Data Science Tools to Increase Insight in Genomics Data

Johns Hopkins University, Baltimore MD

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Abstract

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.