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Novel Sequence Discovery by Subtractive Genomics
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Sequencing data discovery with MetaSeek.

Adrienne Hoarfrost1, Nick Brown2, C Titus Brown3

  • 1Department of Marine Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Bioinformatics (Oxford, England)
|June 22, 2019
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Summary
This summary is machine-generated.

MetaSeek simplifies the discovery of sequencing datasets by enabling flexible searches across metadata. This tool streamlines the curation process for large-scale meta-analyses, saving researchers time.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Exponential growth in sequencing data resources necessitates efficient methods for large-scale meta-analyses.
  • Current curation of integrated sequencing datasets is time-intensive and imprecise, hindering research.
  • Need for a tool to quickly identify relevant sequencing data based on specific research priorities.

Purpose of the Study:

  • To introduce MetaSeek, a novel sequencing data discovery tool.
  • To enable users to flexibly search and filter sequencing datasets based on any metadata field.
  • To expedite the identification of relevant datasets for meta-analyses and other research applications.

Main Methods:

  • MetaSeek automatically scrapes metadata from the Sequence Read Archive (SRA).
  • It cleans, parses, and structures messy user-provided metadata into a compliant database.
  • Predicts missing metadata fields to enhance data completeness.
  • Provides a web-based graphical user interface (GUI) and a programmatic API.

Main Results:

  • MetaSeek enables rapid searching and filtering of sequencing metadata.
  • Users can visualize, save, share, and download relevant datasets efficiently.
  • The tool supports flexible querying across all metadata fields.

Conclusions:

  • MetaSeek significantly improves the efficiency and precision of sequencing data discovery.
  • It addresses the challenges of curating large-scale integrated datasets for meta-analyses.
  • The tool empowers researchers to quickly find and utilize relevant sequencing data.