OA Epidemiology

QCGWAS: A Flexible R Package for Automated Quality Control of Genome-Wide Association Results Files

Proceedings of the 2013 annual meeting of the Netherlands Epidemiology Society

Volume 1 Issue S1 Abstract 55

 

P.J. van der Most, University Medical Center Groningen, The Netherlands
A. Vaez, University Medical Center Groningen, The Netherlands
B. Prins, University Medical Center Groningen, The Netherlands
M.L. Munoz, University Medical Center Groningen, The Netherlands
H. Snieder, University Medical Center Groningen, The Netherlands
B.Z. Alizadeh, University Medical Center Groningen, The Netherlands
I.M. Nolte, University Medical Center Groningen, The Netherlands

Background
The number of consortia aiming to identify genes for complex traits or diseases through meta-analysis of genome-wide association studies (GWASs) has mushroomed in the last five years. For a meta-analysis, it is important to ensure that all data included are valid, of high quality, and compatible between cohorts. Since a GWAS results file usually follows a standard pattern, we developed the R package  ‘QCGWAS’ to automate the quality control (QC) of these files, thereby gaining speed, reliability, and flexibility in performing dedicated quality checks. Additionally QCGWAS will produce high quality input files for meta-analysis of quantitative trait GWASs.

Methods
A standard QC consists of six steps: (i) inspecting the file for invalid or missing values; (ii) matching alleles and allele frequencies with those from a reference set; (iii) creating histograms and QQ-plots to determine high-quality filters; (iv) calculating QC statistics; (v) saving the cleaned file; (vi) performing between-study comparisons. Detailed QC results are saved to an accessible log-file.

Results
QCGWAS offers many options relating to loading, saving, and testing the data inside a GWAS results file, but the default settings have been chosen so to make running a standard QC very simple. It takes 4-8 minutes and 3 GB of RAM to process a GWAS results file on a computer with a 2.4 GHz processor using R v2.15 (64-bit), depending on the size of the file and the options selected.

Conclusions
QCGWAS is a flexible and easy tool to check the quality of GWAS results files.

Published: 06 Jun, 2013

 
Licensee OA Publishing London 2013. Creative Commons Attribution License (CC-BY)