Journalartikel

Jahr der Veröffentlichung: 2016

Seiten: 3702-3708

Zeitschrift: Bioinformatics

Bandnummer: 32

Heftnummer: 24

ISSN: 1367-4803

eISSN: 1460-2059

Open Access Status: Hybrid

DOI Link: https://doi.org/10.1093/bioinformatics/btw541

Verlag: Oxford University Press

Abstract: 
Motivation: The vast amount of already available and currently generated read mapping data requires comprehensive visualization, and should benefit from bioinformatics tools offering a wide spectrum of analysis functionality from just one source. Appropriate handling of multiple mapped reads during mapping analyses remains an issue that demands improvement.Results: The capabilities of the read mapping analysis and visualization tool ReadXplorer were vastly enhanced. Here, we present an even finer granulated read mapping classification, improving the level of detail for analyses and visualizations. The spectrum of automatic analysis functions has been broadened to include genome rearrangement detection as well as correlation analysis between two mapping data sets. Existing functions were refined and enhanced, namely the computation of differentially expressed genes, the read count and normalization analysis and the transcription start site detection. Additionally, ReadXplorer 2 features a highly improved support for large eukaryotic data sets and a command line version, enabling its integration into workflows. Finally, the new version is now able to display any kind of tabular results from other bioinformatics tools.

Harvard-Zitierstil: Hilker, R., Stadermann, K., Schwengers, O., Anisiforov, E., Jaenicke, S., Weisshaar, B., et al. (2016) ReadXplorer 2-detailed read mapping analysis and visualization from one single source, Bioinformatics, 32(24), pp. 3702-3708. https://doi.org/10.1093/bioinformatics/btw541

APA-Zitierstil: Hilker, R., Stadermann, K., Schwengers, O., Anisiforov, E., Jaenicke, S., Weisshaar, B., Zimmermann, T., & Goesmann, A. (2016). ReadXplorer 2-detailed read mapping analysis and visualization from one single source. Bioinformatics. 32(24), 3702-3708. https://doi.org/10.1093/bioinformatics/btw541