A benchmark study of compression software for human short-read sequence data

A benchmark study of compression software for human short-read sequence data

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Abstract Efficient data compression technologies are crucial to reduce the cost of long-term storage and file transfer in whole genome sequencing studies.This study benchmarked four specialized compression tools developed for paired-end fastq.gz files DRAGEN ORA 4.

3.4 (ORA), Genozip 15.0.

62, repaq 0.3.0, and SPRING 1.

1.1 using three subjects from the genome-in-a-bottle consortium that were sequenced 82 times on an Illumina NovaSeq 6000, with an average coverage of 35x.It additionally compared Genozip with SAMtools 1.

20 for the compression of BAM files.All tools provided lossless sheepshead bay boats compression.ORA and Genozip achieved compression ratios of approximately 1:6 when compressing fastq.

gz.repaq and SPRING had lower compression ratios of 1:2 and 1:4, respectively.repaq and SPRING took longer for both compression and decompression than ORA and Genozip.

Genozip had approximately 16% higher compression for BAM files than SAMtools.However, the BAM compression of SAMtools produces caruso milk thistle CRAM files, which are compatible with many software packages.ORA, repaq, and SPRING are limited to compressing fastq.

gz files, while Genozip supports various file formats.Although Genozip requires an annual license, its source code is freely available, ensuring sustainability.In conclusion, paired-end short-read sequence data can be efficiently compressed using specialized compression software.

Commercial tools offer higher compression ratios than freely available software.