ArticlePloS one2019
LFastqC: A lossless non-reference-based FASTQ compressor.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Dear-OMG: An Omics-General Compression Method for Genomics, Proteomics and Metabolomics Data.Interdisciplinary sciences, computational life sciences · 2026Article
- OReO: optimizing read order for practical compression.Bioinformatics advances · 2025Article
- PMFFRC: a large-scale genomic short reads compression optimizer via memory modeling and redundant clustering.BMC bioinformatics · 2023Article
- Efficient sequencing data compression and FPGA acceleration based on a two-step framework.Frontiers in genetics · 2023Article
- Efficient compression of SARS-CoV-2 genome data using Nucleotide Archival Format.Patterns (New York, N.Y.) · 2022Review
- ACO:lossless quality score compression based on adaptive coding order.BMC bioinformatics · 2022Article
- FCLQC: fast and concurrent lossless quality scores compressor.BMC bioinformatics · 2021Article
- Sequence Compression Benchmark (SCB) database-A comprehensive evaluation of reference-free compressors for FASTA-formatted sequences.GigaScience · 2020Article
- SCA-NGS: Secure compression algorithm for next generation sequencing data using genetic operators and block sorting.Science progressArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The cost-effectiveness of next-generation sequencing (NGS) has led to the advancement of genomic research, thereby regularly generating a large amount of raw data that often requires efficient infrastructures such as data centers to manage the storage and transmission of such data. The generated NGS data are highly redundant and need to be efficiently compressed to reduce the cost of storage space and transmission bandwidth. We present a lossless, non-reference-based FASTQ compression algorithm, known as LFastqC, an improvement over the LFQC tool, to address these issues. LFastqC is compared with several state-of-the-art compressors, and the results indicate that LFastqC achieves better compression ratios for important datasets such as the LS454, PacBio, and MinION. Moreover, LFastqC has a better compression and decompression speed than LFQC, which was previously the top-performing compression algorithm for the LS454 dataset. LFastqC is freely available at https://github.uconn.edu/sya12005/LFastqC.
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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.