4.7 Article

ReadXplorer 2-detailed read mapping analysis and visualization from one single source

Journal

BIOINFORMATICS
Volume 32, Issue 24, Pages 3702-3708

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btw541

Keywords

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Funding

  1. German Center for Infection Research (DZIF) project 'DZIF Bioinformatics Platform' [8000 701-3]
  2. BMBF within de.NBI network [FKZ 031A533]
  3. CLIB-Graduate Cluster Industrial Biotechnology - Ministry of Innovation of North Rhine-Westphalia
  4. LOEWE focus group Medical RNomics (State of Hessen, Germany)
  5. Deutsche Forschungsgemeinschaft (DFG) within Transregional Collaborative Research Centre 81 [TRR81]

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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. Availability and Implementation: http://www.readxplorer.org Contact: readxplorer@computational.bio.uni-giessen.de Supplementary information: Supplementary data are available at Bioinformatics online.

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