نتایج جستجو برای: genome wide association study

تعداد نتایج: 4629884  

2016
Chunnian Liang Lizhong Wang Xiaoyun Wu Kun Wang Xuezhi Ding Mingcheng Wang Min Chu Xiuyue Xie Qiang Qiu Ping Yan

The absence of horns, known as the polled phenotype, is an economically important trait in modern yak husbandry, but the genomic structure and genetic basis of this phenotype have yet to be discovered. Here, we conducted a genome-wide association study with a panel of 10 horned and 10 polled yaks using whole genome sequencing. We mapped the POLLED locus to a 200-kb interval, which comprises thr...

2017
D Zabaneh E Krapohl HA Gaspar C Curtis SH Lee H Patel S Newhouse HM Wu MA Simpson M Putallaz D Lubinski R Plomin

We used a case–control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and significant genom...

2013
Timothy Caulfield Jim Evans Amy McGuire Christopher McCabe Tania Bubela Robert Cook-Deegan Jennifer Fishman Stuart Hogarth Fiona A. Miller Vardit Ravitsky Barbara Biesecker Pascal Borry Mildred K. Cho June C. Carroll Holly Etchegary Yann Joly Kazuto Kato Sandra Soo-Jin Lee Karen Rothenberg Pamela Sankar Michael J. Szego Pilar Ossorio Daryl Pullman Francois Rousseau Wendy J. Ungar Brenda Wilson

The cost of whole genome sequencing is dropping rapidly. There has been a great deal of enthusiasm about the potential for this technological advance to transform clinical care. Given the interest and significant investment in genomics, this seems an ideal time to consider what the evidence tells us about potential benefits and harms, particularly in the context of health care policy. The scale...

2009
Charles Kooperberg

Index 4 powerGWASinteraction Power calculations for identifying interactions in GWAS studies Description This function carries out approximate power calculations for identifying SNP x SNP and SNP x environment interactions in genome-wide association (GWAS) studies. It assumes a two-stage analysis , where only SNPs that are significant at a marginal significance level alpha1 are investgigated fo...

2017
Daniel W. Belsky

There are no easy answers in complex disease genetics. Common, chronic health conditions such as obesity and heart disease are influenced by many genetic variants scattered across the genome, with each variant making small contributions to risk. Ever-larger genome-wide association studies (GWAS) are uncovering more and more of these variants. For many diseases and disease-related traits, discov...

2011
Renate B. Schnabel

Study Hypothesis Initial genome-wide association studies (GWAS) for hypertension, a common cardiovascular risk factor, have delivered unexpectedly few and modest associations. The authors of the International Consortium for Blood Pressure Genome-Wide Association Studies set out to identify novel genetic variants in relation to blood pressure, intermediate phenotypes, and cardiovascular disease ...

Journal: :International journal of bioinformatics research and applications 2008
Jing Li

Large-scale Genome-Wide Association Studies (GWAS) for complex diseases are increasingly common, due to recent advances in genotyping technology. Gene-gene interactions play an important role in the etiology of complex diseases and have to be addressed in GWAS. In this paper, an efficient strategy based on two-stage analysis is proposed. It combines a single-locus approach with a Goodness-Of-Fi...

2016
David Hugh-Jones Karin J.H. Verweij Beate St. Pourcain Abdel Abdellaoui

Article history: Received 7 June 2016 Received in revised form 25 July 2016 Accepted 14 August 2016 Available online xxxx We examinedwhether assortative mating for educational attainment (“likemarries like”) can be detected in the genomes of ~1600 UK spouse pairs of European descent. Assortative mating on heritable traits like educational attainment increases the genetic variance and heritabili...

2014
Fei Yu Zhanglong Ji

In response to the growing interest in genome-wide association study (GWAS) data privacy, the Integrating Data for Analysis, Anonymization and SHaring (iDASH) center organized the iDASH Healthcare Privacy Protection Challenge, with the aim of investigating the effectiveness of applying privacy-preserving methodologies to human genetic data. This paper is based on a submission to the iDASH Healt...

2017
Paul S de Vries Maria Sabater-Lleal Daniel I Chasman Stella Trompet Tarunveer S Ahluwalia Alexander Teumer Marcus E Kleber Ming-Huei Chen Jie Jin Wang John R Attia Riccardo E Marioni Maristella Steri Lu-Chen Weng Rene Pool Vera Grossmann Jennifer A Brody Cristina Venturini Toshiko Tanaka Lynda M Rose Christopher Oldmeadow Johanna Mazur Saonli Basu Mattias Frånberg Qiong Yang Symen Ligthart Jouke J Hottenga Ann Rumley Antonella Mulas Anton J M de Craen Anne Grotevendt Kent D Taylor Graciela E Delgado Annette Kifley Lorna M Lopez Tina L Berentzen Massimo Mangino Stefania Bandinelli Alanna C Morrison Anders Hamsten Geoffrey Tofler Moniek P M de Maat Harmen H M Draisma Gordon D Lowe Magdalena Zoledziewska Naveed Sattar Karl J Lackner Uwe Völker Barbara McKnight Jie Huang Elizabeth G Holliday Mark A McEvoy John M Starr Pirro G Hysi Dena G Hernandez Weihua Guan Fernando Rivadeneira Wendy L McArdle P Eline Slagboom Tanja Zeller Bruce M Psaty André G Uitterlinden Eco J C de Geus David J Stott Harald Binder Albert Hofman Oscar H Franco Jerome I Rotter Luigi Ferrucci Tim D Spector Ian J Deary Winfried März Andreas Greinacher Philipp S Wild Francesco Cucca Dorret I Boomsma Hugh Watkins Weihong Tang Paul M Ridker Jan W Jukema Rodney J Scott Paul Mitchell Torben Hansen Christopher J O'Donnell Nicholas L Smith David P Strachan Abbas Dehghan

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we ...

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