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

J. Dylan Weissenkampen, Yu Jiang, Scott Eckert, Bibo Jiang, Bingshan Li, Dajiang J. Liu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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.

Original languageEnglish (US)
Article numbere83
JournalCurrent protocols in human genetics
Volume101
Issue number1
DOIs
StatePublished - Apr 2019

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

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