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

TitleMethods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.
Publication TypeJournal Article
Year of Publication2019
AuthorsJ Weissenkampen, D, Jiang, Y, Eckert, S, Jiang, B, Li, B, Liu, DJ
JournalCurr Protoc Hum Genet
Volume101
Issue1
Paginatione83
Date Published2019 04
ISSN1934-8258
KeywordsAlgorithms, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, High-Throughput Nucleotide Sequencing, Humans, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Whole Exome Sequencing, Whole Genome Sequencing
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.

DOI10.1002/cphg.83
Alternate JournalCurr Protoc Hum Genet
PubMed ID30849219
PubMed Central IDPMC6455968
Grant ListR01 GM126479 / GM / NIGMS NIH HHS / United States
R01 HG008983 / HG / NHGRI NIH HHS / United States
R21 DA040177 / DA / NIDA NIH HHS / United States
U01 HG009086 / HG / NHGRI NIH HHS / United States