The Terabase Search Engine: a large-scale relational database of short-read sequences

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• The exponential growth of DNA sequencing data presents significant challenges for searching raw read data.
• Existing methods struggle with the scale of genomic archives and applying relational logic across multiple whole-genome sequencing samples.

Purpose of the Study:

• To develop a high-performance data-query technology for large-scale DNA sequencing archives.
• To enable real-time searching of raw read data across numerous human genomes.

Main Methods:

• Development of a compact, efficiently-indexed database storing raw read data for over 250 human genomes.
• Implementation of the Terabase Search Engine for rapid retrieval of reads based on genomic location or sequence alignment.

Main Results:

• The Terabase Search Engine allows real-time querying of trillions of DNA bases.
• Users can retrieve all reads for any genomic location within seconds.
• Searches can be performed using genomic position ranges or on-the-fly sequence alignment.

Conclusions:

• The Terabase Search Engine offers a powerful solution for navigating massive genomic datasets.
• This technology facilitates efficient analysis of raw read data from large-scale sequencing projects.
• Public access to the database is provided for broader research utilization.