Content deleted Content added
pausing for now, hopefully one more push and this will be done |
finished last section, need to do applications to human genetics next |
||
Line 7:
== 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 ===
Line 28:
== Genetic clustering and race ==
A plurality of human genetic clustering studies have produced clusters of individuals with similar geographic origins or ancestry, and these findings have been interpreted by some to suggest biological support for the concept of race. Clustering results often, for example, have shown a clear cluster distinction between individuals with African and non-African ancestry, and other levels of clustering have come close to placing individuals all within their corresponding continental populations (i.e., Europeans clustered together, East Asians clustered together, etc.).<ref
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.
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>{{Cite journal|date=2012-10-29|editor-last=Goodman|editor-first=Alan H.|editor2-last=Moses|editor2-first=Yolanda T.|editor3-last=Jones|editor3-first=Joseph L.|title=Race|url=http://dx.doi.org/10.1002/9781118233023|doi=10.1002/9781118233023}}</ref><ref name=":6" /> 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=":6" /> Race as a variable in medicine is more likely to reflect social circumstances, where ancestry information is more likely to be meaningful when considering genetic ancestry.<ref name=":3" /><ref name=":6" />
<references />
| |||