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Rgb: a scriptable genome browser for R.

Sylvain Mareschal1, Sydney Dubois1, Thierry Lecroq1

  • 1Centre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, France.

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Summary
This summary is machine-generated.

A new R package offers efficient interactive genome browsing for bioinformatics. It handles large genomic datasets, outperforming existing solutions in speed and memory usage.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • R is a widely adopted tool in bioinformatics.
  • Genomic data analysis presents computational challenges.
  • Existing R packages lack efficiency for interactive genome browsing.

Purpose of the Study:

  • To introduce a novel R package for efficient interactive genome browsing.
  • To address the need for computationally intensive genomic data manipulation in R.
  • To provide a multilevel interface for diverse user needs.

Main Methods:

  • Development of a new R package for genome browsing.
  • Implementation of a multilevel interface from full browser to low-level methods.
  • Testing and benchmarking against existing solutions using a human dataset.

Main Results:

  • The proposed R package demonstrates superior time and memory efficiency.
  • Outperformed existing solutions by several orders of magnitude in human dataset analysis.
  • Offers a versatile interface suitable for various bioinformatics tasks.

Conclusions:

  • The new R package is an essential tool for bioinformatics, particularly for handling large genomic datasets.
  • Its efficiency makes it suitable for computationally intensive tasks like interactive genome browsing.
  • Free licensing and initiatives like Bioconductor further enhance its accessibility and utility.