|first4=Christopher|last5=Ranciaro|first5=Alessia|last6=Froment|first6=Alain|last7=Hirbo|first7=Jibril B|last8=Awomoyi|first8=Agnes A|last9=Bodo|first9=Jean-Marie|last10=Doumbo|first10=Ogobara|last11=Ibrahim|first11=Muntaser|date=2009-05-22|title=The Genetic Structure and History of Africans and African Americans|journal=Science|volume=324|issue=5930|pages=1035–1044|bibcode=2009Sci...324.1035T|doi=10.1126/science.1172257|issn=0036-8075|pmc=2947357|pmid=19407144|first12=Abdalla T|last13=Kotze|first13=Maritha J|last14=Lema|first14=Godfrey|last15=Moore|first15=Jason H|last16=Mortensen|first16=Holly|first17=Thomas B|last18=Omar|first18=Sabah A|last12=Juma|first19=Kweli|last19=Powell|first20=Gideon S|last21=Smith|first21=Michael W|last22=Thera|first22=Mahamadou A|last23=Wambebe|first23=Charles|last24=Weber|first24=James L|last25=Williams|first25=Scott M|last20=Pretorius|last17=Nyambo}}</ref>
|~3400 / 185
|HGDP-CEPH ''plus'' 133 additional African populations and Indian individuals
|1327 STRs + indels
|-
|Xing et al.
|2010
|Toward a more uniform sampling of human genetic diversity: A survey of worldwide populations by high-density genotyping<ref name=":72">{{Cite journal|last1=Xing|first1=Jinchuan|last2=Watkins|first2=W. Scott|last3=Shlien|first3=Adam|last4=Walker|first4=Erin|last5=Huff|first5=Chad D.|last6=Witherspoon|first6=David J.|last7=Zhang|first7=Yuhua|last8=Simonson|first8=Tatum S.|last9=Weiss|first9=Robert B.|last10=Schiffman|first10=Joshua D.|last11=Malkin|first11=David|date=October 2010|title=Toward a more uniform sampling of human genetic diversity: A survey of worldwide populations by high-density genotyping|journal=Genomics|volume=96|issue=4|pages=199–210|doi=10.1016/j.ygeno.2010.07.004|issn=0888-7543|pmc=2945611|pmid=20643205|last12=Woodward|first12=Scott R.|last13=Jorde|first13=Lynn B.}}</ref>
|850 / 40
|HapMap ''plus'' 296 individuals
|250,000 SNPs
|}
== Genetic clustering and race ==▼
Clusters of individuals are often [[population structure (genetics)|geographically structured]]. For example, when clustering a population of East Asians and Europeans, each group will likely form its own respective cluster based on similar [[allele frequency|allele frequencies]].<ref>{{cite journal |last1=Spencer |first1=Quayshawn |title=A Radical Solution to the Race Problem |journal=Philosophy of Science |date=2014 |volume=81 |issue=5 |page=1029-30 |doi=10.1086/677694 |doi-access=free }}</ref> In this way, clusters can have a correlation with traditional concepts of race and self-identified ancestry; in some cases, such as medical questionnaires, the latter variables can be used as a proxy for genetic ancestry where genetic data is unavailable.<ref name=":42" /><ref name=":102" /> However, genetic variation is distributed in a complex, continuous, and overlapping manner, so this correlation is imperfect and the use of [[Race and health|racial categories in medicine]] can introduce additional hazards.<ref name=":42" />
In the related context of [[personalized medicine]], race is currently listed as a [[risk factor]] for a wide range of medical conditions with genetic and non-genetic causes. Questions have emerged regarding whether or not genetic clusters support the idea of race as a valid construct to apply to medical research and treatment of disease, because there are many diseases that correspond with specific genetic markers and/or with specific populations, as seen with [[Tay–Sachs disease|Tay-Sachs disease]] or [[sickle cell disease]].<ref name=":92" /><ref name=":63">{{Cite book|last1=Koenig|first1=Barbara A. Lee|first2=Sandra|last2=Soo-Jin|last3=Richardson|first3=Sarah S.|author-link3=Sarah S. Richardson|url=https://worldcat.org/oclc/468194495|title=Revisiting race in a genomic age|date=2008|publisher=Rutgers University Press|isbn=978-0-8135-4323-9|oclc=468194495}}</ref> Researchers are careful to emphasize that ancestry—revealed in part through cluster analyses—plays an important role in understanding risk of disease. But racial or ethnic identity does not perfectly align with genetic ancestry, and so race and ethnicity do not reveal enough information to make a medical diagnosis.<ref name=":63" /> Race as a variable in medicine is more likely to reflect social factors, where ancestry information is more likely to be meaningful when considering genetic ancestry.<ref name=":32" /><ref name=":63" />
▲== Genetic clustering and race ==
== References ==
▲Many other scholars have challenged the idea that race can be inferred by genetic clusters, drawing distinctions between arbitrarily assigned genetic clusters, ancestry, and race. One recurring caution against thinking of human populations in terms of clusters is the notion that genotypic variation and traits are distributed evenly between populations, along gradual [[Cline (biology)|clines]] rather than along discrete population boundaries; so although genetic similarities are usually organized geographically, their underlying populations have never been completely separated from one another. And due to migration, gene flow, and baseline homogeneity, features between groups are extensively overlapping and intermixed.<ref name=":3" /><ref name=":4" /> Moreover, genetic clusters do not typically match socially defined racial groups; many commonly understood races may not be sorted into the same genetic cluster, and many genetic clusters are made up of individuals who would have distinct racial identities.<ref name=":5" /> In general, clusters may most simply be understood as products of the methods used to sample and analyze genetic data; not without meaning for understanding ancestry and genetic characteristics, but inadequate to fully explaining the concept of race, which is more often described in terms of social and cultural forces.
<references />
{{Human genetics}}
{{Population genetics}}
[[Category:Human population genetics]]
[[Category:Biological anthropology]]
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