ArticleBioinformatics (Oxford, England)2015
Data-dependent bucketing improves reference-free compression of sequencing reads.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Efficient and robust search of microbial genomes via phylogenetic compression.Nature methods · 2025Article
- OReO: optimizing read order for practical compression.Bioinformatics advances · 2025Article
- Creating and Using Minimizer Sketches in Computational Genomics.Journal of computational biology : a journal of computational molecular cell biology · 2023Review
- Image-centric compression of protein structures improves space savings.BMC bioinformatics · 2023Article
- Hamming-shifting graph of genomic short reads: Efficient construction and its application for compression.PLoS computational biology · 2021Article
- Deficient autophagy in epithelial stem cells drives aging in the freshwater cnidarianDevelopment (Cambridge, England) · 2020Article
- Compression of genomic sequencing reads via hash-based reordering: algorithm and analysis.Bioinformatics (Oxford, England) · 2018Article
- Optimal compressed representation of high throughput sequence data via light assembly.Nature communications · 2018Article
- BdBG: a bucket-based method for compressing genome sequencing data with dynamic de Bruijn graphs.PeerJ · 2018Article
- LW-FQZip 2: a parallelized reference-based compression of FASTQ files.BMC bioinformatics · 2017Article
- Comparison of high-throughput sequencing data compression tools.Nature methods · 2016Article
- Computational Biology in the 21st Century: Scaling with Compressive Algorithms.Communications of the ACM · 2016Article
- Reference-free compression of high throughput sequencing data with a probabilistic de Bruijn graph.BMC bioinformatics · 2015Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
motivationThe storage and transmission of high-throughput sequencing data consumes significant resources. As our capacity to produce such data continues to increase, this burden will only grow. One approach to reduce storage and transmission requirements is to compress this sequencing data.
resultsWe present a novel technique to boost the compression of sequencing that is based on the concept of bucketing similar reads so that they appear nearby in the file. We demonstrate that, by adopting a data-dependent bucketing scheme and employing a number of encoding ideas, we can achieve substantially better compression ratios than existing de novo sequence compression tools, including other bucketing and reordering schemes. Our method, Mince, achieves up to a 45% reduction in file sizes (28% on average) compared with existing state-of-the-art de novo compression schemes. AVAILABILITY AND IMPLEMENTATION: Mince is written in C++11, is open source and has been made available under the GPLv3 license. It is available at http://www.cs.cmu.edu/∼ckingsf/software/mince. CONTACT: carlk@cs.cmu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
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.