Methods to Analyze Big Data in Pharmacogenomics Research

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::

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

Financial & competing interests disclosure

This work was funded in part by the following grants: AI077505, GM115318 and AI116794. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Additional information

Funding

This work was funded in part by the following grants: National Institute of Health (NIH) AI077505, GM115318 and AI116794. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.