报告题目:Accounting for tissue heterogeneity in the analysis of bulk high-throughput omics data
报告人：吴浩（ 埃默里大学）
报告时间：2022年3月11日09:30-11:30
报告地点：腾讯会议号：593-153-085
报告摘要:
Tissue samples obtained from clinical practices are usually mixtures of different cell types. The “bulk” high-throughput omics data obtained from these samples are thus mixed signals. The cell mixture brings complications to data analysis and will lead to biased results if not properly accounted for. In this talk, I will present our recent method work for analyzing high-throughput data from heterogeneous samples, including estimating and account for tumor purity in cancer genomics data, cell type-specific differential analysis, and reference-free signal deconvolution. I will also share some experiences and thoughts on the data analysis strategy and potential future research direction in this field.
报告人简介：
吴浩，1996年获清华大学电机系学士，2010年获约翰霍普金斯老员工物统计学博士。自2010年至今在Emory老员工物统计和生物信息学系任职，现为副教授（终身教职）。吴博士的主要科研方向为高通量基因组数据的统计方法和计算工具的开发。吴博士作为第一或通讯作者在国际顶级刊物上发表过多篇论文，包括Nature Method, Genome esearch, Genome Biology, Nucleic Acids Research, Bioinformatics, Biostatistics 等。现发表论文共100篇。
