𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Quality control and quality assurance in genotypic data for genome-wide association studies

✍ Scribed by Cathy C. Laurie; Kimberly F. Doheny; Daniel B. Mirel; Elizabeth W. Pugh; Laura J. Bierut; Tushar Bhangale; Frederick Boehm; Neil E. Caporaso; Marilyn C. Cornelis; Howard J. Edenberg; Stacy B. Gabriel; Emily L. Harris; Frank B. Hu; Kevin B. Jacobs; Peter Kraft; Maria Teresa Landi; Thomas Lumley; Teri A. Manolio; Caitlin McHugh; Ian Painter; Justin Paschall; John P. Rice; Kenneth M. Rice; Xiuwen Zheng; Bruce S. Weir; for the GENEVA Investigators

Publisher
John Wiley and Sons
Year
2010
Tongue
English
Weight
334 KB
Volume
34
Category
Article
ISSN
0741-0395

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

Genome‐wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome‐wide association studies (GWAS). This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy‐Weinberg equilibrium test P‐values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis to SNP selection. The methods are illustrated with examples from the “Gene Environment Association Studies” (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of GWAS. Genet. Epidemiol. 34: 591–602, 2010. © 2010 Wiley‐Liss, Inc.

📜 SIMILAR VOLUMES

Genome-wide association studies: quality
Genome-wide association studies: quality control and population-based measures
✍ Andreas Ziegler 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 139 KB

## Abstract Genome‐wide association studies, using hundreds of thousands of single‐nucleotide polymorphism (SNP) markers, have become a standard approach for identifying disease susceptibility genes. The change in the technology poses substantial computational and statistical challenges that have b

The quality assurance and quality contro
The quality assurance and quality control issues for sponsors on GCP compliance in Japan
✍ Kouichi Inoue; Saburo Hasebe 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 101 KB 👁 2 views

Implementing and maintaining quality assurance (QA) and quality control (QC) systems for clinical trials is essential for sponsors to assure the integrity and reliability of clinical trials and the data obtained from clinical trials. The main points of the revised Good Clinical Practice (GCP) in Jap

A simple and fast two-locus quality cont
A simple and fast two-locus quality control test to detect false positives due to batch effects in genome-wide association studies
✍ Sang Hong Lee; Dale R. Nyholt; Stuart Macgregor; Anjali K. Henders; Krina T. Zon 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 328 KB 👁 1 views

The impact of erroneous genotypes having passed standard quality control (QC) can be severe in genome-wide association studies, genotype imputation, and estimation of heritability and prediction of genetic risk based on single nucleotide polymorphisms (SNP). To detect such genotyping errors, a simpl

P-value based analysis for shared contro
P-value based analysis for shared controls design in genome-wide association studies
✍ Dmitri V. Zaykin; Damian O. Kozbur 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 212 KB 👁 2 views

## Abstract An appealing genome‐wide association study design compares one large control group against several disease samples. A pioneering study by the Wellcome Trust Case Control Consortium that employed such a design has identified multiple susceptibility regions, many of which have been indepe

Shrinkage estimation for robust and effi
Shrinkage estimation for robust and efficient screening of single-SNP association from case-control genome-wide association studies
✍ Sheng Luo; Bhramar Mukherjee; Jinbo Chen; Nilanjan Chatterjee 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 160 KB 👁 2 views

## Abstract Population‐based case‐control design has become one of the most popular approaches for conducting genome‐wide association scans for rare diseases like cancer. In this article, we propose a novel method for improving the power of the widely used single‐single‐nucleotide polymorphism (SNP