Lab focus: Statistical bioinformatics and single cells

Each cell in the body contains the same genetic code, and the interpretation of that code gives rise to a diverse array of cell types and structures. Gene expression is the fundamental first step in the interpretation of the cell’s genetic code. Precise programs of gene expression and regulation are essential for normal development and are disrupted in disease.

New technologies enables us to measure gene expression and other genetic information in individual cells, leading to exciting discoveries. The focus of our research is developing novel bioinformatics methods to better analyse the massive datasets arising from single cell and related technologies.

Research interest

The Phipson laboratory works on both novel bioinformatics methods development as well as collaborative analysis projects with scientists within and external to the Institute. We use sophisticated statistical modelling to reveal insights into normal development and disease.

A major research focus of the Phipson laboratory is on developing new bioinformatics methods for data generated from single cell technologies. We also work on genomic data generated from other high-throughput technologies including RNA-seq and DNA methylation. Our novel bioinformatics methods are implemented as publicly available open source software through the Bioconductor project.

Current research areas of interest include:

• Developing statistical methods for designed single cell experiments with biological replication
• Advancing DNA methylation analysis for current and emerging technologies