ArticleBMC bioinformatics2017
LW-FQZip 2: a parallelized reference-based compression of FASTQ files.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- PQSDC: a parallel lossless compressor for quality scores data via sequences partition and run-length prediction mapping.Bioinformatics (Oxford, England) · 2024Article
- A Pipeline for Constructing Reference Genomes for Large Cohort-Specific Metagenome Compression.Microorganisms · 2023Article
- SparkGC: Spark based genome compression for large collections of genomes.BMC bioinformatics · 2022Article
- CMIC: an efficient quality score compressor with random access functionality.BMC bioinformatics · 2022Article
- GBDR: a Bayesian model for precise prediction of pathogenic microorganisms using 16S rRNA gene sequences.BMC genomics · 2022Article
- LCQS: an efficient lossless compression tool of quality scores with random access functionality.BMC bioinformatics · 2020Article
- Tackling the Challenges of FASTQ Referential Compression.Bioinformatics and biology insights · 2019Article
- FMSM: a novel computational model for predicting potential miRNA biomarkers for various human diseases.BMC systems biology · 2018Article
- Novel link prediction for large-scale miRNA-lncRNA interaction network in a bipartite graph.BMC medical genomics · 2018Article
- Comparison of Compression-Based Measures with Application to the Evolution of Primate Genomes.Entropy (Basel, Switzerland) · 2018Article
- BdBG: a bucket-based method for compressing genome sequencing data with dynamic de Bruijn graphs.PeerJ · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe rapid progress of high-throughput DNA sequencing techniques has dramatically reduced the costs of whole genome sequencing, which leads to revolutionary advances in gene industry. The explosively increasing volume of raw data outpaces the decreasing disk cost and the storage of huge sequencing data has become a bottleneck of downstream analyses. Data compression is considered as a solution to reduce the dependency on storage. Efficient sequencing data compression methods are highly demanded.
resultsIn this article, we present a lossless reference-based compression method namely LW-FQZip 2 targeted at FASTQ files. LW-FQZip 2 is improved from LW-FQZip 1 by introducing more efficient coding scheme and parallelism. Particularly, LW-FQZip 2 is equipped with a light-weight mapping model, bitwise prediction by partial matching model, arithmetic coding, and multi-threading parallelism. LW-FQZip 2 is evaluated on both short-read and long-read data generated from various sequencing platforms. The experimental results show that LW-FQZip 2 is able to obtain promising compression ratios at reasonable time and memory space costs.
conclusionsThe competence enables LW-FQZip 2 to serve as a candidate tool for archival or space-sensitive applications of high-throughput DNA sequencing data. LW-FQZip 2 is freely available at http://csse.szu.edu.cn/staff/zhuzx/LWFQZip2 and https://github.com/Zhuzxlab/LW-FQZip2 .
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