LFastqC: A lossless non-reference-based FASTQ compressor

Autoři: Sultan Al Yami aff001;  Chun-Hsi Huang aff001
Působiště autorů: Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, United States of America aff001;  Computer Science and Information System, Najran University, Najran, Saudi Arabia aff002
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224806


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.

Klíčová slova:

Algorithms – Arithmetic – Compression – Data management – Next-generation sequencing – Nucleotide sequencing – Spring – Data compression


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Článek vyšel v časopise


2019 Číslo 11