Muhammad Sardaraz* and Muhammad Tahir Pages 123 - 129 ( 7 )
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.
High throughput sequencing, NGS technologies, NGS sequence compression, Huffman Coding, Fcompress, Algorithm.
Department of Computer Science, COMSATS Institute of Information Technology, Attock, Department of Computer Science, COMSATS Institute of Information Technology, Attock