Janka Puterová1, Tomáš Martínek2. 1. IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, Bozetechova 2, 612 66, Brno, Czechia. 2. IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, Bozetechova 2, 612 66, Brno, Czechia. martinto@fit.vutbr.cz.
Abstract
BACKGROUND: The insertion sequence elements (IS elements) represent the smallest and the most abundant mobile elements in prokaryotic genomes. It has been shown that they play a significant role in genome organization and evolution. To better understand their function in the host genome, it is desirable to have an effective detection and annotation tool. This need becomes even more crucial when considering rapid-growing genomic and metagenomic data. The existing tools for IS elements detection and annotation are usually based on comparing sequence similarity with a database of known IS families. Thus, they have limited ability to discover distant and putative novel IS elements. RESULTS: In this paper, we present digIS, a software tool based on profile hidden Markov models assembled from catalytic domains of transposases. It shows a very good performance in detecting known IS elements when tested on datasets with manually curated annotation. The main contribution of digIS is in its ability to detect distant and putative novel IS elements while maintaining a moderate level of false positives. In this category it outperforms existing tools, especially when tested on large datasets of archaeal and bacterial genomes. CONCLUSION: We provide digIS, a software tool using a novel approach based on manually curated profile hidden Markov models, which is able to detect distant and putative novel IS elements. Although digIS can find known IS elements as well, we expect it to be used primarily by scientists interested in finding novel IS elements. The tool is available at https://github.com/janka2012/digIS.
BACKGROUND: The insertion sequence elements (IS elements) represent the smallest and the most abundant mobile elements in prokaryotic genomes. It has been shown that they play a significant role in genome organization and evolution. To better understand their function in the host genome, it is desirable to have an effective detection and annotation tool. This need becomes even more crucial when considering rapid-growing genomic and metagenomic data. The existing tools for IS elements detection and annotation are usually based on comparing sequence similarity with a database of known IS families. Thus, they have limited ability to discover distant and putative novel IS elements. RESULTS: In this paper, we present digIS, a software tool based on profile hidden Markov models assembled from catalytic domains of transposases. It shows a very good performance in detecting known IS elements when tested on datasets with manually curated annotation. The main contribution of digIS is in its ability to detect distant and putative novel IS elements while maintaining a moderate level of false positives. In this category it outperforms existing tools, especially when tested on large datasets of archaeal and bacterial genomes. CONCLUSION: We provide digIS, a software tool using a novel approach based on manually curated profile hidden Markov models, which is able to detect distant and putative novel IS elements. Although digIS can find known IS elements as well, we expect it to be used primarily by scientists interested in finding novel IS elements. The tool is available at https://github.com/janka2012/digIS.
Entities:
Keywords:
Genome annotation; IS elements; Mobile element; Profile HMM; Prokaryotic genomes
Authors: Peter J A Cock; Tiago Antao; Jeffrey T Chang; Brad A Chapman; Cymon J Cox; Andrew Dalke; Iddo Friedberg; Thomas Hamelryck; Frank Kauff; Bartek Wilczynski; Michiel J L de Hoon Journal: Bioinformatics Date: 2009-03-20 Impact factor: 6.937