Comparison of high-throughput sequencing data compression tools
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Updated: Mar 13, 2026

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
Published on: December 13, 2024
Ibrahim Numanagić1, James K Bonfield2, Faraz Hach1,3
1School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Abstract:
High-throughput sequencing (HTS) data are commonly stored as raw sequencing reads in FASTQ format or as reads mapped to a reference, in SAM format, both with large memory footprints. Worldwide growth of HTS data has prompted the development of compression methods that aim to significantly reduce HTS data size. Here we report on a benchmarking study of available compression methods on a comprehensive set of HTS data using an automated framework.
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