Literature DB >> 12432507

Impact of parental relationships in maximum lod score affected sib-pair method.

Anne-Louise Leutenegger1, Emmanuelle Génin, Elizabeth A Thompson, Françoise Clerget-Darpoux.   

Abstract

Many studies are done in small isolated populations and populations where marriages between relatives are encouraged. In this paper, we point out some problems with applying the maximum lod score (MLS) method (Risch, [1990] Am. J. Hum. Genet. 46:242-253) in these populations where relationships exist between the two parents of the affected sib-pairs. Characterizing the parental relationships by the kinship coefficient between the parents (f), the maternal inbreeding coefficient (alpha(m), and the paternal inbreeding coefficient (alpha(p)), we explored the relationship between the identity by descent (IBD) vector expected under the null hypothesis of no linkage and these quantities. We find that the expected IBD vector is no longer (0.25, 0.5, 0.25) when f, alpha(m), and alpha(p) differ from zero. In addition, the expected IBD vector does not always follow the triangle constraints recommended by Holmans ([1993] Am. J. Hum. Genet. 52:362-374). So the classically used MLS statistic needs to be adapted to the presence of parental relationships. We modified the software GENEHUNTER (Kruglyak et al. [1996] Am. J. Hum. Genet. 58: 1347-1363) to do so. Indeed, the current version of the software does not compute the likelihood properly under the null hypothesis. We studied the adapted statistic by simulating data on three different family structures: (1) parents are double first cousins (f=0.125, alpha(m)=alpha(p)=0), (2) each parent is the offspring of first cousins (f=0, alpha(m)=alpha(p)=0.0625), and (3) parents are related as in the pedigree from Goddard et al. ([1996] Am. J. Hum. Genet. 58:1286-1302) (f=0.109, alpha(m)=alpha(p)=0.0625). The appropriate threshold needs to be derived for each case in order to get the correct type I error. And using the classical statistic in the presence of both parental kinship and parental inbreeding almost always leads to false conclusions. Copyright 2002 Wiley-Liss, Inc.

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Year:  2002        PMID: 12432507     DOI: 10.1002/gepi.10190

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  11 in total

1.  Estimation of the inbreeding coefficient through use of genomic data.

Authors:  Anne-Louise Leutenegger; Bernard Prum; Emmanuelle Génin; Christophe Verny; Arnaud Lemainque; Françoise Clerget-Darpoux; Elizabeth A Thompson
Journal:  Am J Hum Genet       Date:  2003-07-29       Impact factor: 11.025

2.  Transmission-ratio distortion and allele sharing in affected sib pairs: a new linkage statistic with reduced bias, with application to chromosome 6q25.3.

Authors:  Mathieu Lemire; Nicole M Roslin; Catherine Laprise; Thomas J Hudson; Kenneth Morgan
Journal:  Am J Hum Genet       Date:  2004-08-20       Impact factor: 11.025

3.  Mathematical assumptions versus biological reality: myths in affected sib pair linkage analysis.

Authors:  Robert C Elston; Danhong Song; Sudha K Iyengar
Journal:  Am J Hum Genet       Date:  2004-11-11       Impact factor: 11.025

4.  Variance calculations for identity-by-descent estimation.

Authors:  Matthew B McQueen; Deborah Blacker; Nan M Laird
Journal:  Am J Hum Genet       Date:  2006-03-29       Impact factor: 11.025

5.  Ignoring intermarker linkage disequilibrium induces false-positive evidence of linkage for consanguineous pedigrees when genotype data is missing for any pedigree member.

Authors:  Bingshan Li; Suzanne M Leal
Journal:  Hum Hered       Date:  2007-12-11       Impact factor: 0.444

6.  Applying novel genome-wide linkage strategies to search for loci influencing type 2 diabetes and adult height in American Samoa.

Authors:  Karolina Aberg; Guangyun Sun; Diane Smelser; Subba Rao Indugula; Hui-Ju Tsai; Matthew S Steele; John Tuitele; Ranjan Deka; Stephen T McGarvey; Daniel E Weeks
Journal:  Hum Biol       Date:  2008-04       Impact factor: 0.553

7.  Identification of novel susceptibility loci for Guam neurodegenerative disease: challenges of genome scans in genetic isolates.

Authors:  Weiva Sieh; Yoonha Choi; Nicola H Chapman; Ulla-Katrina Craig; Ellen J Steinbart; Joseph H Rothstein; Kiyomitsu Oyanagi; Ralph M Garruto; Thomas D Bird; Douglas R Galasko; Gerard D Schellenberg; Ellen M Wijsman
Journal:  Hum Mol Genet       Date:  2009-06-30       Impact factor: 6.150

8.  Using genomic inbreeding coefficient estimates for homozygosity mapping of rare recessive traits: application to Taybi-Linder syndrome.

Authors:  Anne-Louise Leutenegger; Audrey Labalme; Emmanuelle Genin; Annick Toutain; Elisabeth Steichen; Francoise Clerget-Darpoux; Patrick Edery
Journal:  Am J Hum Genet       Date:  2006-04-28       Impact factor: 11.025

9.  Linkage analysis without defined pedigrees.

Authors:  Aaron G Day-Williams; John Blangero; Thomas D Dyer; Kenneth Lange; Eric M Sobel
Journal:  Genet Epidemiol       Date:  2011-04-04       Impact factor: 2.135

10.  Classification and regression tree and spatial analyses reveal geographic heterogeneity in genome wide linkage study of Indian visceral leishmaniasis.

Authors:  Michaela Fakiola; Anshuman Mishra; Madhukar Rai; Shri Prakash Singh; Rebecca A O'Leary; Stephen Ball; Richard W Francis; Martin J Firth; Ben T Radford; E Nancy Miller; Shyam Sundar; Jenefer M Blackwell
Journal:  PLoS One       Date:  2010-12-31       Impact factor: 3.240

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