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PMID: 9837840 Published · ppublish English Comparative Study Journal Article Research Support, U.S. Gov't, P.H.S.

A discordant-sibship test for disequilibrium and linkage: no need for parental data.

American journal of human genetics ·Vol. 63 ·No. 6 ·1998-12-00 ·Pages 1886-97

Horvath S, Laird NM

Abstract

The sibship disequilibrium test (SDT) is designed to detect both linkage in the presence of association and association in the presence of linkage (linkage disequilibrium). The test does not require parental data but requires discordant sibships with at least one affected and one unaffected sibling. The SDT has many desirable properties: it uses all the siblings in the sibship; it remains valid if there are misclassifications of the affectation status; it does not detect spurious associations due to population stratification; asymptotically it has a chi2 distribution under the null hypothesis; and exact P values can be easily computed for a biallelic marker. We show how to extend the SDT to markers with multiple alleles and how to combine families with parents and data from discordant sibships. We discuss the power of the test by presenting sample-size calculations involving a complex disease model, and we present formulas for the asymptotic relative efficiency (which is approximately the ratio of sample sizes) between SDT and the transmission/disequilibrium test (TDT) for special family structures. For sib pairs, we compare the SDT to a test proposed both by Curtis and, independently, by Spielman and Ewens. We show that, for discordant sib pairs, the SDT has good power for testing linkage disequilibrium relative both to Curtis's tests and to the TDT using trios comprising an affected sib and its parents. With additional sibs, we show that the SDT can be more powerful than the TDT for testing linkage disequilibrium, especially for disease prevalence >.3.

MeSH Terms
Alleles Female Genetic Linkage/genetics Genetic Markers Genetic Testing Genotype Humans Linkage Disequilibrium Male Nuclear Family Parents Sample Size Statistics, Nonparametric
Chemicals
Genetic Markers
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Horvath S
Department of Biostatistics, Harvard School of Public Health, Boston, USA.
Laird N M
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Article Info
Journal
American journal of human genetics
Abbr.
Am J Hum Genet
ISSN
0002-9297
Published
1998-12-00
Pages
1886-97
Language
English
Region
United States
NLM ID
0370475
PMCID
PMC1377659
Subset
IM
Grants
NIGMS NIH HHS · GM29745 · United States
NIMH NIH HHS · MH59536 · United States
Corrections
CommentIn
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