Literature DB >> 22128053

Detecting multiple causal rare variants in exome sequence data.

Kenny Q Ye1, Corinne D Engelman.   

Abstract

Recent advances in sequencing technology have presented both opportunities and challenges, with limited statistical power to detect a single causal rare variant with practical sample sizes. To overcome this, the contributors to Group 1 of Genetic Analysis Workshop 17 sought to develop methods to detect the combined signal of multiple causal rare variants in a biologically meaningful way. The contributors used genes, genome location proximity, or genetic pathways as the basic unit in combining the information from multiple variants. Weaknesses of the exome sequence data and the relative strengths and weaknesses of the five approaches are discussed.
© 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 22128053      PMCID: PMC3271433          DOI: 10.1002/gepi.20644

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


  8 in total

1.  Genetic Analysis Workshop 17 mini-exome simulation.

Authors:  Laura Almasy; Thomas D Dyer; Juan Manuel Peralta; Jack W Kent; Jac C Charlesworth; Joanne E Curran; John Blangero
Journal:  BMC Proc       Date:  2011-11-29

2.  Identification of genes and variants associated with quantitative traits using Bayesian factor screening.

Authors:  Kith Pradhan; Seungtai Chris Yoon; Tao Wang; Kenny Ye
Journal:  BMC Proc       Date:  2011-11-29

3.  A weighted accumulation test for associating rare genetic variation with quantitative phenotypes.

Authors:  Chuanhua Xing; Glen A Satten; Andrew S Allen
Journal:  BMC Proc       Date:  2011-11-29

4.  Genome-wide association analysis of GAW17 data using an empirical Bayes variable selection.

Authors:  Vitara Pungpapong; Libo Wang; Yanzhu Lin; Dabao Zhang; Min Zhang
Journal:  BMC Proc       Date:  2011-11-29

5.  Identifying influential regions in extremely rare variants using a fixed-bin approach.

Authors:  Michael Agne; Chien-Hsun Huang; Inchi Hu; Haitian Wang; Tian Zheng; Shaw-Hwa Lo
Journal:  BMC Proc       Date:  2011-11-29

6.  A gene-based approach for testing association of rare alleles.

Authors:  Hongyan Xu; Varghese George
Journal:  BMC Proc       Date:  2011-11-29

7.  A groupwise association test for rare mutations using a weighted sum statistic.

Authors:  Bo Eskerod Madsen; Sharon R Browning
Journal:  PLoS Genet       Date:  2009-02-13       Impact factor: 5.917

8.  Case-control genome-wide association study of rheumatoid arthritis from Genetic Analysis Workshop 16 using penalized orthogonal-components regression-linear discriminant analysis.

Authors:  Min Zhang; Yanzhu Lin; Libo Wang; Vitara Pungpapong; James C Fleet; Dabao Zhang
Journal:  BMC Proc       Date:  2009-12-15
  8 in total
  4 in total

Review 1.  The value of extended pedigrees for next-generation analysis of complex disease in the rhesus macaque.

Authors:  Amanda Vinson; Kamm Prongay; Betsy Ferguson
Journal:  ILAR J       Date:  2013

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.  Lessons learned from Genetic Analysis Workshop 17: transitioning from genome-wide association studies to whole-genome statistical genetic analysis.

Authors:  Alexander F Wilson; Andreas Ziegler
Journal:  Genet Epidemiol       Date:  2011       Impact factor: 2.135

4.  Considering interactive effects in the identification of influential regions with extremely rare variants via fixed bin approach.

Authors:  Michael Agne; Chien-Hsun Huang; Inchi Hu; Haitian Wang; Tian Zheng; Shaw-Hwa Lo
Journal:  BMC Proc       Date:  2014-06-17
  4 in total

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