Search and comparison of (epi)genomic feature patterns in multiple genome browser tracks
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SOFTWARE
Search and comparison of (epi)genomic feature patterns in multiple genome browser tracks Arnaud Ceol1,2, Piero Montanari3, Ilaria Bartolini3, Stefano Ceri4, Paolo Ciaccia3, Marco Patella3 and Marco Masseroli4*
*Correspondence: [email protected] 4 Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy Full list of author information is available at the end of the article
Abstract Background: Genome browsers are widely used for locating interesting genomic regions, but their interactive use is obviously limited to inspecting short genomic portions. An ideal interaction is to provide patterns of regions on the browser, and then extract other genomic regions over the whole genome where such patterns occur, ranked by similarity. Results: We developed SimSearch, an optimized pattern-search method and an open source plugin for the Integrated Genome Browser (IGB), to find genomic region sets that are similar to a given region pattern. It provides efficient visual genome-wide analytics computation in large datasets; the plugin supports intuitive user interactions for selecting an interesting pattern on IGB tracks and visualizing the computed occurrences of similar patterns along the entire genome. SimSearch also includes functions for the annotation and enrichment of results, and is enhanced with a Quickload repository including numerous epigenomic feature datasets from ENCODE and Roadmap Epigenomics. The paper also includes some use cases to show multiple genome-wide analyses of biological interest, which can be easily performed by taking advantage of the presented approach. Conclusions: The novel SimSearch method provides innovative support for effective genome-wide pattern search and visualization; its relevance and practical usefulness is demonstrated through a number of significant use cases of biological interest. The SimSearch IGB plugin, documentation, and code are freely available at https://deibgeco.github.io/simsearch-app/ and https://github.com/DEIB-GECO/simsearch-app/. Keywords: Computational genomics, Genome-wide pattern-search, Visual analytics, Genome browser
Background Next Generation Sequencing (NGS) technologies allow the production of high amounts of reliable high-throughput datasets about a variety of biomolecular signals in a single study [1]; such data are usually collected in huge repositories by large research consortia, such as the Encyclopedia of DNA Elements (ENCODE) [2] or the Roadmap Epigenomics © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise
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