Literature DB >> 19924715

Phenotype definition and development--contributions from Group 7.

Marsha A Wilcox1, Andrew D Paterson.   

Abstract

The papers in Genetic Analysis Workshop 16 Group 7 covered a wide range of topics. The effects of confounder misclassification and selection bias on association results were examined by one group. Another focused on bias introduced by various methods of accounting for treatment effects. Two groups used related methods to derive phenotypic traits. They used different analytic strategies for genetic associations with non-overlapping results (but because they used different sets of single-nucleotide polymorphisms (SNPs) and significance criteria, this is not surprising). Another group relied on the well-characterized definition of type 2 diabetes to show benefits of a novel predictive test. Transmission-ratio distortion was the focus of another paper. The results were extended to show a potential secondary benefit of the test to identify potentially mis-called SNPs. (c) 2009 Wiley-Liss, Inc.

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Year:  2009        PMID: 19924715      PMCID: PMC3033653          DOI: 10.1002/gepi.20471

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


  19 in total

1.  Sample size requirements for association studies of gene-gene interaction.

Authors:  W James Gauderman
Journal:  Am J Epidemiol       Date:  2002-03-01       Impact factor: 4.897

Review 2.  An overview of relations among causal modelling methods.

Authors:  Sander Greenland; Babette Brumback
Journal:  Int J Epidemiol       Date:  2002-10       Impact factor: 7.196

Review 3.  Transmission ratio distortion in mice.

Authors:  Mary F Lyon
Journal:  Annu Rev Genet       Date:  2003       Impact factor: 16.830

4.  Using the optimal receiver operating characteristic curve to design a predictive genetic test, exemplified with type 2 diabetes.

Authors:  Qing Lu; Robert C Elston
Journal:  Am J Hum Genet       Date:  2008-03       Impact factor: 11.025

5.  Evidence for a gene influencing blood pressure on chromosome 17. Genome scan linkage results for longitudinal blood pressure phenotypes in subjects from the framingham heart study.

Authors:  D Levy; A L DeStefano; M G Larson; C J O'Donnell; R P Lifton; H Gavras; L A Cupples; R H Myers
Journal:  Hypertension       Date:  2000-10       Impact factor: 10.190

6.  Identification and characterization of metabolically benign obesity in humans.

Authors:  Norbert Stefan; Konstantinos Kantartzis; Jürgen Machann; Fritz Schick; Claus Thamer; Kilian Rittig; Bernd Balletshofer; Fausto Machicao; Andreas Fritsche; Hans-Ulrich Häring
Journal:  Arch Intern Med       Date:  2008-08-11

7.  Genome-wide association study for empirically derived metabolic phenotypes in the Framingham Heart Study offspring cohort.

Authors:  Marsha Wilcox; Qingqin Li; Yu Sun; Paul Stang; Jesse Berlin; Dai Wang
Journal:  BMC Proc       Date:  2009-12-15

8.  Genome-wide association analysis of Framingham Heart Study data for the Genetics Analysis Workshop 16: effects due to medication use.

Authors:  Treva K Rice; Yun Ju Sung; Gang Shi; C Charles Gu; Dc Rao
Journal:  BMC Proc       Date:  2009-12-15

9.  Genetics Analysis Workshop 16 Problem 2: the Framingham Heart Study data.

Authors:  L Adrienne Cupples; Nancy Heard-Costa; Monica Lee; Larry D Atwood
Journal:  BMC Proc       Date:  2009-12-15

10.  Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.

Authors:  Michael N Weedon; Mark I McCarthy; Graham Hitman; Mark Walker; Christopher J Groves; Eleftheria Zeggini; N William Rayner; Beverley Shields; Katharine R Owen; Andrew T Hattersley; Timothy M Frayling
Journal:  PLoS Med       Date:  2006-10       Impact factor: 11.069

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  1 in total

1.  Genome wide association studies in presence of misclassified binary responses.

Authors:  Shannon Smith; El Hamidi Hay; Nourhene Farhat; Romdhane Rekaya
Journal:  BMC Genet       Date:  2013-12-26       Impact factor: 2.797

  1 in total

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