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GenoWAP: Post-GWAS Prioritization Through Integrated Analysis of Genomic Functional Annotation

View ORCID ProfileQiongshi Lu, Xinwei Yao, Yiming Hu, Hongyu Zhao
doi: https://doi.org/10.1101/019539
Qiongshi Lu
Yale University
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Xinwei Yao
Yale University
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Yiming Hu
Yale University
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Hongyu Zhao
Yale University
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Abstract

Genome-wide association study (GWAS) has been a great success in the past decade. However, significant challenges still remain in both identifying new risk loci and interpreting results. Bonferroni-corrected significance level is known to be conservative, leading to insufficient statistical power when the effect size is moderate at risk locus. Complex structure of linkage disequilibrium also makes it challenging to separate causal variants from nonfunctional ones in large haplotype blocks. We describe GenoWAP, a post-GWAS prioritization method that integrates genomic functional annotation and GWAS test statistics. The effectiveness of GenoWAP is demonstrated through its applications to Crohn’s disease and schizophrenia using the largest studies available, where highly ranked loci show substantially stronger signals in the whole dataset after prioritization based on a subset of samples. At the single nucleotide polymorphism (SNP) level, top ranked SNPs after prioritization have both higher replication rates and consistently stronger enrichment of eQTLs. Within each risk locus, GenoWAP is also able to distinguish functional sites from groups of correlated SNPs. GenoWAP is freely available on the web at http://genocanyon.med.yale.edu/GenoWAP

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The copyright holder for this preprint is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.
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  • Posted May 20, 2015.

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GenoWAP: Post-GWAS Prioritization Through Integrated Analysis of Genomic Functional Annotation
Qiongshi Lu, Xinwei Yao, Yiming Hu, Hongyu Zhao
bioRxiv 019539; doi: https://doi.org/10.1101/019539
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GenoWAP: Post-GWAS Prioritization Through Integrated Analysis of Genomic Functional Annotation
Qiongshi Lu, Xinwei Yao, Yiming Hu, Hongyu Zhao
bioRxiv 019539; doi: https://doi.org/10.1101/019539

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