Literature DB >> 9246001

A linkage strategy for detection of human quantitative-trait loci. I. Generalized relative risk ratios and power of sib pairs with extreme trait values.

C Gu1, D C Rao.   

Abstract

We generalize the concept of the relative risk ratio (lambda) to the case of quantitative traits, to take into account the various trait outcomes of a relative pair. Formulas are derived to express the expected proportions of genes shared identical by descent by a sib pair, in terms of the generalized lambda's for sib pairs (lambda S), parent-offspring pairs (lambda O), and monozygotic twins (lambda M) and in terms of the recombination fraction, with the assumption of no residual correlations. If residual correlations are nonzero among relative pairs, we assume that they are the same among sib pairs, parent-offspring pairs, and monozygotic twins, and we employ a slightly different definition for the generalized lambda so that the same set of formulas still hold. The power (or, the sample size necessary) to detect quantitative-trait loci (QTLs) by use of extreme sib pairs (ESPs) is shown to be a function of the three generalized lambda's. Since lambda M can be derived by use of values of lambda S and lambda O, estimates of the latter two lambda's will suffice for the analysis of power and the necessary sample sizes of ESPs, for a QTL linkage study.

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Year:  1997        PMID: 9246001      PMCID: PMC1715852          DOI: 10.1086/513908

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  9 in total

1.  Linkage analysis of quantitative traits: increased power by using selected samples.

Authors:  G Carey; J Williamson
Journal:  Am J Hum Genet       Date:  1991-10       Impact factor: 11.025

2.  Linkage strategies for genetically complex traits. I. Multilocus models.

Authors:  N Risch
Journal:  Am J Hum Genet       Date:  1990-02       Impact factor: 11.025

3.  Linkage strategies for genetically complex traits. II. The power of affected relative pairs.

Authors:  N Risch
Journal:  Am J Hum Genet       Date:  1990-02       Impact factor: 11.025

4.  A linkage strategy for detection of human quantitative-trait loci. II. Optimization of study designs based on extreme sib pairs and generalized relative risk ratios.

Authors:  C Gu; D C Rao
Journal:  Am J Hum Genet       Date:  1997-07       Impact factor: 11.025

5.  Frequency in relatives for an all-or-none trait.

Authors:  J W James
Journal:  Ann Hum Genet       Date:  1971-07       Impact factor: 1.670

6.  Combining extremely concordant sibpairs with extremely discordant sibpairs provides a cost effective way to linkage analysis of quantitative trait loci.

Authors:  C Gu; A Todorov; D C Rao
Journal:  Genet Epidemiol       Date:  1996       Impact factor: 2.135

7.  Extreme discordant sib pairs for mapping quantitative trait loci in humans.

Authors:  N Risch; H Zhang
Journal:  Science       Date:  1995-06-16       Impact factor: 47.728

8.  Locating human quantitative trait loci: guidelines for the selection of sibling pairs for genotyping.

Authors:  L Eaves; J Meyer
Journal:  Behav Genet       Date:  1994-09       Impact factor: 2.805

9.  The generalized sib pair IBD distribution: its use in the detection of linkage.

Authors:  B K Suarez; J Rice; T Reich
Journal:  Ann Hum Genet       Date:  1978-07       Impact factor: 1.670

  9 in total
  7 in total

1.  The relationship between the sibling recurrence-risk ratio and genotype relative risk.

Authors:  B A Rybicki; R C Elston
Journal:  Am J Hum Genet       Date:  2000-02       Impact factor: 11.025

2.  Seven regions of the genome show evidence of linkage to type 1 diabetes in a consensus analysis of 767 multiplex families.

Authors:  N J Cox; B Wapelhorst; V A Morrison; L Johnson; L Pinchuk; R S Spielman; J A Todd; P Concannon
Journal:  Am J Hum Genet       Date:  2001-08-15       Impact factor: 11.025

3.  Considerations on study designs using the extreme sibpairs methods under multilocus oligogenic models.

Authors:  Chi Gu; D C Rao
Journal:  Genetics       Date:  2002-04       Impact factor: 4.562

4.  A unified framework for detecting rare variant quantitative trait associations in pedigree and unrelated individuals via sequence data.

Authors:  Dajiang J Liu; Suzanne M Leal
Journal:  Hum Hered       Date:  2012-04-28       Impact factor: 0.444

Review 5.  Genomics and genetics in the biology of adaptation to exercise.

Authors:  Claude Bouchard; Tuomo Rankinen; James A Timmons
Journal:  Compr Physiol       Date:  2011-07       Impact factor: 9.090

6.  Identification of an acute ethanol response quantitative trait locus on mouse chromosome 2.

Authors:  K Demarest; J McCaughran; E Mahjubi; L Cipp; R Hitzemann
Journal:  J Neurosci       Date:  1999-01-15       Impact factor: 6.167

7.  A linkage strategy for detection of human quantitative-trait loci. II. Optimization of study designs based on extreme sib pairs and generalized relative risk ratios.

Authors:  C Gu; D C Rao
Journal:  Am J Hum Genet       Date:  1997-07       Impact factor: 11.025

  7 in total

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