PT  - JOURNAL ARTICLE
AU  - Zhu, Henan
AU  - Dennis, Tristan
AU  - Hughes, Joseph
AU  - Gifford, Robert J.
TI  - Database-integrated genome screening (DIGS): exploring genomes heuristically using sequence similarity search tools and a relational database
AID  - 10.1101/246835
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 246835
4099  - http://biorxiv.org/content/early/2018/04/25/246835.short
4100  - http://biorxiv.org/content/early/2018/04/25/246835.full
AB  - A significant fraction of most genomes is comprised of DNA sequences that have been incompletely investigated. This genomic ‘dark matter’ contains a wealth of useful biological information that can be recovered by systematically screening genomes in silico using sequence similarity search tools. Specialized computational tools are required to implement these screens efficiently. Here, we describe the database-integrated genome-screening (DIGS) tool: a computational framework for performing these investigations. To demonstrate, we screen mammalian genomes for endogenous viral elements (EVEs) derived from the Filoviridae, Parvoviridae, Circoviridae and Bornaviridae families, identifying numerous novel elements in addition to those that have been described previously. The DIGS tool provides a simple, robust framework for implementing a broad range of heuristic, sequence analysis-based explorations of genomic diversity.Availability http://giffordlabcvr.github.io/DIGS-tool/Contact robert.gifford{at}glasgow.ac.ukSupplementary information Supplementary data are available at Bioinformatics online.