  Genomic regions represent features such as gene annotations, transcription
factor binding sites and epigenetic modifications. Performing various genomic
operations such as identifying overlapping/non-overlapping regions or nearest
gene annotations are common research needs. The data can be saved in a database
system for easy management, however, there is no comprehensive database
built-in algorithm at present to identify overlapping regions. Therefore I have
developed a region-mapping (RegMap) SQL-based algorithm to perform genomic
operations and have benchmarked the performance of different databases.
Benchmarking identified that PostgreSQL extracts overlapping regions much
faster than MySQL. Insertion and data uploads in PostgreSQL were also better,
although general searching capability of both databases was almost equivalent.
In addition, using the algorithm pair-wise, overlaps of >1000 datasets of
transcription factor binding sites and histone marks, collected from previous
publications, were reported and it was found that HNF4G significantly
co-locates with cohesin subunit STAG1 (SA1).
