Time: 10:00-11:00am, July. 9th, 2019, Tuesday
Venue: RoomA1514, Science Building, North Zhongshan Road Campus
Spreker: Associate Professor Hao Wu, Emory University
Abstract: The modern high-throughput data present unprecedented opportunities for biological and clinical research, as well as tremendous challenges for data analysis. A routine task in high-throughput data analysis is to detect features behaving differently under distinct biological or clinical conditions. These analyses, including differential expression and differential methylation, seems can be done by simple statistical test. However, some special characteristics in the high-throughput data, including small sample size, large test space, and distribution of the data, make the problem more difficult than it appears. In this talk, I will discuss the challenges and solutions for differential expression analysis for data from gene expression microarray and RNA sequencing, as well as differential methylation analysis for data from bisulfite sequencing.
Speaker’s Bio：Hao Wu 副教授，本科毕业于清华大学，博士毕业于美国约翰霍普金斯大学。2010—2016年为美国埃默里大学助理教授，2016至今为美国埃默里大学副教授。曾在顶级期刊Cell, Nature子刊Nature genetics, Nature Neuroscienc,生物信息学顶级期刊 Bioinformatics等杂志发表学术论文80余篇。
