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Reducing the resolution of DNA sequence quality scores can significantly decrease file sizes without impacting alignment accuracy. This study identifies a safe distortion threshold for quality score representation, optimizing data handling for genomic and RNA-seq datasets.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • High-entropy quality scores in sequence data significantly increase file sizes.
  • Current methods for reducing quality score resolution lack consensus due to potential side effects on downstream analysis.

Purpose of the Study:

  • To develop a method for reducing the resolution of quality score scales without compromising sequence alignment.
  • To identify a distortion threshold for safe quality score representation.

Main Methods:

  • Leveraging HISAT2 aligner's penalty functions to rebin quality scores.
  • Testing the rebinning method on whole-genome and RNA-seq data.
  • Comparing the proposed method with three existing lossy compression techniques for quality scores.

Main Results:

  • A method was developed to rebin quality scores, effectively reducing data size.
  • The rebinning approach demonstrated no adverse impact on sequence alignment accuracy.
  • A specific distortion threshold was identified for safe quality score representation.

Conclusions:

  • Quality score rebinning offers a viable strategy for reducing sequence data file sizes.
  • The identified distortion threshold ensures data integrity and alignment performance.
  • This approach provides an effective alternative to existing lossy compression methods for genomic data.