题目：Differential Gene Expression Analysis Using Coexpression and RNA-Seq Data
时间：2013年12月3日 (周二) 13:30
地点：信息工程学院244
演讲人：Tao Jiang (姜涛) 美国加州大学河滨分校计算机科学系教授
Abstract: As a fundamental tool for discovering genes involved in a disease or biological process, differential gene expression analysis plays an important role in genomics research. High throughput sequencing technologies such as RNA-Seq are increasingly being used for differential gene expression analysis which was dominated by the microarray technology in the past decade. However, inferring differential gene expression based on the observed difference of RNA-Seq read counts has unique challenges that were not present in microarray-based analysis. The differential expression estimation may be biased against low read count values such that the differential expression of genes with high read counts is more easily detected. The estimation bias may further propagate in downstream analyses at the systems biology level if it is not corrected. In this work, we propose a new efficient algorithm for detecting differentially expressed genes based on a markov random field (MRF) model, called MRFSeq, that uses additional coexpression data to enhance the prediction power. Our main technical contribution is a careful construction of the clique potential functions in the MRF so its maximum a posteriori (MAP) estimation can be reduced to the well-known maximum flow problem and thus solved in polynomial time. Our extensive experiments on simulated and real RNA-Seq datasets demonstrate that MRFSeq is more accurate and less biased against genes with low read counts than the existing methods based on RNA-Seq data alone. For example, on the well-studied MAQC dataset, MRFSeq improved the sensitivity from 11.6% to 38.8% for genes with low read counts.
演讲人简介：Tao Jiang, 男，美国加州大学河滨分校计算机科学系教授。1984年7月毕业于中国科学技术大学计算机科学系，获本科学位。1988年11月毕业于美国明尼苏达大学，获博士学位。1989年1月至2001年7月在加拿大麦克马斯特大学 (McMaster University)先后担任助理教授、副教授及教授职位，1999年至今任美国加州大学河滨分校教授。研究兴趣包括组合算法、计算生物学、生物信息学、信息检索等。从事计算机算法和生物信息学研究多年，在计算机科学及生物信息领域期刊及会议上共发布学术论文240余篇，学术专著一部。担任ACM Fellow（此荣誉由Association for Computing Machinery，即计算机协会颁给全世界计算机相关领域有杰出贡献之学者），以及American Association for the Advancement of Science (AAAS) Fellow，美国加州大学河滨分校讲席教授（Presidential Chair Professor， 2007-2010）职位。