Introduction

Advances in computing, information technology, automated DNA extraction, sequencing, and genotyping have made it possible for researchers to move beyond studying a single gene (or genetic marker) in small populations to studying thousands of genes or even entire genomes in large populations. Genomic databases are playing an increasingly important role in many types of biomedical research involving human participants, ranging from physiological and behavioral studies to epidemiology and clinical trials. To create a genomic database, investigators extract DNA from biological samples such as blood, cheek scrapings, hair, or sputum. The DNA is then sequenced, and the data (e. g., AUGGAGCCU, etc.) is stored in a computer database. Once digitalized, the information can be easily shared with other investigators (Weir and Olick, 2004). The biological samples that serve as the basis for genomic data are usually stored in centralized sites known as biobanks (Weir and Olick, 2004). As biobanks are closely connected to genomic databases, this chapter will also address biobank issues.

Genomic databases may contain information about genes, genetic markers, or common genetic variants or whole genomes (Weir and Olick, 2004). Genomic information can be linked to other types of information pertaining to RNA, proteins, receptors, cellular structures, drugs, and diseases, to study statistical associations. In the last decade, there has been a tremendous increase in the quantity and variety of genomic databases. There are databases for specific populations, nationalities, and diseases, as well general databases. There are public non-profit databases as well as private, for-profit ones. Genomic databases may contain information from a few individuals to hundreds of thousands (Weir and Olick, 2004).