学术沙龙 | PBLR: an accurate single-cell RNA-seq data imputation tool

文:教师发展中心 / 来源:党委教师工作部、人力资源部 / 2018-09-13 / 点击量:1114

  本次“学术沙龙”教师发展中心邀请中国科学院数学与系统科学研究院张世华研究员,与我校师生分享他在单细胞数据分析方面的研究及进展。具体安排如下,欢迎感兴趣的师生参加:

  一、主题:PBLR: an accurate single-cell RNA-seq data imputation tool

  二、时间:2018年9月14日(周五)上午10:30-11:30

  三、地点:清水河校区 宾诺咖啡

  四、主讲人:中国科学院数学与系统科学研究院 张世华 研究员

  五、主持人:生命科学与技术学院 林昊 教授

  六、 交流内容:

  Single-cell RNA sequencing (scRNA-seq) provides a powerful tool to determine precise expression patterns of tens of thousands of individual cells, decipher cell heterogeneity and cell subpopulations and so on. However, scRNA-seq data analysis remains challenging due to various technical noise, e.g., the presence of dropout events (i.e., excess zero counts). Taking account of cell heterogeneity and structural effect of expression on dropout rate, we propose a novel method named PBLR to accurately impute the dropouts of scRNA-seq data. PBLR is an effective tool to recover dropout events on both simulated and real scRNA-seq datasets, and can dramatically improve low-dimensional representation and recovery of gene-gene relationship masked by dropout events compared to several state-of-the-art methods. Moreover, PBLR also detect accurate and robust cell subpopulations automatically, shedding light its flexibility and generality for scRNA-seq data analysis.

  七、主讲人简介:

  张世华,现任中国科学院数学与系统科学研究院研究员、中国科学院随机复杂结构与数据科学重点实验室副主任、中国科学院大学岗位教授。主要从事运筹学、机器学习、模式识别与生物信息学交叉研究。目前担任BMC Genomics,Frontiers in Genetics,Scientific Reports等5个SCI杂志的编委以及IEEE/ACM TCBB的客座编委。曾荣获中国青年科技奖、国家自然科学基金“优秀青年”基金、中组部“万人计划”青年拔尖人才。

  八、主办单位:人力资源部教师发展中心

    承办单位:生命科学与技术学院

 

                    人力资源部教师发展中心

                       2018年9月13日


编辑:王晓刚  / 审核:李果  / 发布者:陈伟