Abstract
Background: Biological sequence data have increased at a rapid rate due to the
advancements in sequencing technologies and reduction in the cost of sequencing data. The huge
increase in these data presents significant research challenges to researchers. In addition to meaningful
analysis, data storage is also a challenge, an increase in data production is outpacing the storage
capacity. Data compression is used to reduce the size of data and thus reduces storage requirements as
well as transmission cost over the internet.
Objective: This article presents a novel compression algorithm (FCompress) for Next Generation
Sequencing (NGS) data in FASTQ format.
Method: The proposed algorithm uses bits manipulation and dictionary-based compression for bases
compression. Headers are compressed with reference-based compression, whereas quality scores are
compressed with Huffman coding.
Results: The proposed algorithm is validated with experimental results on real datasets. The results are
compared with both general purpose and specialized compression programs.
Conclusion: The proposed algorithm produces better compression ratio in a comparable time to other
algorithms.
Keywords:
High throughput sequencing, NGS technologies, NGS sequence compression, Huffman Coding, Fcompress,
Algorithm.
Graphical Abstract
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