Computation of ancestry scores with mixed families and unrelated individuals

Computation of ancestry scores with mixed families and unrelated individuals IntroductionDiffering ancestries of human subpopulations create systematic differences in genetic allele frequencies across the genome, a phenomenon known as population stratification or substructure. If a phenotypic trait such as disease is associated with subpopulation membership, a genetic association study can identify spurious relationships with genetic markers. Singular value decomposition (SVD) of genotype data or eigen decomposition of covariance matrices can be used to identify population stratification. The eigenvectors (essentially principal component scores) that correspond to large eigenvalues can be used as covariates in association analysis (Levine et al., ). The combined analysis of unrelated and related individuals is a common feature of genetic association studies (Zhu et al., ). However, the presence of close‐degree relatives in a genetic dataset presents difficulties, as the family structure can greatly influence the eigenvalues and eigenvectors.Cystic fibrosis (CF) is a recessive genetic lung disorder, caused by a mutation in the single gene CFTR. However, considerable genetic variation remains in the severity of disease, and evidence indicates this variation is complex and influenced by numerous genes (Wright et al., ). Genotypes gathered by the North American CF Consortium are typical of a large‐scale genomewide association study (GWAS), with thousands of individuals and over 1 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biometrics Wiley

Computation of ancestry scores with mixed families and unrelated individuals

Loading next page...
 
/lp/wiley/computation-of-ancestry-scores-with-mixed-families-and-unrelated-bewo9j3PD9
Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
© 2018, The International Biometric Society
ISSN
0006-341X
eISSN
1541-0420
D.O.I.
10.1111/biom.12708
Publisher site
See Article on Publisher Site

Abstract

IntroductionDiffering ancestries of human subpopulations create systematic differences in genetic allele frequencies across the genome, a phenomenon known as population stratification or substructure. If a phenotypic trait such as disease is associated with subpopulation membership, a genetic association study can identify spurious relationships with genetic markers. Singular value decomposition (SVD) of genotype data or eigen decomposition of covariance matrices can be used to identify population stratification. The eigenvectors (essentially principal component scores) that correspond to large eigenvalues can be used as covariates in association analysis (Levine et al., ). The combined analysis of unrelated and related individuals is a common feature of genetic association studies (Zhu et al., ). However, the presence of close‐degree relatives in a genetic dataset presents difficulties, as the family structure can greatly influence the eigenvalues and eigenvectors.Cystic fibrosis (CF) is a recessive genetic lung disorder, caused by a mutation in the single gene CFTR. However, considerable genetic variation remains in the severity of disease, and evidence indicates this variation is complex and influenced by numerous genes (Wright et al., ). Genotypes gathered by the North American CF Consortium are typical of a large‐scale genomewide association study (GWAS), with thousands of individuals and over 1

Journal

BiometricsWiley

Published: Jan 1, 2018

Keywords: ; ;

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from Google Scholar, PubMed
Create lists to organize your research
Export lists, citations
Access to DeepDyve database
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off