Advancing long-read data analysis of the transcriptome

• PhD and Graduate Research Masters
• Masters by Coursework
• Honours

Modern biology seeks to understand the genome’s circuitry by studying its functional read-out, the transcriptome. Advances in long-read sequencing can paint a more comprehensive picture of transcriptomes by revealing the full length of individual RNA molecules. Splicing and variants can be phased, and repetitive sequence resolved. Moreover, Nanopore long-read sequencing technology offers the potential for rapid, ultra-portable and real-time targeted sequencing. However, long-read transcriptome data analysis remains challenging. The base calling accuracy is low, and new methods are needed to take full advantage of phased events.

This project will build new computational methods to analyse this complex data, with a focus on resolving novel splicing and mutations in cancer and long reads combined with single-cell sequencing data.

Our bioinformatics group is based jointly in the Blood Cells and Blood Cancer Division and the Bioinformatics Division at WEHI. It comprises scientists and students from diverse backgrounds, such as wet lab biology, computer science, mathematics and physics. We build new open source computational methods and approaches to mine omic data, and have an interest in transcriptomics sequencing, long reads, and analysing data without bias from a reference genome or its annotation. We are also involved in collaborative projects to understand cancer initiation, evolution and treatment response through changes to RNA.