Literature DB >> 24739678

Statistical power and significance testing in large-scale genetic studies.

Pak C Sham1, Shaun M Purcell2.   

Abstract

Significance testing was developed as an objective method for summarizing statistical evidence for a hypothesis. It has been widely adopted in genetic studies, including genome-wide association studies and, more recently, exome sequencing studies. However, significance testing in both genome-wide and exome-wide studies must adopt stringent significance thresholds to allow multiple testing, and it is useful only when studies have adequate statistical power, which depends on the characteristics of the phenotype and the putative genetic variant, as well as the study design. Here, we review the principles and applications of significance testing and power calculation, including recently proposed gene-based tests for rare variants.

Mesh:

Year:  2014        PMID: 24739678     DOI: 10.1038/nrg3706

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


  92 in total

1.  Sample size determination for studies of gene-environment interaction.

Authors:  J A Luan; M Y Wong; N E Day; N J Wareham
Journal:  Int J Epidemiol       Date:  2001-10       Impact factor: 7.196

2.  A note on calculation of empirical P values from Monte Carlo procedure.

Authors:  B V North; D Curtis; P C Sham
Journal:  Am J Hum Genet       Date:  2003-02       Impact factor: 11.025

Review 3.  Linkage analysis in the next-generation sequencing era.

Authors:  Joan E Bailey-Wilson; Alexander F Wilson
Journal:  Hum Hered       Date:  2011-12-23       Impact factor: 0.444

4.  Optimal tests for rare variant effects in sequencing association studies.

Authors:  Seunggeun Lee; Michael C Wu; Xihong Lin
Journal:  Biostatistics       Date:  2012-06-14       Impact factor: 5.899

Review 5.  Genome-wide association studies for common diseases and complex traits.

Authors:  Joel N Hirschhorn; Mark J Daly
Journal:  Nat Rev Genet       Date:  2005-02       Impact factor: 53.242

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.  Statistical guidance for experimental design and data analysis of mutation detection in rare monogenic mendelian diseases by exome sequencing.

Authors:  Degui Zhi; Rui Chen
Journal:  PLoS One       Date:  2012-02-10       Impact factor: 3.240

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.  The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits.

Authors:  Benjamin F Voight; Hyun Min Kang; Jun Ding; Cameron D Palmer; Carlo Sidore; Peter S Chines; Noël P Burtt; Christian Fuchsberger; Yanming Li; Jeanette Erdmann; Timothy M Frayling; Iris M Heid; Anne U Jackson; Toby Johnson; Tuomas O Kilpeläinen; Cecilia M Lindgren; Andrew P Morris; Inga Prokopenko; Joshua C Randall; Richa Saxena; Nicole Soranzo; Elizabeth K Speliotes; Tanya M Teslovich; Eleanor Wheeler; Jared Maguire; Melissa Parkin; Simon Potter; N William Rayner; Neil Robertson; Kathleen Stirrups; Wendy Winckler; Serena Sanna; Antonella Mulas; Ramaiah Nagaraja; Francesco Cucca; Inês Barroso; Panos Deloukas; Ruth J F Loos; Sekar Kathiresan; Patricia B Munroe; Christopher Newton-Cheh; Arne Pfeufer; Nilesh J Samani; Heribert Schunkert; Joel N Hirschhorn; David Altshuler; Mark I McCarthy; Gonçalo R Abecasis; Michael Boehnke
Journal:  PLoS Genet       Date:  2012-08-02       Impact factor: 5.917

10.  Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants.

Authors:  Wenqing Fu; Timothy D O'Connor; Goo Jun; Hyun Min Kang; Goncalo Abecasis; Suzanne M Leal; Stacey Gabriel; Mark J Rieder; David Altshuler; Jay Shendure; Deborah A Nickerson; Michael J Bamshad; Joshua M Akey
Journal:  Nature       Date:  2012-11-28       Impact factor: 49.962

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  205 in total

1.  Evaluation of power of the Illumina HumanOmni5M-4v1 BeadChip to detect risk variants for human complex diseases.

Authors:  Chuanhua Xing; Jie Huang; Yi-Hsiang Hsu; Anita L DeStefano; Nancy L Heard-Costa; Philip A Wolf; Sudha Seshadri; Douglas P Kiel; L Adrienne Cupples; Josée Dupuis
Journal:  Eur J Hum Genet       Date:  2015-11-18       Impact factor: 4.246

Review 2.  A guide on gene prioritization in studies of psychiatric disorders.

Authors:  Sven Stringer; Kim C Cerrone; Wim van den Brink; Julia F van den Berg; Damiaan Denys; Rene S Kahn; Eske M Derks
Journal:  Int J Methods Psychiatr Res       Date:  2015-07-31       Impact factor: 4.035

3.  The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants.

Authors:  João Fadista; Alisa K Manning; Jose C Florez; Leif Groop
Journal:  Eur J Hum Genet       Date:  2016-01-06       Impact factor: 4.246

4.  Weighting sequence variants based on their annotation increases power of whole-genome association studies.

Authors:  Gardar Sveinbjornsson; Anders Albrechtsen; Florian Zink; Sigurjón A Gudjonsson; Asmundur Oddson; Gísli Másson; Hilma Holm; Augustine Kong; Unnur Thorsteinsdottir; Patrick Sulem; Daniel F Gudbjartsson; Kari Stefansson
Journal:  Nat Genet       Date:  2016-02-08       Impact factor: 38.330

5.  Overlapping dopaminergic pathway genetic susceptibility to heroin and cocaine addictions in African Americans.

Authors:  Orna Levran; Matthew Randesi; Joel Correa da Rosa; Jurg Ott; John Rotrosen; Miriam Adelson; Mary Jeanne Kreek
Journal:  Ann Hum Genet       Date:  2015-02-27       Impact factor: 1.670

6.  POWERFUL TEST BASED ON CONDITIONAL EFFECTS FOR GENOME-WIDE SCREENING.

Authors:  Yaowu Liu; Jun Xie
Journal:  Ann Appl Stat       Date:  2018-03-09       Impact factor: 2.083

7.  Genome-Wide Association Study of Post-Traumatic Stress Disorder in Two High-Risk Populations.

Authors:  Whitney E Melroy-Greif; Kirk C Wilhelmsen; Rachel Yehuda; Cindy L Ehlers
Journal:  Twin Res Hum Genet       Date:  2017-03-06       Impact factor: 1.587

8.  A simple and accurate method to determine genomewide significance for association tests in sequencing studies.

Authors:  Dan-Yu Lin
Journal:  Genet Epidemiol       Date:  2019-01-08       Impact factor: 2.135

9.  Multimodal imaging of language reorganization in patients with left temporal lobe epilepsy.

Authors:  Yu-Hsuan A Chang; Nobuko Kemmotsu; Kelly M Leyden; N Erkut Kucukboyaci; Vicente J Iragui; Evelyn S Tecoma; Leena Kansal; Marc A Norman; Rachelle Compton; Tobin J Ehrlich; Vedang S Uttarwar; Anny Reyes; Brianna M Paul; Carrie R McDonald
Journal:  Brain Lang       Date:  2017-04-20       Impact factor: 2.381

Review 10.  Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions.

Authors:  Sean Hoban; Joanna L Kelley; Katie E Lotterhos; Michael F Antolin; Gideon Bradburd; David B Lowry; Mary L Poss; Laura K Reed; Andrew Storfer; Michael C Whitlock
Journal:  Am Nat       Date:  2016-08-15       Impact factor: 3.926

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