Genome-wide search of nucleosome patterns using visual analytics.
[EN]The Burrows-Wheeler transform (BWT) is widely used for the fast alignment of high-throughput sequence data. This method also has potential applications in other areas of bioinformatics, and it can be specially useful for the fast searching of patterns on coverage data from different sources. We...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad de Salamanca (USAL) |
| Repositorio: | GREDOS. Repositorio Institucional de la Universidad de Salamanca |
| OAI Identifier: | oai:gredos.usal.es:10366/154276 |
| Acceso en línea: | http://hdl.handle.net/10366/154276 |
| Access Level: | acceso abierto |
| Palabra clave: | Burrows-Wheeler Transform Nucleosome maps Visual Analytics Information Visualization Genome Browser Software Nucleosomes Genome Algorithms nucleosomas programas informáticos algoritmos genoma |
| Sumario: | [EN]The Burrows-Wheeler transform (BWT) is widely used for the fast alignment of high-throughput sequence data. This method also has potential applications in other areas of bioinformatics, and it can be specially useful for the fast searching of patterns on coverage data from different sources. We present a nucleosome pattern search method that converts levels of nucleosomal occupancy to a sequence-like format to which BWT searches can be applied. The method is embedded in a nucleosome map browser, 'Nucleosee', an interactive visual tool specifically designed to enhance BWT searches, giving them context and making them suitable for visual discourse analysis of the results. The proposed method is fast, flexible and sufficiently generic for the exploration of data in a broad and interactive way. The proposed algorithm and visual browser are available for testing at http://cpg3.der.usal.es/nucleosee. The source code and installation packages are also available at https://github.com/rodrigoSantamaria/nucleosee. Supplementary data are available at Bioinformatics online. |
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