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CoGI: Towards Compressing Genomes as an Image

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2015年第6期12卷 1275-1285页

作者： Xie, Xiaojing Zhou, Shuigeng Guan, Jihong Fudan Univ Shanghai Key Lab Intelligent Informat Proc Shanghai 200433 Peoples R China Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China Tongji Univ Dept Comp Sci & Technol Shanghai 201804 Peoples R China

Genomic science is now facing an explosive increase of data thanks to the fast development of sequencing technology. This situation poses serious challenges to genomic data storage and transferring. It is desirable to compress data to reduce storage and transferring cost, and thus to boost data distribution and utilization efficiency. Up to now, a number of algorithms / tools have been developed for compressing genomic sequences. Unlike the existing algorithms, most of which treat genomes as one-dimensional text strings and compress them based on dictionaries or probability models, this paper proposes a novel approach called CoGI (the abbreviation of Compressing Genomes as an Image) for genome compression, which transforms the genomic sequences to a two-dimensional binary image (or bitmap), then applies a rectangular partition coding algorithm to compress the binary image. CoGI can be used as either a reference-based compressor or a reference-free compressor. For the former, we develop two entropy-based algorithms to select a proper reference genome. Performance evaluation is conducted on various genomes. Experimental results show that the reference-based CoGI significantly outperforms two state-of-the-art reference-based genome compressors GReEn and RLZ-opt in both compression ratio and compression efficiency. It also achieves comparable compression ratio but two orders of magnitude higher compression efficiency in comparison with XM-one state-of-the-art reference-free genome compressor. Furthermore, our approach performs much better than Gzip-a general-purpose and widely-used compressor, in both compression speed and compression ratio. So, CoGI can serve as an effective and practical genome compressor. The source code and other related documents of CoGI are available at: http://***/projects/***.

关键词： Genomics genomes compression reference-based compression sequence matrixization rectangular partition coding entropy coding

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CoGI: Towards Compressing Genomes as an Image

CoGI: Towards Compressing Genomes as an Image

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13th Asia Pacific Bioinformatics Conference (APBC) - Systems Biology

关键词： Genomics genomes compression reference-based compression sequence matrixization rectangular partition coding entropy coding

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