Broom: application for non-redundant storage of high throughput sequencing data

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• High-throughput sequencing (HTS) technology has rapidly advanced, increasing data output while decreasing costs.
• The exponential growth in HTS data presents significant storage and transfer challenges for smaller research entities.
• Current HTS data storage strategies need reevaluation in light of improved sequencing quality and coverage.

Purpose of the Study:

• To develop a novel application for efficient storage of high-throughput sequencing data.
• To address the data management challenges faced by small labs and individual researchers using HTS.
• To leverage advancements in sequencing quality for optimized data storage solutions.

Main Methods:

• Developed Broom, a stand-alone C++ application.
• Implemented algorithms for selecting and storing only high-quality sequencing reads.
• Enabled high compression rates for reduced data footprint.
• Supported single and paired-end reads in FASTQ and FASTA formats.

Main Results:

• Broom achieves extremely high compression rates for HTS data.
• The application effectively selects and stores only high-quality sequencing reads.
• Data can be decompressed into FASTA format.
• The software is available as a stand-alone application.

Conclusions:

• Broom offers a viable solution for managing large HTS datasets.
• The application significantly reduces storage requirements for sequencing data.
• This tool can facilitate HTS data accessibility and analysis for researchers with limited resources.