Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107184
Title: | Clustering-based compression for population DNA sequences | Authors: | Cheng, KO Law, NF Siu, WC |
Issue Date: | Jan-2019 | Source: | IEEE/ACM transactions on computational biology and bioinformatics, Jan.-Feb. 2019, v. 16, no. 1, p. 208-221 | Abstract: | Due to the advancement of DNA sequencing techniques, the number of sequenced individual genomes has experienced an exponential growth. Thus, effective compression of this kind of sequences is highly desired. In this work, we present a novel compression algorithm called Reference-based Compression algorithm using the concept of Clustering (RCC). The rationale behind RCC is based on the observation about the existence of substructures within the population sequences. To utilize these substructures, k-means clustering is employed to partition sequences into clusters for better compression. A reference sequence is then constructed for each cluster so that sequences in that cluster can be compressed by referring to this reference sequence. The reference sequence of each cluster is also compressed with reference to a sequence which is derived from all the reference sequences. Experiments show that RCC can further reduce the compressed size by up to 91.0 percent when compared with state-of-the-art compression approaches. There is a compromise between compressed size and processing time. The current implementation in Matlab has time complexity in a factor of thousands higher than the existing algorithms implemented in C/C++. Further investigation is required to improve processing time in future. | Keywords: | Biology and genetics Clustering Compression technologies Data compaction and compression |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE/ACM transactions on computational biology and bioinformatics | ISSN: | 1545-5963 | EISSN: | 1557-9964 | DOI: | 10.1109/TCBB.2017.2762302 | Rights: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication K. -O. Cheng, N. -F. Law and W. -C. Siu, "Clustering-Based Compression for Population DNA Sequences," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 16, no. 1, pp. 208-221, Jan.-Feb. 2019 is available at https://doi.org/10.1109/TCBB.2017.2762302. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Cheng_Clustering-Based_Compression_Population.pdf | Pre-Published version | 14.95 MB | Adobe PDF | View/Open |
Page views
1
Citations as of Jun 30, 2024
Downloads
2
Citations as of Jun 30, 2024
SCOPUSTM
Citations
13
Citations as of Jun 27, 2024
WEB OF SCIENCETM
Citations
8
Citations as of Jun 27, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.