Literature DB >> 23853079

Identifying rare variants associated with complex traits via sequencing.

Bingshan Li1, Dajiang J Liu, Suzanne M Leal.   

Abstract

Although genome-wide association studies have been successful in detecting associations with common variants, there is currently an increasing interest in identifying low-frequency and rare variants associated with complex traits. Next-generation sequencing technologies make it feasible to survey the full spectrum of genetic variation in coding regions or the entire genome. The association analysis for rare variants is challenging, and traditional methods are ineffective, however, due to the low frequency of rare variants, coupled with allelic heterogeneity. Recently a battery of new statistical methods has been proposed for identifying rare variants associated with complex traits. These methods test for associations by aggregating multiple rare variants across a gene or a genomic region or among a group of variants in the genome. In this unit, we describe key concepts for rare variant association for complex traits, survey some of the recent methods, discuss their statistical power under various scenarios, and provide practical guidance on analyzing next-generation sequencing data for identifying rare variants associated with complex traits. 2013 by John Wiley & Sons, Inc.

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Mesh:

Year:  2013        PMID: 23853079      PMCID: PMC3830981          DOI: 10.1002/0471142905.hg0126s78

Source DB:  PubMed          Journal:  Curr Protoc Hum Genet        ISSN: 1934-8258


  88 in total

1.  Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data.

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Review 4.  Next-generation DNA sequencing methods.

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Journal:  Annu Rev Genomics Hum Genet       Date:  2008       Impact factor: 8.929

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Review 6.  Common and rare variants in multifactorial susceptibility to common diseases.

Authors:  Walter Bodmer; Carolina Bonilla
Journal:  Nat Genet       Date:  2008-06       Impact factor: 38.330

Review 7.  Common vs. rare allele hypotheses for complex diseases.

Authors:  Nicholas J Schork; Sarah S Murray; Kelly A Frazer; Eric J Topol
Journal:  Curr Opin Genet Dev       Date:  2009-05-28       Impact factor: 5.578

8.  Discovery of rare variants via sequencing: implications for the design of complex trait association studies.

Authors:  Bingshan Li; Suzanne M Leal
Journal:  PLoS Genet       Date:  2009-05-15       Impact factor: 5.917

9.  Rare independent mutations in renal salt handling genes contribute to blood pressure variation.

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10.  A flexible and accurate genotype imputation method for the next generation of genome-wide association studies.

Authors:  Bryan N Howie; Peter Donnelly; Jonathan Marchini
Journal:  PLoS Genet       Date:  2009-06-19       Impact factor: 5.917

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  21 in total

1.  A haplotype-based framework for group-wise transmission/disequilibrium tests for rare variant association analysis.

Authors:  Rui Chen; Qiang Wei; Xiaowei Zhan; Xue Zhong; James S Sutcliffe; Nancy J Cox; Edwin H Cook; Chun Li; Wei Chen; Bingshan Li
Journal:  Bioinformatics       Date:  2015-01-06       Impact factor: 6.937

2.  To aggregate or not, that is the question. A commentary on single-nucleotide variant proportion in genes: a new concept to explore major depression based on DNA sequencing data.

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Journal:  J Hum Genet       Date:  2017-02-02       Impact factor: 3.172

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Review 4.  Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.

Authors:  J Dylan Weissenkampen; Yu Jiang; Scott Eckert; Bibo Jiang; Bingshan Li; Dajiang J Liu
Journal:  Curr Protoc Hum Genet       Date:  2019-03-08

5.  Exome-based case-control association study using extreme phenotype design reveals novel candidates with protective effect in diabetic retinopathy.

Authors:  Corina Shtir; Mohammed A Aldahmesh; Saad Al-Dahmash; Emad Abboud; Hisham Alkuraya; Marwan A Abouammoh; Sawsan R Nowailaty; Ghazai Al-Thubaiti; E A Naim; B ALYounes; F S Binhumaid; A B ALOtaibi; A S Altamimi; F H Alamer; Mais Hashem; Mohamed Abouelhoda; Dorota Monies; Fowzan S Alkuraya
Journal:  Hum Genet       Date:  2015-12-22       Impact factor: 4.132

6.  VMAT2 gene (SLC18A2) variants associated with a greater risk for developing opioid dependence.

Authors:  Matthew Randesi; Wim van den Brink; Orna Levran; Peter Blanken; Jan M van Ree; Jurg Ott; Mary Jeanne Kreek
Journal:  Pharmacogenomics       Date:  2019-04-15       Impact factor: 2.533

7.  Choosing Subsamples for Sequencing Studies by Minimizing the Average Distance to the Closest Leaf.

Authors:  Jonathan T L Kang; Peng Zhang; Sebastian Zöllner; Noah A Rosenberg
Journal:  Genetics       Date:  2015-08-24       Impact factor: 4.562

8.  Mathematical Properties of Linkage Disequilibrium Statistics Defined by Normalization of the Coefficient D = pAB - pApB.

Authors:  Jonathan T L Kang; Noah A Rosenberg
Journal:  Hum Hered       Date:  2020-02-11       Impact factor: 0.444

Review 9.  Impact of exome sequencing in inflammatory bowel disease.

Authors:  Christopher J Cardinale; Judith R Kelsen; Robert N Baldassano; Hakon Hakonarson
Journal:  World J Gastroenterol       Date:  2013-10-28       Impact factor: 5.742

10.  Pooled sequencing and rare variant association tests for identifying the determinants of emerging drug resistance in malaria parasites.

Authors:  Ian H Cheeseman; Marina McDew-White; Aung Pyae Phyo; Kanlaya Sriprawat; François Nosten; Timothy J C Anderson
Journal:  Mol Biol Evol       Date:  2014-12-21       Impact factor: 16.240

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