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RENANO: a REference-based compressor for NANOpore FASTQ files
Guillermo Dufort Y Álvarez1, Gadiel Seroussi1, Pablo Smircich2,3
1Facultad de Ingeniería, Universidad de la República, Montevideo, 11300, Uruguay.
Bioinformatics (Oxford, England)
|June 15, 2021
Summary
New data compression software, RENANO, efficiently compresses large nanopore sequencing FASTQ files. It offers significant improvements over existing methods, reducing data transmission and storage costs for genomic data.
Area of Science:
- Genomics
- Bioinformatics
- Data Compression
Background:
- Nanopore sequencing generates massive genomic datasets (up to 8.5 TB in <72 hours).
- Efficient compression methods are crucial for managing the costs of transmitting and storing this data.
Purpose of the Study:
- Introduce RENANO, a novel reference-based lossless compressor for nanopore FASTQ files.
- Enhance base call sequence compression compared to the state-of-the-art ENANO.
Main Methods:
- Developed two compression algorithms for RENANO based on reference genome availability (shared or compressor-side only).
- Evaluated RENANO's performance against ENANO and Genozip using public nanopore datasets.
Main Results:
- RENANO improved base call sequence compression by 39.8% (scenario 1) and 33.5% (scenario 2) over ENANO.
- Overall file compression improvements averaged 12.7% (scenario 1) and 10.6% (scenario 2).
- RENANO outperformed the general-purpose genomic compressor Genozip.
Conclusions:
- RENANO offers superior compression for nanopore sequencing data.
- The software is freely available, facilitating its adoption in genomic research.
