一个无损的无引用序列压缩算法,利用语法,统计和替换规则
Subhankar Roy1,2, Dilip Kumar Maity1, Anirban Mukhopadhyay2
1Department of Computer Science & Engineering, Academy of Technology, Adisaptagram, Hooghly-712121, India.
Briefings in functional genomics
|January 8, 2025
概括
一个新的无损序列压缩器,GraSS,通过使用序列特定的功能来增强DNA和RNA数据的压缩. 这种方法优于现有的算法,为基因组研究提供高效的数据压缩.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 像Gzip和Zstd这样的通用压缩机由于缺乏序列特定特征利用,对DNA/RNA序列表现不佳.
- 现有的压缩机需要耗时的参数调整,以实现有效的分子序列压缩.
研究的目的:
- 推出GraSS,一个新的无参考,无损序列压缩器,专为DNA和RNA数据设计.
- 为了提高序列压缩效率,利用基于语法,统计和替换规则的方法.
主要方法:
- 在分子序列数据库中常见的GraSS处理原始,FASTA和多FASTA格式.
- 压缩机利用DNA和RNA序列的固有特征进行有效的压缩.
主要成果:
- 格拉斯实现了DNA序列的4.5和RNA序列的19.6的加权平均压缩比 (WACR).
- DNA序列体的总压缩时间 (TCT) 为246.8秒.
- 与先进的算法相比,GraSS表现出卓越的性能,特别是对于重复序列,具有竞争力的解压缩时间和资源使用.
结论:
- 在分子序列的无损压缩方面,GraSS提供了显著的进步.
- 拟议的方法为处理大规模基因组数据提供了高效和有效的解决方案.
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