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MSU CSE Colloquium Series 2014-2015: Tao Jiang Title:  Differential Gene Expression Analysis Using Coexpression and RNA-Seq Data

Dr. Tao Jiang
Department of Computer Science and Engineering
University of California, Riverside
and Tsinghua University, Beijing

Time: Friday, Nov 7th, 2014, 11am
Location: EB 3105


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.


Tao Jiang received B.S. in Computer Science and Technology from the University of Science and Technology of China, Hefei, in July 1984 and Ph.D. in Computer Science from University of Minnesota in Nov. 1988. He was a faculty member at McMaster University, Hamilton, Ontario, Canada during Jan. 1989 - July 2001 and is now Professor of
Computer Science and Engineering at University of California - Riverside (UCR). He is also a member of the UCR Institute for Integrative Genome Biology, a member of the Center for Plant Cell Biology, a principal scientist at Shanghai Center for Bioinformation Technology, and Chair Visiting Professor at Tsinghua University. Tao Jiang's recent research interest includes combinatorial algorithms, computational molecular biology, bioinformatics, and computational aspects of information retrieval. He is a fellow of the Association for Computing Machinery (ACM) and of the American Association for the Advancement of Science (AAAS), and held a Presidential Chair Professor position at UCR during 2007-2010. He has published over 260 papers in computer science and bioinformatics journals and conferences, and won several best paper awards. More information about his work can be found at


Dr. Yanni Sun