Literature DB >> 19568925

Novel sib pair selection strategy increases power in quantitative association analysis.

Johnny S H Kwan1, Stacey S Cherny, Annie W C Kung, Pak C Sham.   

Abstract

Quantitative-trait association studies have been widely used in search for genetic loci for complex traits in recent years. Yet, fiscal constraints still prohibit many on-going research projects from recruiting a large number of individuals for genotyping to reach a desired level of statistical power. Accordingly, in this article, we describe a novel sib pair sampling strategy for genotyping in QTL association studies. With the use of phenotypic scores (and IBD allele-sharing probabilities if available), the genetic effect of a biallelic additive trait locus can be properly modelled within the maximum-likelihood variance components framework proposed by Fulker et al. (Am J Hum Genet 64(1):259-267, 1999) and sib pairs can be rank-ordered by use of informativeness indices. The performance of our method was investigated using simulation. The power of our approach was shown to be higher when compared with other phenotypic selection schemes. An R-script implementing all the selection approaches (including the traditional phenotype-based ones) used in the simulation is available at http://statgen.hku.hk/jshkwan .

Mesh:

Year:  2009        PMID: 19568925     DOI: 10.1007/s10519-009-9284-x

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


  3 in total

1.  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 2.  Statistical power and significance testing in large-scale genetic studies.

Authors:  Pak C Sham; Shaun M Purcell
Journal:  Nat Rev Genet       Date:  2014-05       Impact factor: 53.242

3.  A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

Authors:  Johnny S H Kwan; Annie W C Kung; Pak C Sham
Journal:  Behav Genet       Date:  2011-05-29       Impact factor: 2.805

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.