Sousa Maria J P, Pinho Armando J, Pratas Diogo
Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
Department of Electronics, Telecommunications and Informatics (DETI), University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
Bioinformatics. 2024 Nov 28;40(12). doi: 10.1093/bioinformatics/btae725.
Large-scale genomic projects grapple with the complex challenge of reducing medium- and long-term storage space and its associated energy consumption, monetary costs, and environmental footprint.
We present JARVIS3, an advanced tool engineered for the efficient reference-free compression of genomic sequences. JARVIS3 introduces a pioneering approach, specifically through enhanced table memory models and probabilistic lookup-tables applied in repeat models. These optimizations are pivotal in substantially enhancing computational efficiency. JARVIS3 offers three distinct profiles: (i) rapid computation with moderate compression, (ii) a balanced trade-off between time and compression, and (iii) slower computation with significantly higher compression ratios. The implementation of JARVIS3 is rooted in the C programming language, building upon the success of its predecessor, JARVIS2. JARVIS3 shows substantial speed improvements relative to JARVIS2 while providing slightly better compression. Furthermore, we provide a versatile C/Bash implementation, facilitating the application in FASTA and FASTQ data, including the capability for parallel computation. In addition, JARVIS3 includes a mode for outputting bit information, as well as providing the Normalized Compression and bit rates, facilitating compression-based analysis. This establishes JARVIS3 as an open-source solution for genomic data compression and analysis.
JARVIS3 is freely available at https://github.com/cobilab/jarvis3.
大型基因组项目面临着减少中长期存储空间及其相关能源消耗、货币成本和环境足迹这一复杂挑战。
我们展示了JARVIS3，这是一种为基因组序列的高效无参考压缩而设计的先进工具。JARVIS3引入了一种开创性方法，特别是通过增强表内存模型和应用于重复模型的概率查找表。这些优化对于大幅提高计算效率至关重要。JARVIS3提供三种不同的配置文件：（i）具有适度压缩的快速计算，（ii）时间与压缩之间的平衡权衡，以及（iii）具有显著更高压缩率的较慢计算。JARVIS3的实现基于C编程语言，它是在其前身JARVIS2成功的基础上构建的。与JARVIS2相比，JARVIS3显示出大幅的速度提升，同时提供略好的压缩效果。此外，我们提供了一种通用的C/Bash实现方式，便于在FASTA和FASTQ数据中应用，包括并行计算能力。此外，JARVIS3包括一种输出位信息的模式，以及提供归一化压缩率和比特率，便于基于压缩的分析。这使JARVIS3成为基因组数据压缩和分析的开源解决方案。
