基因组
数据压缩
冗余(工程)
计算机科学
管道(软件)
参考基因组
数据挖掘
压缩(物理)
压缩比
基因组
数据冗余
计算生物学
数据库
生物
人工智能
工程类
遗传学
基因
复合材料
汽车工程
操作系统
材料科学
程序设计语言
内燃机
作者
L. Wang,Renpeng Ding,Shixu He,Qinyu Wang,Yan Zhou
出处
期刊:Microorganisms
[Multidisciplinary Digital Publishing Institute]
日期:2023-10-14
卷期号:11 (10): 2560-2560
被引量:1
标识
DOI:10.3390/microorganisms11102560
摘要
Metagenomic data compression is very important as metagenomic projects are facing the challenges of larger data volumes per sample and more samples nowadays. Reference-based compression is a promising method to obtain a high compression ratio. However, existing microbial reference genome databases are not suitable to be directly used as references for compression due to their large size and redundancy, and different metagenomic cohorts often have various microbial compositions. We present a novel pipeline that generated simplified and tailored reference genomes for large metagenomic cohorts, enabling the reference-based compression of metagenomic data. We constructed customized reference genomes, ranging from 2.4 to 3.9 GB, for 29 real metagenomic datasets and evaluated their compression performance. Reference-based compression achieved an impressive compression ratio of over 20 for human whole-genome data and up to 33.8 for all samples, demonstrating a remarkable 4.5 times improvement than the standard Gzip compression. Our method provides new insights into reference-based metagenomic data compression and has a broad application potential for faster and cheaper data transfer, storage, and analysis.
科研通智能强力驱动
Strongly Powered by AbleSci AI