宏基因组大数据分析的质量控制流程规范  

Quality control of big data analysis for metagenomics

作　　者：郑广勇[1] 杨桢 曹瑞芳 刘婉[2] 李亦学[1,2] 张国庆[1,2] ZHENG Guangyong;YANG Zhen;CAO Ruifang;LIU Wan;LI Yixue;ZHANG Guoqing(Bio-Med Big Data Center, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences Shanghai 200031, China;Shanghai Center for Bioinformation Technology, Shanghai 201203, China)

机构地区：[1]中国科学院上海生命科学研究院生物医学大数据中心,上海200031 [2]上海生物信息技术研究中心,上海201203

出　　处：《大数据》2018年第3期1-12,共12页Big Data Research

基　　金：国家重点研发计划基金资助项目(No.SQ2017 Y FSF120182,No.2017 Y FC09 07505,No.2016Y FC09 019 04,No.2016YFC0901604);中国科学院微生物组计划基金资助项目(No.KFZD-SW-219-5)~~

摘　　要：宏基因组数据具有数据量大、复杂度高的特点,从数据类型来看,其涵盖了元数据和测序数据。为了保证宏基因组数据后续功能分析的有效性和正确性,需要对这些元数据和测序数据进行严格的质量控制检测。详细描述了宏基因组数据的质量控制流程,包括元数据和测序数据的信息检查、低质量片段的过滤等过程,从而为宏基因组数据分析提供了预处理的规范,这将为微生物组大数据分析提供坚实的基础。Metagenomic data has the characteristics of high volume and complexity. As for data type of metagenomics, it covers metadata and sequencing data. Before performing in-depth functional analysis of metagenomic data, strict quality control for these metadata and sequencing data are needed, so as to ensure the validity and correctness of subsequent data analysis. The quality control process of metagenomic data was described in detail, which included information checking of metadata and sequencing data, filtering of low quality fragments, and so on. A pre-processing specification for metagenomic data analysis was presented, and a solid foundation for big data analysis of microbiome was provided.

关 键 词：微生物组 宏基因组 大数据分析 二代测序 质量控制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]