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张伟伟——东华理工大学
Accounting for tumor purity improves cancer subtype classification from DNA methylation data
嘉宾介绍
张伟伟，2001-2005就读于郑州大学数学系，2005-2007就读于大连理工大学基础数学专业，2014-2017就读于上海师范大学计算生物学专业，2007-至今工作于东华理工大学理学院。以第一作者身份发表论文两篇，主持省级课题三项，参与国家基金三项。
报告摘要
Tumor sample classification has long been an important task in cancer research. Classifying tumors into different subtypes greatly benefits therapeutic development and facilitates application of precision medicine on patients. In practice, solid tumor tissue samples obtained from clinical settings are always mixtures of cancer and normal cells. Thus, the data obtained from these samples are mixed signals. The “tumor purity”, or the percentage of cancer cells in cancer tissue sample, will bias the clustering results if not properly accounted for. In this paper, we developed a model-based clustering method and an R function which uses DNA methylation microarray data to infer tumor subtypes with the consideration of tumor purity. Simulation studies and the analyses of The Cancer Genome Atlas (TCGA) data demonstrate improved results compared with existing methods.
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