数学与统计学院学术报告[2020] 017号

(高水平大学建设系列报告370号)

报告题目: Imputation of single cell RNA-seq dropouts and copy number variation detection in bacterial genomes

报告人： 席瑞斌 教授（北京大学）

报告时间：6月7日10:30-11:30

报告地点：腾讯会议  会议号781 734 092　　　　　　　　　　　　　　　　　　　　　　

报告内容：

Recent breakthrough of sequencing technologies brings about many challenges to statistical analysis. In this talk, I will be talking about two topics about statistical analysis of sequencing data.

In the first part, I will talk about imputation of single cell RNA-seq (scRNA-seq) dropout. scRNA-seq often fails to capture expressed genes, leading to the prominent dropout problem. These dropouts cause many problems in down-stream analysis, such as significant increase of noises, power loss in differential expression analysis and obscuring of gene-to-gene or cell-to-cell relationship. Imputation of these dropout values can be beneficial in scRNA-seq data analysis. I will discuss a method called scRMD based on robust matrix decomposition for dropout imputation of scRNA-seq.

In the second part, I will talk about copy number variation (CNV) detection in bacterial genomes. CNV, consisting of gains or losses of DNA segments, is an important class of genomic variations. The major strategy for detecting CNVs is based on the read depth. We found that in bacterial genomes, read depth is severely influenced by a bias factor which we termed as replication bias. We developed a CNV detection methods called CNV-BAC that can properly normalize such biases and can accurately detect CNVs in bacterial genomes.

报告人简历：

席瑞斌，北京大学数学科学学院、统计科学中心长聘副教授、研究员。 2009年毕业于美国圣路易斯华盛顿大学，同年以助理研究员身份加入哈佛大学医学院从事生物医学信息学方面的研究。2012年9月加入北京大学。席瑞斌的主要研究方向是癌基因组及高通量测序数据计算分析、生物医学大数据的统计分析、大数据、贝叶斯统计、高维统计。席瑞斌近年来有40多篇文章发表于Nature, Nature Genetics, PNAS, Science Translational Medicine, Nature Communications, Journal of Hepatology, Bioinformatics, Biometrika, IEEE Transactions on Knowledge and Data Engineering等顶级或权威学术期刊。席瑞斌先后主持或参与过科技部973项目、国家重点研发项目、基金委重点项目及基金委面上项目等多个科研基金项目。

　　　　　　　　　　　　　　　　　数学与统计学院

2020年6月3日