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Curr Protoc Hum Genet. 2019 Apr;101(1):e83. doi: 10.1002/cphg.83. Epub 2019 Mar 8.

Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.

Author information

1
Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania.
2
Department of Molecular Physiology and Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, Tennessee.

Abstract

With the advent of Next Generation Sequencing (NGS) technologies, whole genome and whole exome DNA sequencing has become affordable for routine genetic studies. Coupled with improved genotyping arrays and genotype imputation methodologies, it is increasingly feasible to obtain rare genetic variant information in large datasets. Such datasets allow researchers to gain a more complete understanding of the genetic architecture of complex traits caused by rare variants. State-of-the-art statistical methods for the statistical genetics analysis of sequence-based association, including efficient algorithms for association analysis in biobank-scale datasets, gene-association tests, meta-analysis, fine mapping methods that integrate functional genomic dataset, and phenome-wide association studies (PheWAS), are reviewed here. These methods are expected to be highly useful for next generation statistical genetics analysis in the era of precision medicine.

KEYWORDS:

GWAS; PheWAS; complex traits; genetic association; genome sequencing; rare variant

PMID:
30849219
PMCID:
PMC6455968
[Available on 2020-04-01]
DOI:
10.1002/cphg.83

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