Data Science Tools to Increase Insight in Genomics Data

项目摘要 高通量分子技术越来越多地用于生物医学和基础科学。新技术- 目前正在快速开发新的诊断方法和检测手段，并有可能对细胞过程进行研究 以前所未有的分辨率和吞吐量。由于测量技术的发展， 越来越多的分子生物学研究者需要统计学方法来分析复杂的数据。我们有一个 发展这种方法的记录和R35机制将为我们提供灵活性， 新的分子方法正在开发中。 我们将专注于（1）测量实验之间共享的分子组分，（2）不同的方法- 使用单细胞RNA-seq的定向和细胞周期测量，（3）检测作用于分子的选择， 特征，如DNA甲基化、组蛋白修饰和转录因子结合，以及（4）表观基因组学 包括纳米孔测序的测定。

Project summary High-throughput molecular technologies are increasingly being used in biomedical and basic science. New tech- nologies and assays are being developed at a rapid pace, and have the potential to interrogate cellular processes at an unprecedented resolution and throughput. As a result of the developments in measurement technologies, more investigators in molecular biology are in need of statistical methods to analyze complex data. We have a track record of developing such methods and the R35 mechanism will provide us with the flexibility to pivot our effort as new molecular approaches are being developed. We will focus on methods for (1) measuring the shared molecular component between experiments, (2) differ- entiation and cell cycle measurements using single-cell RNA-seq, (3) detecting selection acting on molecular features such as DNA methylation, histone modifications and transcription factor binding, and (4) epigenomics assays including nanopore sequencing.