多实验平台下基因及异构体表达分析综述  

A Review of Gene and Isoform Expression Analysis across Multiple Experimental Platforms

作　　者：王凯莉[1] 张礼[2] 刘学军[1] 

机构地区：[1]南京航空航天大学计算机科学与技术学院,南京211106 [2]南京林业大学信息科学技术学院,南京210037

出　　处：《中国生物医学工程学报》2017年第2期211-218,共8页Chinese Journal of Biomedical Engineering

基　　金：国家自然科学基金(61170152)

摘　　要：转录组学研究近几年成为生命科学和医学领域的研究热点,基因表达水平测量则是转录组学研究的基础。差异基因表达分析对于了解基因功能具有重要作用,而差异异构体表达分析则能够反映选择性剪切变化的情况。当前大规模测量基因表达水平的实验平台主要包括基因芯片,以及基于高通量测序技术的RNA-Seq。首先介绍广泛使用的Affymetrix传统3'基因芯片、外显子芯片、较新的全转录组芯片,以及基于RNA-Seq技术的Illumina平台4个主流实验平台的技术原理;其次从基因表达水平计算和差异表达分析两方面介绍每个平台下一些主流数据分析方法和该研究设计的方法,分析每个平台下各数据分析方法的优劣,并进一步展示在标准数据集上一些代表性方法的对比结果。Transcriptomics study has become a hot topic in life science and medical research in recent years. From the expression point of view, the foundation of transcriptomics study is the measurement of gene expression levels. Differential expression （DE） analysis of genes is very important for understanding the function of genes. DE analysis of isoforms is a feasible method to reflect the change of alternative splicing. Currently, there are mainly two large-scale experimental platforms for measuring gene expression levels, including microarray and high-throughput sequencing technology, RNA-Seq. At the beginning of this paper, we introduced the technical principles of the four mainstream experimental platforms： Affymetrix＇s traditional 3＇ GeneChip, Exon array, Human Transcriptome Array 2.0 and Illumina platform based on RNA-Seq. We then reviewed the mainstream analysis methods and our methods on each platform for the calculation of gene expression levels and DE analysis. We also showed the comparison results of expression measurement and DE analysis across various platforms under a well-defined benchmark data set.

关 键 词：传统3’基因芯片 外显子芯片 HTA2.0芯片 RNA-SEQ 基因表达分析 

分 类 号：R318[医药卫生—生物医学工程]