Genome Environment Browser (GEB): A dynamic browser for visualising high-throughput experimental data in the context of genome features

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Abstract

Background: There is accumulating evidence that the milieu of repeat elements and other non-genic sequence features at a given chromosomal locus, here defined as the genome environment, can play an important role in regulating chromosomal processes such as transcription, replication and recombination. The availability of whole-genome sequences has allowed us to annotate the genome environment of any locus in detail. The development of genome wide experimental analyses of gene expression, chromatin modification and chromatin proteins means that it is now possible to identify potential links between chromosomal processes and the underlying genome environment. There is a need for novel bioinformatic tools that facilitate these studies. Results: We developed the Genome Environment Browser (GEB) in order to visualise the integration of experimental data from large scale high throughput analyses with repeat sequence features that define the local genome environment. The browser has incorporated dynamic scales adjustable in real-time, which enables scanning of large regions of the genome as well as detailed investigation of local regions on the same page without the need to load new pages. The interface also accommodates a 2-dimensional display of repetitive features which vary substantially in size, such as LINE-1 repeats. Specific queries for preliminary quantitative analysis of genome features can also be formulated, results of which can be exported for further analysis. Conclusion: The Genome Environment Browser is a versatile program which can be easily adapted for displaying all types of genome data with known genomic coordinates. It is currently available at http://web.bioinformatics.ic.ac.uk/geb/. © 2008 Huntley et al; licensee BioMed Central Ltd.

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Huntley, D., Tang, Y. A., Nesterova, T. B., Butcher, S., & Brockdorff, N. (2008). Genome Environment Browser (GEB): A dynamic browser for visualising high-throughput experimental data in the context of genome features. BMC Bioinformatics, 9. https://doi.org/10.1186/1471-2105-9-501

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