Literature DB >> 27840428

Dissecting the genetics of complex traits using summary association statistics.

Bogdan Pasaniuc1, Alkes L Price2,3.   

Abstract

During the past decade, genome-wide association studies (GWAS) have been used to successfully identify tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyse summary association statistics. Here, we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases.

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Year:  2016        PMID: 27840428      PMCID: PMC5449190          DOI: 10.1038/nrg.2016.142

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN: 1471-0056            Impact factor:   53.242


  119 in total

1.  Best linear unbiased estimation and prediction under a selection model.

Authors:  C R Henderson
Journal:  Biometrics       Date:  1975-06       Impact factor: 2.571

Review 2.  Five years of GWAS discovery.

Authors:  Peter M Visscher; Matthew A Brown; Mark I McCarthy; Jian Yang
Journal:  Am J Hum Genet       Date:  2012-01-13       Impact factor: 11.025

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

Authors:  Bingshan Li; Suzanne M Leal
Journal:  Am J Hum Genet       Date:  2008-08-07       Impact factor: 11.025

4.  Estimating missing heritability for disease from genome-wide association studies.

Authors:  Sang Hong Lee; Naomi R Wray; Michael E Goddard; Peter M Visscher
Journal:  Am J Hum Genet       Date:  2011-03-03       Impact factor: 11.025

5.  Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets.

Authors:  Zhihong Zhu; Futao Zhang; Han Hu; Andrew Bakshi; Matthew R Robinson; Joseph E Powell; Grant W Montgomery; Michael E Goddard; Naomi R Wray; Peter M Visscher; Jian Yang
Journal:  Nat Genet       Date:  2016-03-28       Impact factor: 38.330

6.  Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.

Authors:  Joshua C Denny; Lisa Bastarache; Marylyn D Ritchie; Robert J Carroll; Raquel Zink; Jonathan D Mosley; Julie R Field; Jill M Pulley; Andrea H Ramirez; Erica Bowton; Melissa A Basford; David S Carrell; Peggy L Peissig; Abel N Kho; Jennifer A Pacheco; Luke V Rasmussen; David R Crosslin; Paul K Crane; Jyotishman Pathak; Suzette J Bielinski; Sarah A Pendergrass; Hua Xu; Lucia A Hindorff; Rongling Li; Teri A Manolio; Christopher G Chute; Rex L Chisholm; Eric B Larson; Gail P Jarvik; Murray H Brilliant; Catherine A McCarty; Iftikhar J Kullo; Jonathan L Haines; Dana C Crawford; Daniel R Masys; Dan M Roden
Journal:  Nat Biotechnol       Date:  2013-12       Impact factor: 54.908

7.  Testing for an unusual distribution of rare variants.

Authors:  Benjamin M Neale; Manuel A Rivas; Benjamin F Voight; David Altshuler; Bernie Devlin; Marju Orho-Melander; Sekar Kathiresan; Shaun M Purcell; Kathryn Roeder; Mark J Daly
Journal:  PLoS Genet       Date:  2011-03-03       Impact factor: 5.917

8.  Mendelian randomization analysis with multiple genetic variants using summarized data.

Authors:  Stephen Burgess; Adam Butterworth; Simon G Thompson
Journal:  Genet Epidemiol       Date:  2013-09-20       Impact factor: 2.135

9.  JEPEG: a summary statistics based tool for gene-level joint testing of functional variants.

Authors:  Donghyung Lee; Vernell S Williamson; T Bernard Bigdeli; Brien P Riley; Ayman H Fanous; Vladimir I Vladimirov; Silviu-Alin Bacanu
Journal:  Bioinformatics       Date:  2014-12-12       Impact factor: 6.937

10.  FINEMAP: efficient variable selection using summary data from genome-wide association studies.

Authors:  Christian Benner; Chris C A Spencer; Aki S Havulinna; Veikko Salomaa; Samuli Ripatti; Matti Pirinen
Journal:  Bioinformatics       Date:  2016-01-14       Impact factor: 6.937

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  142 in total

Review 1.  Complex Trait Prediction from Genome Data: Contrasting EBV in Livestock to PRS in Humans: Genomic Prediction.

Authors:  Naomi R Wray; Kathryn E Kemper; Benjamin J Hayes; Michael E Goddard; Peter M Visscher
Journal:  Genetics       Date:  2019-04       Impact factor: 4.562

2.  Screening Human Embryos for Polygenic Traits Has Limited Utility.

Authors:  Ehud Karavani; Or Zuk; Danny Zeevi; Nir Barzilai; Nikos C Stefanis; Alex Hatzimanolis; Nikolaos Smyrnis; Dimitrios Avramopoulos; Leonid Kruglyak; Gil Atzmon; Max Lam; Todd Lencz; Shai Carmi
Journal:  Cell       Date:  2019-11-21       Impact factor: 41.582

3.  RAISS: robust and accurate imputation from summary statistics.

Authors:  Hanna Julienne; Huwenbo Shi; Bogdan Pasaniuc; Hugues Aschard
Journal:  Bioinformatics       Date:  2019-11-01       Impact factor: 6.937

4.  Generalized meta-analysis for multiple regression models across studies with disparate covariate information.

Authors:  Prosenjit Kundu; Runlong Tang; Nilanjan Chatterjee
Journal:  Biometrika       Date:  2019-07-13       Impact factor: 2.445

5.  Phenotype-Specific Enrichment of Mendelian Disorder Genes near GWAS Regions across 62 Complex Traits.

Authors:  Malika Kumar Freund; Kathryn S Burch; Huwenbo Shi; Nicholas Mancuso; Gleb Kichaev; Kristina M Garske; David Z Pan; Zong Miao; Karen L Mohlke; Markku Laakso; Päivi Pajukanta; Bogdan Pasaniuc; Valerie A Arboleda
Journal:  Am J Hum Genet       Date:  2018-10-04       Impact factor: 11.025

6.  Integrate multiple traits to detect novel trait-gene association using GWAS summary data with an adaptive test approach.

Authors:  Bin Guo; Baolin Wu
Journal:  Bioinformatics       Date:  2019-07-01       Impact factor: 6.937

7.  One Hundred Years of Linkage Disequilibrium.

Authors:  John A Sved; William G Hill
Journal:  Genetics       Date:  2018-07       Impact factor: 4.562

8.  Statistical methods to detect novel genetic variants using publicly available GWAS summary data.

Authors:  Bin Guo; Baolin Wu
Journal:  Comput Biol Chem       Date:  2018-03-01       Impact factor: 2.877

Review 9.  Genomic Approaches to Posttraumatic Stress Disorder: The Psychiatric Genomic Consortium Initiative.

Authors:  Caroline M Nievergelt; Allison E Ashley-Koch; Shareefa Dalvie; Michael A Hauser; Rajendra A Morey; Alicia K Smith; Monica Uddin
Journal:  Biol Psychiatry       Date:  2018-02-02       Impact factor: 13.382

Review 10.  Genomic updates in understanding PTSD.

Authors:  Sumeet Sharma; Kerry J Ressler
Journal:  Prog Neuropsychopharmacol Biol Psychiatry       Date:  2018-11-16       Impact factor: 5.067

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