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Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data
- Source :
- Genome Biology, Genome Biology, Vol 18, Iss 1, Pp 1-10 (2017)
- Publication Year :
- 2017
- Publisher :
- BioMed Central, 2017.
-
Abstract
- Background Understanding the mapping precision of genome-wide association studies (GWAS), that is the physical distances between the top associated single-nucleotide polymorphisms (SNPs) and the causal variants, is essential to design fine-mapping experiments for complex traits and diseases. Results Using simulations based on whole-genome sequencing (WGS) data from 3642 unrelated individuals of European descent, we show that the association signals at rare causal variants (minor allele frequency ≤ 0.01) are very unlikely to be mapped to common variants in GWAS using either WGS data or imputed data and vice versa. We predict that at least 80% of the common variants identified from published GWAS using imputed data are within 33.5 Kbp of the causal variants, a resolution that is comparable with that using WGS data. Mapping precision at these loci will improve with increasing sample sizes of GWAS in the future. For rare variants, the mapping precision of GWAS using WGS data is extremely high, suggesting WGS is an efficient strategy to detect and fine-map rare variants simultaneously. We further assess the mapping precision by linkage disequilibrium between GWAS hits and causal variants and develop an online tool (gwasMP) to query our results with different thresholds of physical distance and/or linkage disequilibrium (http://cnsgenomics.com/shiny/gwasMP). Conclusions Our findings provide a benchmark to inform future design and development of fine-mapping experiments and technologies to pinpoint the causal variants at GWAS loci. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1216-0) contains supplementary material, which is available to authorized users.
- Subjects :
- 0301 basic medicine
Linkage disequilibrium
lcsh:QH426-470
Genotype
Quantitative Trait Loci
Genomics
Genome-wide association study
Biology
Genome-wide association studies
Polymorphism, Single Nucleotide
Linkage Disequilibrium
White People
03 medical and health sciences
0302 clinical medicine
Gene Frequency
Humans
False positive rate
lcsh:QH301-705.5
Alleles
Genetic association
Imputation
Genome, Human
Research
Physical Chromosome Mapping
High-Throughput Nucleotide Sequencing
Minor allele frequency
lcsh:Genetics
030104 developmental biology
Phenotype
lcsh:Biology (General)
Mapping precision
Evolutionary biology
Whole genome sequencing
Sample Size
030217 neurology & neurosurgery
Imputation (genetics)
Personal genomics
Genome-Wide Association Study
Subjects
Details
- Language :
- English
- ISSN :
- 1474760X and 14747596
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Genome Biology
- Accession number :
- edsair.doi.dedup.....21a9c7d4efb95d3082c9f482f7cbbd75