TY - JOUR
T1 - Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits
AU - Weissenkampen, J. Dylan
AU - Jiang, Yu
AU - Eckert, Scott
AU - Jiang, Bibo
AU - Li, Bingshan
AU - Liu, Dajiang J.
N1 - Funding Information:
This research is supported partially by National Institutes of Health grants U01HG009086 (B.L.) and R01GM126479 and R01HG008983 (D.L.).
Publisher Copyright:
© 2019 John Wiley & Sons, Inc.
PY - 2019/4
Y1 - 2019/4
N2 - 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.
AB - 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.
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U2 - 10.1002/cphg.83
DO - 10.1002/cphg.83
M3 - Article
C2 - 30849219
AN - SCOPUS:85062784974
SN - 1934-8266
VL - 101
JO - Current protocols in human genetics
JF - Current protocols in human genetics
IS - 1
M1 - e83
ER -