ArticleSource code for biology and medicine2019
MZPAQ: a FASTQ data compression tool.
Article in Source code for biology and medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Lossless and reference-free compression of FASTQ/A files using GeneSqueeze.Scientific reports · 2025Article
- Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa.Scientific data · 2023Article
- SCA-NGS: Secure compression algorithm for next generation sequencing data using genetic operators and block sorting.Science progressArticle
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDue to the technological progress in Next Generation Sequencing (NGS), the amount of genomic data that is produced daily has seen a tremendous increase. This increase has shifted the bottleneck of genomic projects from sequencing to computation and specifically storing, managing and analyzing the large amount of NGS data. Compression tools can reduce the physical storage used to save large amount of genomic data as well as the bandwidth used to transfer this data. Recently, DNA sequence compression has gained much attention among researchers.
resultsIn this paper, we study different techniques and algorithms used to compress genomic data. Most of these techniques take advantage of some properties that are unique to DNA sequences in order to improve the compression rate, and usually perform better than general-purpose compressors. By exploring the performance of available algorithms, we produce a powerful compression tool for NGS data called MZPAQ. Results show that MZPAQ outperforms state-of-the-art tools on all benchmark datasets obtained from a recent survey in terms of compression ratio. MZPAQ offers the best compression ratios regardless of the sequencing platform or the size of the data.
conclusionsCurrently, MZPAQ's strength is its higher compression ratio as well as its compatibility with all major sequencing platforms. MZPAQ is more suitable when the size of compressed data is crucial, such as long-term storage and data transfer. More efforts will be made in the future to target other aspects such as compression speed and memory utilization.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.