Altuna Akalin1, Vedran Franke1, Kristian Vlahoviček2, Christopher E Mason1, Dirk Schübeler2. 1. Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland, Bioinformatics Group, Department of Molecular Biology, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia, Department of Physiology and Biophysics and the Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA, Faculty of Science, University of Basel, 4051 Basel, Switzerland and Department of Informatics, University of Oslo, NO-0316 Oslo, Norway. 2. Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland, Bioinformatics Group, Department of Molecular Biology, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia, Department of Physiology and Biophysics and the Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA, Faculty of Science, University of Basel, 4051 Basel, Switzerland and Department of Informatics, University of Oslo, NO-0316 Oslo, Norway Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland, Bioinformatics Group, Department of Molecular Biology, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia, Department of Physiology and Biophysics and the Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA, Faculty of Science, University of Basel, 4051 Basel, Switzerland and Department of Informatics, University of Oslo, NO-0316 Oslo, Norway.
Abstract
UNLABELLED: Biological insights can be obtained through computational integration of genomics data sets consisting of diverse types of information. The integration is often hampered by a large variety of existing file formats, often containing similar information, and the necessity to use complicated tools to achieve the desired results. We have built an R package, genomation, to expedite the extraction of biological information from high throughput data. The package works with a variety of genomic interval file types and enables easy summarization and annotation of high throughput data sets with given genomic annotations. AVAILABILITY AND IMPLEMENTATION: The software is currently distributed under MIT artistic license and freely available at http://bioinformatics.mdc-berlin.de/genomation, and through the Bioconductor framework.
UNLABELLED: Biological insights can be obtained through computational integration of genomics data sets consisting of diverse types of information. The integration is often hampered by a large variety of existing file formats, often containing similar information, and the necessity to use complicated tools to achieve the desired results. We have built an R package, genomation, to expedite the extraction of biological information from high throughput data. The package works with a variety of genomic interval file types and enables easy summarization and annotation of high throughput data sets with given genomic annotations. AVAILABILITY AND IMPLEMENTATION: The software is currently distributed under MIT artistic license and freely available at http://bioinformatics.mdc-berlin.de/genomation, and through the Bioconductor framework.
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