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Fine-tuning the Size and Minimizing the Noise of Solid-state Nanopores
Published on: October 31, 2013
13.6K
Nanopore quality score resolution can be reduced with little effect on downstream analysis
Martín Rivara-Espasandín1,2,3, Lucía Balestrazzi1,4, Guillermo Dufort Y Álvarez1
1Instituto de Computación, Facultad de Ingeniería, Universidad de la República, 11300 Montevideo, Uruguay.
Bioinformatics Advances
|January 26, 2023
Summary
Quantizing nanopore sequencing quality scores has minimal impact on downstream analysis and can significantly reduce file size. This suggests current precision levels are unnecessarily high, enabling efficient data compression.
Area of Science:
- Bioinformatics
- Genomics
- Data Compression
Background:
- High precision in nanopore sequencing quality scores increases FASTQ file size.
- These scores are a major component of data storage in lossless compression.
Purpose of the Study:
- Investigate the impact of quality score quantization on nanopore sequencing data analysis.
- Evaluate the potential for lossy compression of nanopore sequencing data.
Main Methods:
- Performed de novo assembly polishing and variant calling on human and mock microbial genomes.
- Utilized various pipelines, coverage levels, and quality score quantizers.
- Assessed results using original and quantized quality scores.
Main Results:
- Quality score quantization showed minimal differences, and sometimes improvements, in downstream analysis results.
- Lossy compression via quantization led to substantial storage savings, even with standard tools like gzip.
- Current nanopore quality score precision may be excessive.
Conclusions:
- Quantization of nanopore sequencing quality scores is a viable strategy for reducing data size without compromising downstream analysis.
- Lossy compression methods are recommended for nanopore sequencing data to improve storage efficiency.
