Literature DB >> 7896296

The affected-pedigree-member method: power to detect linkage.

D E Weeks1, L D Harby.   

Abstract

The affected-pedigree-member (APM) method of linkage analysis is a nonparametric statistic for testing for nonindependent segregation of a marker to affected members of a pedigree. We present here results of a simulation study evaluating the power of the APM method to detect linkage. We have systematically explored, by computer simulation, the effect of a variety of factors on the power to detect linkage using the single-locus APM statistic. These factors include mode of inheritance, marker polymorphism, the distance between marker and disease, phenocopy rate, heterogeneity, and misspecified marker allele frequencies. We also evaluated the relative power obtained under fixed-structure sampling and sequential sampling. For a dominant disease, sequential sampling led to increased power as compared to fixed-structure sampling, while for a recessive disease, there was no clear advantage in sampling beyond nuclear families.

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Mesh:

Year:  1995        PMID: 7896296     DOI: 10.1159/000154250

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  4 in total

1.  Affecteds-only linkage methods are not a panacea.

Authors:  D A Greenberg; S E Hodge; V J Vieland; M A Spence
Journal:  Am J Hum Genet       Date:  1996-04       Impact factor: 11.025

2.  Parametric and nonparametric linkage analysis: a unified multipoint approach.

Authors:  L Kruglyak; M J Daly; M P Reeve-Daly; E S Lander
Journal:  Am J Hum Genet       Date:  1996-06       Impact factor: 11.025

3.  An efficient method to handle the 'large p, small n' problem for genomewide association studies using Haseman-Elston regression.

Authors:  Bujun Mei; Zhihua Wang
Journal:  J Genet       Date:  2016-12       Impact factor: 1.166

4.  Noncoding mutations of HGF are associated with nonsyndromic hearing loss, DFNB39.

Authors:  Julie M Schultz; Shaheen N Khan; Zubair M Ahmed; Saima Riazuddin; Ali M Waryah; Dhananjay Chhatre; Matthew F Starost; Barbara Ploplis; Stephanie Buckley; David Velásquez; Madhulika Kabra; Kwanghyuk Lee; Muhammad J Hassan; Ghazanfar Ali; Muhammad Ansar; Manju Ghosh; Edward R Wilcox; Wasim Ahmad; Glenn Merlino; Suzanne M Leal; Sheikh Riazuddin; Thomas B Friedman; Robert J Morell
Journal:  Am J Hum Genet       Date:  2009-07-02       Impact factor: 11.025

  4 in total

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