报告人:周彦副教授
深圳大学
题目: A statistical normalization method and differential expression analysis for RNA-seq data between different species
时间:2018年12月29日上午09:00
地点:海韵实验楼108
摘要: Background: High-throughput techniques bring novel tools but also statistical challenges to genomic research. Identifying genes with differential expression between different species is an effective way to discover evolutionarily conserved transcriptional responses. To remove systematic variation between different species for a fair comparison, the normalization procedure serves as a crucial pre-processing step that adjusts for the varying sample sequencing depths and other confounding technical effects. Results: In this paper, we propose a scale based normalization (SCBN) method by taking into account the available knowledge of conserved orthologous genes and hypothesis testing framework. Considering the different gene lengths and unmapped genes between different species, we formulate the problem from the perspective of hypothesis testing and search for the optimal scaling factor that minimizes the deviation between the empirical and nominal type I errors. Conclusions: Simulation studies show that the proposed method performs significantly better than the existing competitor in a wide range of settings. An RNA-seq dataset of different species is also analyzed and it coincides with the conclusion that the proposed method outperforms the existing method. For practical applications, we have also developed an R package named \SCBN" and the software is available at http://www.bioconductor.org/packages/devel/bioc/html/SCBN.html.
报告人简介:周彦,深圳大学数学与统计学院副教授,硕士研究生导师。 2013年本硕博毕业于东北师范大学数学与统计学院,随后在美国伊利诺伊大学香槟分校从事博士后工作,2015年进入深圳大学工作。主要从事统计学,生物信息学,生物统计,医学统计,数据科学等统计方面的研究。获得“深圳市海外高层次人才” 和“南山区领航人才” 荣誉称号。获得深圳市孔雀计划奖励C类。主持国家两项,国家统计局项目一项,广东省项目一项,深圳市高端人才项目等。近年来以第一作者身份在Genome Research(影响因子:14.38),bioinformatics(影响因子:7.38),BMC Genomics(影响因子:3.86)等国际期刊上发表高水平文章二十余篇。单篇最高引用次数近70次。协会兼职广东省现场统计协会副秘书长,理事;中国工业统计协会理事;中国环境资源统计会议理事。担任Biometrics,BMC bioinformatics等杂志审稿人。
联系人:胡杰助理教授
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