Quality control procedures for genome-wide association studies.
paper
Cited
Public
- Authors
- Turner, Stephen; Armstrong, Loren L; Bradford, Yuki; Carlson, Christopher S; Crawford, Dana C; Crenshaw, Andrew T; de Andrade, Mariza; Doheny, Kimberly F; Haines, Jonathan L; Hayes, Geoffrey; Jarvik, Gail; Jiang, Lan; Kullo, Iftikhar J; Li, Rongling; Ling, Hua; Manolio, Teri A; Matsumoto, Martha; McCarty, Catherine A; McDavid, Andrew N; Mirel, Daniel B; Paschall, Justin E; Pugh, Elizabeth W; Rasmussen, Luke V; Wilke, Russell A; Zuvich, Rebecca L; Ritchie, Marylyn D
- Year
- 2011
- Journal
- Current protocols in human genetics
- PMID
- 21234875
- DOI
- 10.1002/0471142905.hg0119s68
- PMCID
- PMC3066182
Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of complex disease. Regardless of context, the practical utility of this information will ultimately depend upon the quality of the original data. Quality control (QC) procedures for GWAS are computationally intensive, operationally challenging, and constantly evolving. Here we enumerate some of the challenges in QC of GWAS data and describe the approaches that the electronic MEdical Records and Genomics (eMERGE) network is using for quality assurance in GWAS data, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of GWAS data, including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We propose best practices and discuss areas of ongoing and future research.
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| How to include chromosome X in your genome-wide association study. | KΓΆnig IR et al. | β | 2014 | β |
| Letter to the editor: expression of concern, reaffirmed. | Paterson AD | β | 2014 | β |
| Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index. | Cronin RM et al. | β | 2014 | β |
| Quantitative trait loci mapping for canine hip dysplasia and its related traits in UK Labrador Retrievers. | SΓ‘nchez-Molano E et al. | β | 2014 | β |
| Secondary use of clinical data: the Vanderbilt approach. | Danciu I et al. | β | 2014 | β |
| The ATXN2-SH2B3 locus is associated with peripheral arterial disease: an electronic medical record-based genome-wide association study. | Kullo IJ et al. | β | 2014 | β |
| Common variants within oxidative phosphorylation genes influence risk of ischemic stroke and intracerebral hemorrhage. | Anderson CD et al. | β | 2013 | β |
| Confirmation of the reported association of clonal chromosomal mosaicism with an increased risk of incident hematologic cancer. | Schick UM et al. | β | 2013 | β |
| Enhancing the power of genetic association studies through the use of silver standard cases derived from electronic medical records. | McDavid A et al. | β | 2013 | β |
| Genetic variants that confer resistance to malaria are associated with red blood cell traits in African-Americans: an electronic medical record-based genome-wide association study. | Ding K et al. | β | 2013 | β |
| Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk. | Ritchie MD et al. | β | 2013 | β |
| Infinium assay for large-scale SNP genotyping applications. | Adler AJ et al. | β | 2013 | β |
| Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit. | Pendergrass SA et al. | β | 2013 | β |
| Phenotyping clinical disorders: lessons learned from pelvic organ prolapse. | Wu JM et al. | β | 2013 | β |
| pyGenClean: efficient tool for genetic data clean up before association testing. | Lemieux Perreault LP et al. | β | 2013 | β |
| Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. | Denny JC et al. | β | 2013 | β |
| Family-based genome-wide association study of frontal ΞΈ oscillations identifies potassium channel gene KCNJ6. | Kang SJ et al. | β | 2012 | β |
| FastUniq: a fast de novo duplicates removal tool for paired short reads. | Xu H et al. | β | 2012 | β |
| Genetic Loci implicated in erythroid differentiation and cell cycle regulation are associated with red blood cell traits. | Ding K et al. | β | 2012 | β |
| Genetic variants associated with the white blood cell count in 13,923 subjects in the eMERGE Network. | Crosslin DR et al. | β | 2012 | β |
| High density GWAS for LDL cholesterol in African Americans using electronic medical records reveals a strong protective variant in APOE. | Rasmussen-Torvik LJ et al. | β | 2012 | β |
| Next generation analytic tools for large scale genetic epidemiology studies of complex diseases. | Mechanic LE et al. | β | 2012 | β |
| The effect of non-differential measurement error on bias, precision and power in Mendelian randomization studies. | Pierce BL et al. | β | 2012 | β |
| Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study. | Kho AN et al. | β | 2012 | β |
| Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate. | Kullo IJ et al. | β | 2011 | β |
| Evaluating the influence of quality control decisions and software algorithms on SNP calling for the affymetrix 6.0 SNP array platform. | de Andrade M et al. | β | 2011 | β |
| Genotype-informed estimation of risk of coronary heart disease based on genome-wide association data linked to the electronic medical record. | Ding K et al. | β | 2011 | β |
| Knowledge-driven multi-locus analysis reveals gene-gene interactions influencing HDL cholesterol level in two independent EMR-linked biobanks. | Turner SD et al. | β | 2011 | β |
| Pitfalls of merging GWAS data: lessons learned in the eMERGE network and quality control procedures to maintain high data quality. | Zuvich RL et al. | β | 2011 | β |
| Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies. | Denny JC et al. | β | 2011 | β |