Evidence map›Paper›PMID 21913176›Full record

ArticleAmerican journal of physical anthropology2011

Single nucleotide polymorphisms and haplotypes in Native American populations.

Judith R Kidd, Françoise Friedlaender, Andrew J Pakstis, Manohar Furtado, Rixun Fang, Xudong Wang, Caroline M Nievergelt, Kenneth K Kidd

Abstract read
In one paragraph

Article in American journal of physical anthropology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Worldwide distribution of theProceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  6. Genetic variation in Tunisia in the context of human diversity worldwide.American journal of physical anthropology · 2016
    Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Judith R KiddDepartment of Genetics, Yale University Medical School, New Haven, CT 06520, USA. judith.kidd@yale.edu
Françoise Friedlaender
Andrew J Pakstis
Manohar Furtado
Rixun Fang
Xudong Wang
Caroline M Nievergelt
Kenneth K Kidd

Funding

Theoretical Studies of Linkage DisequilibriumP01GM057672 · NIGMS · YALE UNIVERSITY · PI KIDD, JUDITH R · 1998 to 2008
$11.0M
CONTROLS FOR ASSOCIATION STUDIES OF ALCOHOLISMR01AA009379 · NIAAA · YALE UNIVERSITY · PI KIDD, KENNETH K. · 1992 to 2009
$2.7M
Genomic Predictors of Combat Stress Vulnerability and ResilienceR01MH093500 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NIEVERGELT, CAROLINE M · 2011 to 2013
$2.7M
NIAAA NIH HHS AA009379NIAAA NIH HHS R01 AA009379NIGMS NIH HHS GM057672NIGMS NIH HHS P01 GM057672NIMH NIH HHS R01 MH093500
6 · The paper itself

Abstract

Autosomal DNA polymorphisms can provide new information and understanding of both the origins of and relationships among modern Native American populations. At the same time that autosomal markers can be highly informative, they are also susceptible to ascertainment biases in the selection of the markers to use. Identifying markers that can be used for ancestry inference among Native American populations can be considered separate from identifying markers to further the quest for history. In the current study, we are using data on nine Native American populations to compare the results based on a large haplotype-based dataset with relatively small independent sets of single nucleotide polymorphisms. We are interested in what types of limited datasets an individual laboratory might be able to collect are best for addressing two different questions of interest. First, how well can we differentiate the Native American populations and/or infer ancestry by assigning an individual to her population(s) of origin? Second, how well can we infer the historical/evolutionary relationships among Native American populations and their Eurasian origins? We conclude that only a large comprehensive dataset involving multiple autosomal markers on multiple populations will be able to answer both questions; different small sets of markers are able to answer only one or the other of these questions. Using our largest dataset, we see a general increasing distance from Old World populations from North to South in the New World except for an unexplained close relationship between our Maya and Quechua samples.

Indexed as

HaplotypesPolymorphism, Single NucleotideCluster AnalysisDatabases, GeneticHumansIndians, North AmericanLeast-Squares AnalysisPhylogenyPrincipal Component AnalysisWhite People

Identifiers

PMID21913176
PMCPMC3658315

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.