Bioinformatics methods for detecting and making sense of somatic genomic rearrangements (Masters option available)

Bioinformatics methods for detecting and making sense of somatic genomic rearrangements (Masters option available)

Project details

This project will build on state-of-the-art bioinformatics methods to identify genomic rearrangements, previously created in the lab (Cameron et al, Genome Research 2017, 27:2050). It involves the development of new computational methods, primarily using R, to analyse short read, linked read and long read data. The student will contribute to a suite of methods to identify chromosomal rearrangements and to make sense of cancer genome sequencing data. This will include methods for the refinement, visualisation and classification of genomic rearrangements including rearrangements in repetitive parts of the genome, retrotransposon insertions, and their application to clinical cancer samples. 

Cameron et al, GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly, Genome Research 2017, 27:2050 

About our research group

The Papenfuss Lab is a computational biology and bioinformatics research laboratory that is joint between the Bioinformatics Division at the Walter and Eliza Hall Institute of Medical Research and the Computational Biology Program at the Peter MacCallum Cancer Centre. 

We apply mathematics, statistics and computing to make sense of genomics data from human disease, especially related to the evolution of cancer. 

Our major research interests are: 

1. Cancer evolution, including 

  • Complex genomic rearrangements 
  • Formation and evolution of cancer neochromosomes 
  • Melanoma progression 

2. Bioinformatics methods development, including 

  • Identification and classification of genomic rearrangements 

3. Translational bioinformatics, including 

  • Rare cancers 
  • Bioinformatics tools for clinical cancer genomics 

Researchers:

Professor Tony Papenfuss

Tony Papenfuss
Professor
Tony
Papenfuss
Head, Computational Biology; Laboratory Head
Daniel Cameron
Dr
Daniel
Cameron
Bioinformatics division

Project Type: