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Long read sequencing for transcriptome characterization --- (how) can we quantify transcripts accurately with long reads
- 来源：
- 学校官网
- 收录时间：
- 2026-07-16 03:09:55
- 时间：
- 2024-07-20 16:00:00
- 地点：
- 长安校区会议中心121会议室
- 报告人：
- KinFai Au
- 学校：
- 西安电子科技大学
- 关键词：
- long-read sequencing, transcriptome, isoform quantification, K-value, miniQuant, RNA-seq, gene isoform, transposable elements
- 简介：
- Long-read sequencing has been widely adopted in transcriptomics research, particularly for identifying novel and complex transcriptomic events. As the cost and throughput of long-read sequencing have been improved, the applications to quantitative transcriptome analysis are emerging. Here I will present the development of the "K-value", which is designed to: (1) quantify the influence of gene isoform structural complexity on expression estimation via data deconvolution; and (2) rigorously demonstrate the advantages of long reads over short reads in isoform quantification through mathematical modeling, simulations, experimental validation, and large-scale public datasets. I also will present the software miniQuant that integrates short reads and long reads in a gene- and data-specific manner to achieve better gene isoform quantification over long reads alone and short reads alone. The proof-of-concept applications include the discoveries of gene isoform switching during stem cell differentiation and unique pattern of zygotic genome activation of transposable elements.
- -/- 1
报告介绍：
Long-read sequencing has been widely adopted in transcriptomics research, particularly for identifying novel and complex transcriptomic events. As the cost and throughput of long-read sequencing have been improved, the applications to quantitative transcriptome analysis are emerging. Here I will present the development of the "K-value", which is designed to: (1) quantify the influence of gene isoform structural complexity on expression estimation via data deconvolution; and (2) rigorously demonstrate the advantages of long reads over short reads in isoform quantification through mathematical modeling, simulations, experimental validation, and large-scale public datasets. I also will present the software miniQuant that integrates short reads and long reads in a gene- and data-specific manner to achieve better gene isoform quantification over long reads alone and short reads alone. The proof-of-concept applications include the discoveries of gene isoform switching during stem cell differentiation and unique pattern of zygotic genome activation of transposable elements.
报告人介绍：
Kin Fai Au（区健辉）教授2004年本科毕业于清华大学，2009年于牛津大学获得博士学位，2009年至2013年在斯坦福大学师从美国科学院院士Wing H. Wong教授从事博士后研究，2013年在爱荷华大学建立实验室直到2018年转至俄亥俄州立大学。在俄亥俄州立大学期间，曾任职生物医学信息学系副系主任（研究）及博士课程主任。2023年加入密歇根大学担任终身正教授。主要从事测序数据（尤其是长读长数据）的统计方法和计算方法（如genome lanauge model)方法开发，近年来在Nature Biotechnology、Nature Methods、Nature Structural & Molecular Biology等期刊发表了多篇关于长读长测序，RNA修饰，基因异构体和转座子的高水平论文。区教授是The Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) Consortium的主要负责人之一，并且担任著名学术期刊Genome Biology和Genome Research的编委。
报告图片：
