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Epiviz File Server: Query, transform and interactively explore data from indexed genomic files.

Jayaram Kancherla1,2,3, Yifan Yang3, Hyeyun Chae4

  • 1Center for Bioinformatics and Computational Biology.

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|July 4, 2020
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Summary
This summary is machine-generated.

Epiviz File Server offers in situ querying for genomic data, enabling efficient data retrieval and transformation for visualization and analysis. This Python library simplifies access to large genomic datasets, supporting custom genome browsers and workflow integration.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Genomic data repositories provide vast amounts of flat-file genomic data.
  • Researchers commonly download subsets of these files for exploratory data analysis.
  • Existing methods can be inefficient for accessing and processing large genomic datasets.

Purpose of the Study:

  • To develop a Python library for in situ querying of indexed genomic files.
  • To enable efficient data retrieval and transformation for visualization and analysis.
  • To decouple data access from specific analysis tools.

Main Methods:

  • Developed Epiviz File Server, a Python library implementing an in situ data query system.
  • Indexed local or remotely hosted genomic files for efficient access.
  • Created an abstract interface for defining computations independent of file location, format, or structure.

Main Results:

  • Demonstrated Epiviz File Server's capability for in situ data querying.
  • Showcased integration with Galaxy workflows for genomic data analysis.
  • Utilized Epiviz File Server to build a custom genome browser using Epigenome Roadmap data.

Conclusions:

  • Epiviz File Server provides a flexible and efficient system for accessing and transforming genomic data.
  • The library facilitates integration with existing bioinformatics workflows and tools.
  • Enables the creation of custom data visualization and analysis applications.