上海财经大学 > 科学研究 > 学术交流 > 学术报告
  • 统计与管理学院2016年学术报告第37

     

    【主  题】Concordant integrative analysis of multiple two-sample genome-wide

    expression data sets

    【报告人】 Yinglei Lai, Ph.D.

    The George Washington University

    【时  间】 2016年10月09日(星期日)15:30-16:30

    【地  点】 上海财经大学统计与管理学院大楼1208室

    【摘  要】The development of microarray and sequencing technologies enables biomedical researchers to collect and analyze large-scale molecular data. We will introduce our recent studies on the concordant integrative approach to the analysis of multiple related two-sample genome-wide expression data sets.  A mixture model is developed and yields concordant integrative differential expression analysis as well as concordant integrative gene set enrichment analysis. As the number of data sets increases, it is necessary to reduce the number of parameters in the model.  Motivated by the well-known generalized estimating equations (GEEs) for longitudinal data analysis, we focus on the concordant components and assume some special structures for the proportions of non-concordant components in the mixture model. The advantage and usefulness of this approach are illustrated on experimental data.

    【邀请人】 黄涛