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With the advent of high throughput data genomic technologies the volume of available data is now staggering. In addition databases that provide resources to annotate, translate, and connect biological data have grown exponentially in content and use. The availability of such data emphasizes the importance of bioinformatics and computational biology in genomics research and has led to the development of thousands of tools to integrate and utilize these resources. When utilizing such resources, the principles of reproducible research are often overlooked. In this manuscript we provide selected case studies illustrating issues that may arise while working with genes and genetic polymorphisms. These case studies illustrate potential sources of error which can be introduced if the practices of reproducible research are not employed and non-concurrent databases are used. We also show examples of a lack of transparency when these databases are concerned when using popular bioinformatics tools. These examples highlight that resources are constantly evolving, and in order to provide reproducible results, research should be aware of and connected to the correct release of the data, particularly when implementing computational tools.

Where in the genome are we? A cautionary tale of database use in genomics research