Genomic Sequence Data Compression using Lempel-Ziv-Welch Algorithm with Indexed Multiple Dictionary
Keerthy A. S.1, S. Manju Priya2
1Dr. Keerthy A S* , Research Scholar, Department of Computer Science, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu) India.
2Dr. S. Manju Priya, Professor, Department of CS, CA & IT, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu) India.
Manuscript received on November 25, 2019. | Revised Manuscript received on December 08, 2019. | Manuscript published on December 30, 2019. | PP: 541-547 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3278129219/2019©BEIESP | DOI: 10.35940/ijeat.B3278.129219
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the advancement in technology and development of High Throughput System (HTS), the amount of genomic data generated per day per laboratory across the globe is surpassing the Moore’s law. The huge amount of data generated is of concern to the biologists with respect to their storage as well as transmission across different locations for further analysis. Compression of the genomic data is the wise option to overcome the problems arising from the data deluge. This paper discusses various algorithms that exists for compression of genomic data as well as a few general purpose algorithms and proposes a LZW-based compression algorithm that uses indexed multiple dictionaries for compression. The proposed method exhibits an average compression ratio of 0.41 bits per base and an average compression time of 6.45 secs for a DNA sequence of an average size 105.9 KB.
Keywords: Compression, lossless, LZW, DNA, Multiple Dictionary, Decompression.