ArticleCurrent protocols in human genetics2011
Quality control procedures for genome-wide association studies.
Article in Current protocols in human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 218 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
218 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Genetic Polymorphisms Associated with Fetal Hemoglobin (HbF) Levels and F-Cell Numbers: A Systematic Review of Genome-Wide Association Studies.International journal of molecular sciences · 2024Pooled it
- A systematic review of analytical methods used in genetic association analysis of the X-chromosome.Briefings in bioinformatics · 2022Pooled it
- Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure.Briefings in bioinformatics · 2022Pooled it
- Phenome-wide association analysis suggests the APOL1 linked disease spectrum primarily drives kidney-specific pathways.Kidney international · 2020Pooled it
- Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019Trial
- A non-coding CRHR2 SNP rs255105, a cis-eQTL for a downstream lincRNA AC005154.6, is associated with heroin addiction.PloS one · 2018Trial
- Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.Circulation · 2013Trial
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- Eras of bioinformatics technologies from command-line interfaces to artificial intelligence (AI) chatbots.Briefings in bioinformatics · 2026Review
- Privacy-preserving verification of preprocessing in federated learning for genomic data.JAMIA open · 2026Article
- Decoding Complex Traits in Goats Through Genome-Wide Association Studies: Progress, Challenges, and Perspectives.International journal of molecular sciences · 2026Review
- Impact of control selection strategies on GWAS results: a study of prostate cancer in the UK Biobank.Briefings in bioinformatics · 2026Article
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- Genetic predisposition to elevated total immunoglobulin E levels defines a distinct adult-onset-predominant asthma phenotype.Scientific reports · 2026Article
- Evidence for reduced somatic T-cell receptor sequence diversity profiles among Midwestern Amish in an aging cohort study.medRxiv : the preprint server for health sciences · 2026Article
- Genotype subtyping approach to identify unnoticed variants in diseases from GWAS data.BioData mining · 2026Article
- Association of Brain Structural Measurements and Polygenic Risk Scores with Obsessive-Compulsive Symptoms in Adolescents Diagnosed with Obsessive-Compulsive Disorder, Attention-Deficit/Hyperactivity Disorder, Anxiety, Depression, Autism and Tic Disorders.medRxiv : the preprint server for health sciences · 2025Article
- Uncertainty-aware genomic classification of Alzheimer's disease: a transformer-based ensemble approach with Monte Carlo dropout.Briefings in bioinformatics · 2025Article
158 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.