报告题目：An imputation method for single-cell RNA-seq data

报告人：靳水林 哈尔滨工业大学数学学院 教授

报告时间：2022年11月16日（周三）下午2:00-3:00

腾讯会议：690-950-4009

报告摘要：Single-cell RNA sequencing (scRNA-seq) technologies obtain gene expression at single-cell resolution and provide a tool for exploring cell heterogeneity and cell types. As the low amount of extracted mRNA copies per cell, scRNA-seq data exhibit a large number of dropouts, which hinders the downstream analysis of the scRNA-seq data. We propose a statistical method, SDImpute (Single-cell RNA-seq Dropout Imputation), to implement block imputation for dropout events in scRNA-seq data. SDImpute automatically identifies the dropout events based on the gene expression levels and the variations of gene expression across similar cells and similar genes, and it implements block imputation for dropouts by utilizing gene expression unaffected by dropouts from similar cells. The results of experiments suggest that SDImpute is an effective tool to recover the data and preserve the heterogeneity of gene expression across cells and improves the accuracy of the downstream analysis including clustering, visualization, and differential expression analysis.

报告人简介：靳水林，河北邢台人，哈尔滨工业大学数学学院教授，数学、统计学博士生导师。哈尔滨工业大学青年科学家工作室负责人。主持国家自然科学基金面上项目、青年基金项目、863项目等项目，入选哈工大理学创新培育计划；参与国家“生物安全”重大科技专项课题等。获得黑龙江自然科学一等奖。现担任数学评论(Math Review)评论员，德国数学文摘(Zentralblatt Math)评论员，多个杂志通讯评审，自然科学基金通讯评审，教育部自然科学奖通讯评审，教育部学位论文通讯评审，中国高校创新创业教育研究中心专家等。