Enhort: a platform for deep analysis of genomic positions

The rise of high-throughput methods in genomic research greatly expanded our knowledge about the functionality of the genome. At the same time, the amount of available genomic position data increased massively, e.g., through genome-wide profiling of protein binding, virus integration or DNA methylat...

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Bibliographic Details
Published in:PeerJ. Computer science 2019-06, Vol.5, p.e198-e198, Article e198
Main Authors: Menzel, Michael, Koch, Peter, Glasenhardt, Stefan, Gogol-Döring, Andreas
Format: Article
Language:English
Subjects:
Analysis
Bioinformatics
Computational Biology
Criminal investigation
Data analysis
Data processing
DNA
DNA sequencing
Gene therapy
Genetic research
Genome annotation
Genomes
Genomics
Integration profiling
Methods
Methylation
Next-generation sequencing
Protein binding
Software
Technology application
Transcription (Genetics)
Virology
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Summary:The rise of high-throughput methods in genomic research greatly expanded our knowledge about the functionality of the genome. At the same time, the amount of available genomic position data increased massively, e.g., through genome-wide profiling of protein binding, virus integration or DNA methylation. However, there is no specialized software to investigate integration site profiles of virus integration or transcription factor binding sites by correlating the sites with the diversity of available genomic annotations. Here we present Enhort, a user-friendly software tool for relating large sets of genomic positions to a variety of annotations. It functions as a statistics based genome browser, not focused on a single locus but analyzing many genomic positions simultaneously. Enhort provides comprehensive yet easy-to-use methods for statistical analysis, visualization, and the adjustment of background models according to experimental conditions and scientific questions. Enhort is publicly available online at enhort.mni.thm.de and published under GNU General Public License.
ISSN:2376-5992
2376-5992
DOI:10.7717/peerj-cs.198