ArticleNucleic acids research2012
Unrecognized sequence homologies may confound genome-wide association studies.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Genetic Associations with Temporal Modeling of Alzheimer's Disease Progression Supports a Novel Paradigm for Disease Risk.medRxiv : the preprint server for health sciences · 2026Article
- The genetic landscape of pediatric postural orthostatic tachycardia syndrome.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2025Article
- Discovery of Genetic Biomarkers for Alzheimer's Disease Using Adaptive Convolutional Neural Networks Ensemble and Genome-Wide Association Studies.Interdisciplinary sciences, computational life sciences · 2021Article
- Detecting sex-linked genes using genotyped individuals sampled in natural populations.Genetics · 2021Article
- Genome-Wide Analysis of Sex Disparities in the Genetic Architecture of Lung and Colorectal Cancers.Genes · 2021Article
- The signal of sex-specific selection in humans is not an artefact: Reply to Mank et al.Molecular ecology · 2020Article
- Article
- DivergentFrontiers in plant science · 2018Article
- A SNP panel and online tool for checking genotype concordance through comparing QR codes.PloS one · 2017Article
- From next-generation sequencing alignments to accurate comparison and validation of single-nucleotide variants: the pibase software.Nucleic acids research · 2013Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association studies (GWAS) have become a preferred method to identify new genetic susceptibility loci. This technique aims to understanding the molecular etiology of common diseases, but in many cases, it has led to the identification of loci with no obvious biological relevance. Herein, we show that previously unrecognized sequence homologies have caused single-nucleotide polymorphism (SNP) microarrays to incorrectly associate a phenotype to a given locus when in fact the linkage is to another distant locus. Using genetic differences between male and female subjects as a model to study the effect of one specific genomic region on the whole SNP microarray, we provide strong evidence that the use of standard methods for GWAS can be misleading. We suggest a new systematic quality control step in the biological interpretation of previous and future GWAS.
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