Literature DB >> 15785775

Complex trait mapping in isolated populations: Are specific statistical methods required?

Catherine Bourgain1, Emmanuelle Génin.   

Abstract

In this paper, we review the statistical methods that can be used in isolated populations to map genes involved in complex diseases. Our intention is to highlight the fact that if the features of population isolates may help in the identification of susceptibility factors for complex traits, the choice and design of methods for statistical analysis in these populations deserve particular care. We show that methods designed for outbred samples are generally not appropriate for isolated populations and could lead to false conclusions.

Mesh:

Year:  2005        PMID: 15785775     DOI: 10.1038/sj.ejhg.5201400

Source DB:  PubMed          Journal:  Eur J Hum Genet        ISSN: 1018-4813            Impact factor:   4.246


  14 in total

1.  Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population.

Authors:  Eimear E Kenny; Minseung Kim; Alexander Gusev; Jennifer K Lowe; Jacqueline Salit; J Gustav Smith; Sirisha Kovvali; Hyun Min Kang; Christopher Newton-Cheh; Mark J Daly; Markus Stoffel; David M Altshuler; Jeffrey M Friedman; Eleazar Eskin; Jan L Breslow; Itsik Pe'er
Journal:  Hum Mol Genet       Date:  2010-11-30       Impact factor: 6.150

2.  Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis.

Authors:  Yurii S Aulchenko; Dirk-Jan de Koning; Chris Haley
Journal:  Genetics       Date:  2007-07-29       Impact factor: 4.562

3.  Campora: a young genetic isolate in South Italy.

Authors:  Vincenza Colonna; Teresa Nutile; Maria Astore; Ombretta Guardiola; Giuliano Antoniol; Marina Ciullo; M Graziella Persico
Journal:  Hum Hered       Date:  2007-05-02       Impact factor: 0.444

4.  Identity-by-descent estimation and mapping of qualitative traits in large, complex pedigrees.

Authors:  Mark Abney
Journal:  Genetics       Date:  2008-07-13       Impact factor: 4.562

5.  Comparing population structure as inferred from genealogical versus genetic information.

Authors:  Vincenza Colonna; Teresa Nutile; Ronald R Ferrucci; Giulio Fardella; Mario Aversano; Guido Barbujani; Marina Ciullo
Journal:  Eur J Hum Genet       Date:  2009-06-24       Impact factor: 4.246

6.  HapMap tagSNP transferability in multiple populations: general guidelines.

Authors:  Jinchuan Xing; David J Witherspoon; W Scott Watkins; Yuhua Zhang; Whitney Tolpinrud; Lynn B Jorde
Journal:  Genomics       Date:  2008-05-14       Impact factor: 5.736

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.  Population-based and family-based designs to analyze rare variants in complex diseases.

Authors:  Rémi Kazma; Julia N Bailey
Journal:  Genet Epidemiol       Date:  2011       Impact factor: 2.135

9.  Permutation testing in the presence of polygenic variation.

Authors:  Mark Abney
Journal:  Genet Epidemiol       Date:  2015-03-10       Impact factor: 2.135

10.  Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae.

Authors:  Jennifer K Lowe; Julian B Maller; Itsik Pe'er; Benjamin M Neale; Jacqueline Salit; Eimear E Kenny; Jessica L Shea; Ralph Burkhardt; J Gustav Smith; Weizhen Ji; Martha Noel; Jia Nee Foo; Maude L Blundell; Vita Skilling; Laura Garcia; Marcia L Sullivan; Heather E Lee; Anna Labek; Hope Ferdowsian; Steven B Auerbach; Richard P Lifton; Christopher Newton-Cheh; Jan L Breslow; Markus Stoffel; Mark J Daly; David M Altshuler; Jeffrey M Friedman
Journal:  PLoS Genet       Date:  2009-02-06       Impact factor: 5.917

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