应数学学院、数学研究院邀请，上海师范大学郑小琪教授将于近日在我院作关于生物信息学方面的学术报告，欢迎感兴趣的师生参加！

报告题目：Detection of differentially methylated CpG sites between tumor samples with uneven tumor purities

报告摘要：Inference of differentially methylated CpG sites between two groups of tumor samples with different geno- or pheno-types is a critical step to uncover the epigenetic mechanism of tumorigenesis, and identify biomarkers for cancer subtyping. However, as a major source of confounding factor, uneven distributions of tumor purity between two groups of tumor samples will lead to biased discovery of differentially methylated sites if not properly accounted for. We here propose InfiniumDM, a generalized least square model to adjust tumor purity effect for differential methylation analysis. Our method is applicable to a variety of experimental designs including with or without normal controls, different sources of normal tissue contaminations. We com-pared our method with conventional methods including minfi, limma, and limma corrected by tumor purity using simulated data sets. Our method shows significantly better performance at different levels of differential methylation thresholds, sample sizes, mean purity deviations and so on. We also applied the proposed method to breast cancer samples from TCGA database to further evaluate its performance. Overall, both simulation and real data analyses demonstrate favorable performance over existing methods serving similar purpose.

报告时间：2020年10月16日14:00 -14:40

报告地点：明德楼201

报告人简介：郑小琪，上海师范大学数学系教授，博士生导师。主要从事生物信息学领域的研究，在基于DNA甲基化 (包括亚硫酸盐测序和450k芯片数据) 的肿瘤纯度估计、校正肿瘤纯度的差异甲基化分析及肿瘤样本聚类等问题上取得了一系列研究成果。2008年至今累计发表SCI论文60余篇，包括第一或通讯作者论文40余篇，累积影响因子超过300。以负责人承担国家自然科学基金面上项目2项，青年项目1项，以项目骨干承担国家重点研发计划专项1项。现任中国计算机学会生物信息专业委员会委员，中国抗癌学会肿瘤标志物专业委员会肿瘤测序及大数据分析协作组常务委员，中国现场统计研究会大数据统计分会理事等。