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Pharmacogenomics. 2017 Jun;18(8):807-820. doi: 10.2217/pgs-2016-0152. Epub 2017 Jun 14.

Methods to analyze big data in pharmacogenomics research.

Author information

1
Bioinformatics & Genomics Graduate Program, The Pennsylvania State University, University Park, PA 16802, USA.
2
Biomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA 17821, USA.

Abstract

The scale and scope of pharmacogenomics research continues to expand as the cost and efficiency of molecular data generation techniques advance. These new technologies give rise to enormous opportunity for the identification of important genetic and genomic factors important for drug treatment response. With this opportunity come significant challenges. Most of these can be categorized as 'big data' issues, facing not only pharmacogenomics, but other fields in the life sciences as well. In this review, we describe some of the analysis techniques and tools being implemented for genetic/genomic discovery in pharmacogenomics.

KEYWORDS:

GWAS; association analysis; big data; biological knowledge; epistasis; genomics; systems genomics

PMID:
28612644
DOI:
10.2217/pgs-2016-0152
[Indexed for MEDLINE]

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