bioRxivBioinformaticsPreprint
Database-integrated genome screening (DIGS): exploring genomes heuristically using sequence similarity search tools and a relational database.
Henan ZhuiD, Tristan P. W. DennisiD, Joseph HughesiD, Robert James GiffordiD
Abstract
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.\n\nAvailabilityhttp://giffordlabcvr.github.io/DIGS-tool/\n\nContactrobert.gifford@glasgow.ac.uk\n\nSupplementary informationSupplementary data are available at Bioinformatics online.
- organism: mouse
- organism: human
- assay: whole-genome sequencing
- research focus: database / resource
- research focus: variant calling
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 17
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