Chen Shifu, Chen Yaru, Wang Zhouyang, Qin Wenjian, Zhang Jing, Nand Heera, Zhang Jishuai, Li Jun, Zhang Xiaoni, Liang Xiaoming, Xu Mingyan
HaploX Biotechnology, Shenzhen, Guangdong, China.
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.
Front Genet. 2023 Sep 21;14:1260531. doi: 10.3389/fgene.2023.1260531. eCollection 2023.
With the increasing throughput of modern sequencing instruments, the cost of storing and transmitting sequencing data has also increased dramatically. Although many tools have been developed to compress sequencing data, there is still a need to develop a compressor with a higher compression ratio. We present a two-step framework for compressing sequencing data in this paper. The first step is to repack original data into a binary stream, while the second step is to compress the stream with a LZMA encoder. We develop a new strategy to encode the original file into a LZMA highly compressed stream. In addition an FPGA-accelerated of LZMA was implemented to speedup the second step. As a demonstration, we present repaq as a lossless non-reference compressor of FASTQ format files. We introduced a multifile redundancy elimination method, which is very useful for compressing paired-end sequencing data. According to our test results, the compression ratio of repaq is much higher than other FASTQ compressors. For some deep sequencing data, the compression ratio of repaq can be higher than 25, almost four times of Gzip. The framework presented in this paper can also be applied to develop new tools for compressing other sequencing data. The open-source code of repaq is available at: https://github.com/OpenGene/repaq.
随着现代测序仪器通量的不断提高,存储和传输测序数据的成本也急剧增加。尽管已经开发了许多工具来压缩测序数据,但仍需要开发一种具有更高压缩率的压缩器。在本文中,我们提出了一个用于压缩测序数据的两步框架。第一步是将原始数据重新打包成二进制流,而第二步是使用LZMA编码器对该流进行压缩。我们开发了一种新策略,将原始文件编码为LZMA高度压缩流。此外,还实现了LZMA的FPGA加速,以加快第二步的速度。作为演示,我们展示了repaq作为FASTQ格式文件的无损非参考压缩器。我们引入了一种多文件冗余消除方法,这对于压缩双端测序数据非常有用。根据我们的测试结果,repaq的压缩率远高于其他FASTQ压缩器。对于一些深度测序数据,repaq的压缩率可以高于25,几乎是Gzip的四倍。本文提出的框架也可应用于开发用于压缩其他测序数据的新工具。repaq的开源代码可在以下网址获取:https://github.com/OpenGene/repaq。