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ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines.

Michael T Wolfinger1, Jörg Fallmann2, Florian Eggenhofer2

  • 1Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090, Vienna, Austria ; Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, Dr. Bohr-Gasse 9, A-1030 Vienna, Austria ; Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, Dr. Bohr-Gasse 9, A-1030 Vienna, Austria.

F1000Research
|August 6, 2015
PubMed
Summary
This summary is machine-generated.

ViennaNGS offers reusable Perl modules for building efficient next-generation sequencing (NGS) analysis pipelines. This software facilitates genomics data processing, from file conversion to complex analyses like splice junction identification.

Keywords:
PerlRNA-seqnext generation sequencingpipelinesread mapping

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) generates large datasets, necessitating efficient data processing.
  • Customized analysis workflows are crucial for extracting meaningful insights from genomics data.

Purpose of the Study:

  • To present ViennaNGS, a collection of Perl modules for constructing efficient NGS data processing pipelines.
  • To provide reusable software components for various genomics data analysis tasks.

Main Methods:

  • Development of integrated Perl modules for NGS data handling.
  • Implementation of functionalities for file format conversion, read mapping statistics, and RNA abundance normalization.
  • Inclusion of tools for splice junction identification, sequence motif analysis, and genome browser hub construction.

Main Results:

  • ViennaNGS provides a comprehensive suite of tools for diverse NGS data analysis needs.
  • The software supports common NGS file formats and integrates with popular command-line tools.
  • Automated construction of Assembly and Track Hubs for the UCSC genome browser is a key feature.

Conclusions:

  • ViennaNGS simplifies the creation of customized and efficient analysis pipelines for big genomics data.
  • The modular design promotes reusability and adaptability in bioinformatics workflows.
  • This collection of modules addresses the growing demand for streamlined NGS data processing solutions.