Sequence Compression Benchmark (SCB) database—A comprehensive evaluation of reference-free compressors for FASTA-formatted sequences

Author:

Kryukov Kirill12ORCID,Ueda Mahoko Takahashi13ORCID,Nakagawa So1ORCID,Imanishi Tadashi1ORCID

Affiliation:

1. Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa 259–1193, Japan

2. Current address: Department of Genomics and Evolutionary Biology, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan

3. Current address: Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University, Bunkyo, Tokyo 113-8510, Japan

Abstract

Abstract Background Nearly all molecular sequence databases currently use gzip for data compression. Ongoing rapid accumulation of stored data calls for a more efficient compression tool. Although numerous compressors exist, both specialized and general-purpose, choosing one of them was difficult because no comprehensive analysis of their comparative advantages for sequence compression was available. Findings We systematically benchmarked 430 settings of 48 compressors (including 29 specialized sequence compressors and 19 general-purpose compressors) on representative FASTA-formatted datasets of DNA, RNA, and protein sequences. Each compressor was evaluated on 17 performance measures, including compression strength, as well as time and memory required for compression and decompression. We used 27 test datasets including individual genomes of various sizes, DNA and RNA datasets, and standard protein datasets. We summarized the results as the Sequence Compression Benchmark database (SCB database, http://kirr.dyndns.org/sequence-compression-benchmark/), which allows custom visualizations to be built for selected subsets of benchmark results. Conclusion We found that modern compressors offer a large improvement in compactness and speed compared to gzip. Our benchmark allows compressors and their settings to be compared using a variety of performance measures, offering the opportunity to select the optimal compressor on the basis of the data type and usage scenario specific to a particular application.

Funder

Japan Society for the Promotion of Science

Scientific Research on Innovative Areas

Takeda Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

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