Literature DB >> 22128065

Detecting rare variant associations: methods for testing haplotypes and multiallelic genotypes.

Rita M Cantor1, Marsha Wilcox.   

Abstract

We summarize the work done by the contributors to Group 13 at Genetic Analysis Workshop 17 (GAW17) and provide a synthesis of their data analyses. The Group 13 contributors used a variety of approaches to test associations of both rare variants and common single-nucleotide polymorphisms (SNPs) with the GAW17 simulated traits, implementing analytic methods that incorporate multiallelic genotypes and haplotypes. In addition to using a wide variety of statistical methods and approaches, the contributors exhibited a remarkable amount of flexibility and creativity in coding the variants and their genes and in evaluating their proposed approaches and methods. We describe and contrast their methods along three dimensions: (1) selection and coding of genetic entities for analysis, (2) method of analysis, and (3) evaluation of the results. The contributors consistently presented a strong rationale for using multiallelic analytic approaches. They indicated that power was likely to be increased by capturing the signals of multiple markers within genetic entities defined by sliding windows, haplotypes, genes, functional pathways, and the entire set of SNPs and rare variants taken in aggregate. Despite this variability, the methods were fairly consistent in their ability to identify two associated genes for each simulated trait. The first gene was selected for the largest number of causal alleles and the second for a high-frequency causal SNP. The presumed model of inheritance and choice of genetic entities are likely to have a strong effect on the outcomes of the analyses.
© 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 22128065      PMCID: PMC3274416          DOI: 10.1002/gepi.20656

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


  11 in total

Review 1.  Statistical analysis of rare sequence variants: an overview of collapsing methods.

Authors:  Carmen Dering; Claudia Hemmelmann; Elizabeth Pugh; Andreas Ziegler
Journal:  Genet Epidemiol       Date:  2011       Impact factor: 2.135

2.  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

3.  Identifying rare variants using a Bayesian regression approach.

Authors:  Aimin Yan; Nan M Laird; Cheng Li
Journal:  BMC Proc       Date:  2011-11-29

4.  Analysis of human mini-exome sequencing data from Genetic Analysis Workshop 17 using a Bayesian hierarchical mixture model.

Authors:  Julio S Bueno Filho; Gota Morota; Quoc Tran; Matthew J Maenner; Lina M Vera-Cala; Corinne D Engelman; Kristin J Meyers
Journal:  BMC Proc       Date:  2011-11-29

5.  Detecting disease rare alleles using single SNPs in families and haplotyping in unrelated subjects from the Genetic Analysis Workshop 17 data.

Authors:  Aldi T Kraja; Jacek Czajkowski; Mary F Feitosa; Ingrid B Borecki; Michael A Province
Journal:  BMC Proc       Date:  2011-11-29

6.  Rare variant collapsing in conjunction with mean log p-value and gradient boosting approaches applied to Genetic Analysis Workshop 17 data.

Authors:  Yauheniya Cherkas; Nandini Raghavan; Stephan Francke; Frank Defalco; Marsha A Wilcox
Journal:  BMC Proc       Date:  2011-11-29

7.  Search for compound heterozygous effects in exome sequence of unrelated subjects.

Authors:  G Bryce Christensen; Christophe G Lambert
Journal:  BMC Proc       Date:  2011-11-29

8.  Penalized-regression-based multimarker genotype analysis of Genetic Analysis Workshop 17 data.

Authors:  Kristin L Ayers; Chrysovalanto Mamasoula; Heather J Cordell
Journal:  BMC Proc       Date:  2011-11-29

9.  Addition of multiple rare SNPs to known common variants improves the association between disease and gene in the Genetic Analysis Workshop 17 data.

Authors:  Jenna Sykes; Lu Cheng; Wei Xu; Ming-Sound Tsao; Geoffrey Liu; Melania Pintilie
Journal:  BMC Proc       Date:  2011-11-29

10.  Finding genes that influence quantitative traits with tree-based clustering.

Authors:  Ian J Wilson; Richard Aj Howey; Darren T Houniet; Mauro Santibanez-Koref
Journal:  BMC Proc       Date:  2011-11-29
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  1 in total

1.  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

  1 in total

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