Literature DB >> 7993321

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

L Eaves1, J Meyer.   

Abstract

Simulation studies were conducted to assess the relative merits of different nonrandom sampling strategies for the selection of sibling pairs for genotyping in the attempt to locate individual loci (QTLs) contributing to variation in human quantitative traits. For a constant amount of variation contributed by a QTL (25% of the total) the frequencies and dominance relationships of a trait increasing allele were varied. Three strategies for selection of pairs for genotyping were based on the phenotypic values of the siblings: "Concordant sib pairs" (CSP) are pairs in which both individuals exceed a given threshold value; "discordant sib pairs" (DSP) are pairs in which one member exceeds a given upper threshold and the other is below a specified lower threshold; and "most similar pairs" (MSP) are pairs selected for falling below a specified percentile ranking of the within-pair mean square for the quantitative trait. Tests for linkage with markers at 1, 2, 5, 10, and 20 cM from each of the QTLs were conducted for each of the selected samples and compared with tests based on the regression, in the entire sample, of within pair variation on the proportion of alleles identical by descent (IBD) at each marker locus. Tests for the effect of the increasing allele at the QTL ("candidate gene") were also conducted for the DSP pairs. No single nonrandom selection procedure yields as much as half the information realized in the total sample. However, a combined strategy which involves genotyping the 5% of MSP and DSP for the upper and lower quintiles of values of the quantitative trait (a further 3% of the sample approximately) yields lod scores which are usually more than 65% of the values realized for the entire sample. Tests comparing the proportion of increasing alleles in high- and low-scoring siblings from DSP samples are uniformly very powerful for detecting candidate loci. Even when it is not possible to measure the entire range of the phenotype with uniform precision, some attempt to differentiate among individuals in a common "unaffected" class of individuals can lead to considerable increase in power.

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Year:  1994        PMID: 7993321     DOI: 10.1007/BF01076180

Source DB:  PubMed          Journal:  Behav Genet        ISSN: 0001-8244            Impact factor:   2.805


  1 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

  1 in total
  29 in total

1.  Testing the robustness of the likelihood-ratio test in a variance-component quantitative-trait loci-mapping procedure.

Authors:  D B Allison; M C Neale; R Zannolli; N J Schork; C I Amos; J Blangero
Journal:  Am J Hum Genet       Date:  1999-08       Impact factor: 11.025

2.  Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data.

Authors:  P C Sham; S S Cherny; S Purcell; J K Hewitt
Journal:  Am J Hum Genet       Date:  2000-04-12       Impact factor: 11.025

3.  Sampling strategies for model free linkage analyses of quantitative traits: implications for sib pair studies of reading and spelling disabilities to minimize the total study cost.

Authors:  A Ziegler
Journal:  Eur Child Adolesc Psychiatry       Date:  1999       Impact factor: 4.785

4.  Nonpaternity in linkage studies of extremely discordant sib pairs.

Authors:  Michael C Neale; Benjamin M Neale; Patrick F Sullivan
Journal:  Am J Hum Genet       Date:  2001-12-14       Impact factor: 11.025

5.  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

6.  The power to detect linkage disequilibrium with quantitative traits in selected samples.

Authors:  G R Abecasis; W O Cookson; L R Cardon
Journal:  Am J Hum Genet       Date:  2001-05-08       Impact factor: 11.025

7.  Sibling-based tests of linkage and association for quantitative traits.

Authors:  D B Allison; M Heo; N Kaplan; E R Martin
Journal:  Am J Hum Genet       Date:  1999-06       Impact factor: 11.025

8.  Linkage analysis of extremely discordant and concordant sibling pairs identifies quantitative-trait loci that influence variation in the human personality trait neuroticism.

Authors:  Jan Fullerton; Matthew Cubin; Hemant Tiwari; Chenxi Wang; Amarjit Bomhra; Stuart Davidson; Sue Miller; Christopher Fairburn; Guy Goodwin; Michael C Neale; Simon Fiddy; Richard Mott; David B Allison; Jonathan Flint
Journal:  Am J Hum Genet       Date:  2003-02-20       Impact factor: 11.025

9.  Evidence of linkage of HDL level variation to APOC3 in two samples with different ascertainment.

Authors:  France Gagnon; Gail P Jarvik; Arno G Motulsky; Samir S Deeb; John D Brunzell; Ellen M Wijsman
Journal:  Hum Genet       Date:  2003-08-29       Impact factor: 4.132

Review 10.  Genetic epidemiological approaches in the study of risk factors for cardiovascular disease.

Authors:  Anastasia Iliadou; Harold Snieder
Journal:  Eur J Epidemiol       Date:  2004       Impact factor: 8.082

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