Dissecting cellular heterogeneity and communication via integration of single-cell genomics data
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：金锁钦（武汉大学）
：2022-09-19 14:30
：腾讯会议APP：579-922-4321（无密码）
报告人：金锁钦（武汉大学）
时 间：9月19日下午14:30
地 点：腾讯会议APP：579-922-4321（无密码）
内容摘要:
Recent advances of single-cell technologies, in particular single-cell RNA and ATAC sequencing, provide an unprecedented opportunity to dissect cellular heterogeneity and communication more comprehensively. To deconvolute heterogeneous single cells from both transcriptomic and epigenomic profiles, we developed a matrix factorization-based method for integrating single cell RNA-seq data and ATAC-seq or DNA methylation data obtained from the same individual cells. We demonstrate its capability of dissecting novel cellular populations from sparse single-cell multiomics data, including subpopulations with subtle transcriptomic differences but strong chromatin accessibility differences. In addition, to quantitatively build and analyze cell-cell communication networks in an easily interpretable way, we developed an integrated method CellChat for systematic inference and quantitative analysis of cell-cell communication by leveraging systems biology and machine learning approaches.
个人简介：
金锁钦，武汉大学数学与统计学院副教授。研究方向是计算生物学、生物信息学和大数据分析，在发展数学的理论与方法应用于解决生物医学前沿科学问题、单细胞等生物医学大数据的数学建模和计算挖掘等方面开展了系列研究。研究成果发表于Nature Communications, Nature Neuroscience, Genome Biology, Cell Reports, SIAM Journal on Applied Mathematics等领域知名期刊上。
联系人：周达
