Lossless and reference-free compression of FASTQ/A files using GeneSqueeze.

ABSTRACT: As sequencing becomes more accessible, there is an acute need for novel compression methods to efficiently store sequencing files. Omics analytics can leverage sequencing technologies to enhance biomedical research and individualize patient care, but sequencing files demand immense storage capabilities, particularly when sequencing is utilized for longitudinal studies. Addressing the storage challenges posed by these technologies is crucial for omics analytics to achieve their full potential. We present a novel lossless, reference-free compression algorithm, GeneSqueeze, that leverages the patterns inherent in the underlying components of FASTQ files to solve this need. GeneSqueeze's benefits include an auto-tuning compression protocol based on each file's distribution, lossless preservati

SUBMITTER: Nazari F 

PROVIDER: S-EPMC11696233 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature