Long read sequence analysis of cancer

Cancer causes 1 in 8 deaths worldwide. We use whole genome sequencing to study a variety of tumor types including breast cancer, mesothelioma, melanoma and lung cancer. Genomic data is paving the way for precision medicine, whereby treatment is guided by the mutation profile of the patients tumour. Our group uses bioinformatic approaches to analyse large genome and RNA sequence datasets generated from tumor tissues ad matched germline samples. The data has helped to redefine the genomic, transcriptomic and methylation landscape of cancers and allow the identification of driver genes. To date most cancer genome studies have used short read sequencing to study cancer genomes which has limitations, however new long read technology is now available which can sequence long stretches of DNA and RNA and has the potential to change cancer genomics.
This project will use a combination of short read and long read whole genome and RNA sequence data to characterize coding and non-coding mutations in a variety of cancer types. The project will look to i) develop processes to analyse and visualize the long read data, ii) develop process to annotate and curate somatic mutations. This project will provide novel insights into tumour development and provide a basis for the use of long read sequence data in precision medicine.
The project is a dry lab project (computational) and will suit an individual with experience in bioinformatics. The successful applicant will be part of a team of bioinformaticians and will work closely with postdoctoral researchers in the lab.

For more information on this research group: https://www.qimrberghofer.edu.au/lab/medical-genomics/