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Review
. 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

J Dylan Weissenkampen  1 , Yu Jiang  1 , Scott Eckert  1 , Bibo Jiang  1 , Bingshan Li  2 , Dajiang J Liu  1
Affiliations
Review

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

J Dylan Weissenkampen et al. Curr Protoc Hum Genet. 2019 Apr.

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. © 2019 by John Wiley & Sons, Inc.

Keywords: GWAS; PheWAS; complex traits; genetic association; genome sequencing; rare variant.

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References

    1. Askland K, Read C, & Moore J (2009). Pathways-based analyses of whole-genome association study data in bipolar disorder reveal genes mediating ion channel activity and synaptic neurotransmission. Hum Genet, 125(1), 63–79. doi:10.1007/s00439-008-0600-y - DOI - PubMed
    1. Band G, & Marchini J (2018). BGEN: a binary file format for imputed genotype and haplotype data. bioRxiv.
    1. Barth AS, & Tomaselli GF (2016). Gene scanning and heart attack risk. Trends Cardiovasc Med, 26(3), 260–265. doi:10.1016/j.tcm.2015.07.003 - DOI - PMC - PubMed
    1. Benner C, Spencer CC, Havulinna AS, Salomaa V, Ripatti S, & Pirinen M (2016). FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics, 32(10), 1493–1501. doi:10.1093/bioinformatics/btw018 - DOI - PMC - PubMed
    1. Birdwell KA, Grady B, Choi L, Xu H, Bian A, Denny JC, Haas DW (2012). The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients. Pharmacogenet Genomics, 22(1), 32–42. doi:10.1097/FPC.0b013e32834e1641 - DOI - PMC - PubMed

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