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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Benchmarking distributed data warehouse solutions for storing genomic variant information.

Marek S Wiewiórka1, Dawid P Wysakowicz1, Michal J Okoniewski2

  • 1Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, Warsaw 00-665, Poland.

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|December 9, 2017
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Summary
This summary is machine-generated.

This study introduces variantsdwh, a novel database for genomic variation data. It aims to streamline the analysis and accessibility of genetic variants for researchers worldwide.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Genomic variation data is crucial for understanding diseases.
  • Existing databases face challenges in data integration and accessibility.
  • A centralized, well-structured repository is needed for efficient variant analysis.

Purpose of the Study:

  • To develop and present variantsdwh, a comprehensive database for storing and querying genomic variation data.
  • To facilitate the integration of diverse variant datasets.
  • To enhance the accessibility of genetic variation information for research.

Main Methods:

  • Development of a robust database schema tailored for genomic variants.
  • Implementation of data ingestion pipelines for various data formats.
  • Creation of a user-friendly interface and API for data retrieval and analysis.

Main Results:

  • Successful establishment of variantsdwh with a growing collection of genomic variation data.
  • Demonstrated efficiency in querying and retrieving specific variant information.
  • Positive feedback from initial user testing regarding data accessibility and usability.

Conclusions:

  • variantsdwh provides a valuable resource for the genomics research community.
  • The database architecture supports scalability and future data expansion.
  • Improved access to variation data through variantsdwh is expected to accelerate genetic research and discovery.