Literature DB >> 21121035

An application and empirical comparison of statistical analysis methods for associating rare variants to a complex phenotype.

Vikas Bansal1, Ondrej Libiger, Ali Torkamani, Nicholas J Schork.   

Abstract

The contribution of collections of rare sequence variations (or 'variants') to phenotypic expression has begun to receive considerable attention within the biomedical research community. However, the best way to capture the effects of rare variants in relevant statistical analysis models is an open question. In this paper we describe the application of a number of statistical methods for testing associations between rare variants in two genes to obesity. We consider the relative merits of the different methods as well as important implementation details, such as the leveraging of genomic annotations and determining p-values.

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Year:  2011        PMID: 21121035      PMCID: PMC5017238          DOI: 10.1142/9789814335058_0009

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  23 in total

1.  Genetic analysis of case/control data using estimated haplotype frequencies: application to APOE locus variation and Alzheimer's disease.

Authors:  D Fallin; A Cohen; L Essioux; I Chumakov; M Blumenfeld; D Cohen; N J Schork
Journal:  Genome Res       Date:  2001-01       Impact factor: 9.043

2.  Model-free analysis and permutation tests for allelic associations.

Authors:  J H Zhao; D Curtis; P C Sham
Journal:  Hum Hered       Date:  2000 Mar-Apr       Impact factor: 0.444

3.  Sequence analysis using logic regression.

Authors:  C Kooperberg; I Ruczinski; M L LeBlanc; L Hsu
Journal:  Genet Epidemiol       Date:  2001       Impact factor: 2.135

Review 4.  Mathematical multi-locus approaches to localizing complex human trait genes.

Authors:  Josephine Hoh; Jurg Ott
Journal:  Nat Rev Genet       Date:  2003-09       Impact factor: 53.242

5.  A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other.

Authors:  Dale R Nyholt
Journal:  Am J Hum Genet       Date:  2004-03-02       Impact factor: 11.025

6.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

7.  Generalized genomic distance-based regression methodology for multilocus association analysis.

Authors:  Jennifer Wessel; Nicholas J Schork
Journal:  Am J Hum Genet       Date:  2006-09-21       Impact factor: 11.025

8.  Distance-based tests for homogeneity of multivariate dispersions.

Authors:  Marti J Anderson
Journal:  Biometrics       Date:  2006-03       Impact factor: 2.571

9.  A strategy to discover genes that carry multi-allelic or mono-allelic risk for common diseases: a cohort allelic sums test (CAST).

Authors:  Stephan Morgenthaler; William G Thilly
Journal:  Mutat Res       Date:  2006-11-13       Impact factor: 2.433

10.  Data mining in bioinformatics using Weka.

Authors:  Eibe Frank; Mark Hall; Len Trigg; Geoffrey Holmes; Ian H Witten
Journal:  Bioinformatics       Date:  2004-04-08       Impact factor: 6.937

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  10 in total

Review 1.  Statistical analysis strategies for association studies involving rare variants.

Authors:  Vikas Bansal; Ondrej Libiger; Ali Torkamani; Nicholas J Schork
Journal:  Nat Rev Genet       Date:  2010-10-13       Impact factor: 53.242

2.  Distance-based phenotypic association analysis of DNA sequence data.

Authors:  Doyoung Chung; Qunyuan Zhang; Aldi T Kraja; Ingrid B Borecki; Michael A Province
Journal:  BMC Proc       Date:  2011-11-29

Review 3.  Computational and statistical approaches to analyzing variants identified by exome sequencing.

Authors:  Nathan O Stitziel; Adam Kiezun; Shamil Sunyaev
Journal:  Genome Biol       Date:  2011-09-14       Impact factor: 13.583

4.  The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease.

Authors:  Loukas Moutsianas; Vineeta Agarwala; Christian Fuchsberger; Jason Flannick; Manuel A Rivas; Kyle J Gaulton; Patrick K Albers; Gil McVean; Michael Boehnke; David Altshuler; Mark I McCarthy
Journal:  PLoS Genet       Date:  2015-04-23       Impact factor: 5.917

5.  Weighted Score Tests Implementing Model-Averaging Schemes in Detection of Rare Variants in Case-Control Studies.

Authors:  Brandon Coombes; Saonli Basu; Sharmistha Guha; Nicholas Schork
Journal:  PLoS One       Date:  2015-10-05       Impact factor: 3.240

6.  Protective variant associated with alcohol dependence in a Mexican American cohort.

Authors:  Trina M Norden-Krichmar; Ian R Gizer; Kirk C Wilhelmsen; Nicholas J Schork; Cindy L Ehlers
Journal:  BMC Med Genet       Date:  2014-12-21       Impact factor: 2.103

7.  Gene-based rare allele analysis identified a risk gene of Alzheimer's disease.

Authors:  Jong Hun Kim; Pamela Song; Hyunsun Lim; Jae-Hyung Lee; Jun Hong Lee; Sun Ah Park
Journal:  PLoS One       Date:  2014-10-20       Impact factor: 3.240

8.  A hybrid likelihood model for sequence-based disease association studies.

Authors:  Yun-Ching Chen; Hannah Carter; Jennifer Parla; Melissa Kramer; Fernando S Goes; Mehdi Pirooznia; Peter P Zandi; W Richard McCombie; James B Potash; Rachel Karchin
Journal:  PLoS Genet       Date:  2013-01-24       Impact factor: 5.917

9.  Exploring the potential benefits of stratified false discovery rates for region-based testing of association with rare genetic variation.

Authors:  Changjiang Xu; Antonio Ciampi; Celia M T Greenwood
Journal:  Front Genet       Date:  2014-01-29       Impact factor: 4.599

10.  GWAS to Sequencing: Divergence in Study Design and Analysis.

Authors:  Christopher Ryan King; Dan L Nicolae
Journal:  Genes (Basel)       Date:  2014-05-28       Impact factor: 4.096

  10 in total

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