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mod_bio: Apache modules for Next-Generation sequencing data.

Pierre Lindenbaum1, Richard Redon1

  • 1Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, L'Institut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, L'Institut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, L'Institut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, L'Institut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, L'Institut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, L'Institut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, L'Institut du Thorax, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Centre Hospitalier Universitaire (CHU) de Nantes, L'Institut du Thorax, Service de Cardiologie, 44000 Nantes and Université de Nantes, 44000 Nantes, France.

Bioinformatics (Oxford, England)
|September 7, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces mod_bio, a web-accessible module for querying biological data files like FASTQ and BAM directly through a web browser. It enables seamless data retrieval and visualization for researchers.

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Area of Science:

  • Bioinformatics
  • Web Technologies
  • Genomic Data Management

Background:

  • Accessing and querying large biological datasets (FASTQ, tabix, FASTA, BAM) can be challenging.
  • Traditional methods often require specialized software and command-line interfaces.
  • Efficient web-based solutions are needed for broader accessibility.

Purpose of the Study:

  • To develop a novel Apache HTTP server module (mod_bio) for simplified access to biological data files.
  • To enable querying of various genomic file formats directly via a web browser.
  • To facilitate data sharing and analysis through web services.

Main Methods:

  • Implementation of mod_bio as a set of modules for the Apache HTTP server.
  • Support for accessing and querying FASTQ, tabix, FASTA, and BAM file formats.
  • Data output formats include plain text, HTML, XML, JSON, and JSON-P.
  • Development of a JavaScript-based genome browser utilizing JSON-P for cross-domain communication.

Main Results:

  • mod_bio provides a user-friendly web interface for biological data querying.
  • Multiple data formats are supported for flexible data integration.
  • A functional genome browser demonstrates the utility of the JSON-P communication technique.
  • The module enhances the accessibility of genomic data for researchers.

Conclusions:

  • mod_bio offers an efficient solution for web-based access and querying of biological data.
  • The developed modules simplify data retrieval and integration into web applications.
  • The provided genome browser serves as a practical example of cross-domain web service implementation.
  • mod_bio enhances the usability of genomic data through web technologies.