Pharmacogenomic and Statistical Analysis

Haimeng Bai; Xueyi Zhang; William S Bush

doi:10.1007/978-1-0716-2986-4_14

Pharmacogenomic and Statistical Analysis

Methods Mol Biol. 2023:2629:305-330. doi: 10.1007/978-1-0716-2986-4_14.

Authors

Haimeng Bai^#^{1

2}, Xueyi Zhang^#¹, William S Bush^#³

Affiliations

¹ Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
² Department of Nutrition, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
³ Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA. Wsb36@case.edu.

^# Contributed equally.

PMID: 36929083
DOI: 10.1007/978-1-0716-2986-4_14

Abstract

Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.

Keywords: Haplotypes; High-throughput sequencing; Pharmacogenomics; Quality control; Rare variants; Statistical genomics.

MeSH terms

Pharmacogenetics* / methods
Pharmacogenomic Testing
Phenotype
Research Design*