The following PhD projects are available. Interested students can contact Tony Papenfuss for further information. Students will need to obtain a competitive PhD scholarship through the University of Melbourne. This usually requires the equivalent of an H1 Honours or Masters degree. Projects for Masters are also available.
Machine learning methods for somatic genome rearrangement detection
Supervisors: Tony Papenfuss & Justin Bedo
Structural variants (SVs) are large-scale rearrangements of chromosomes. These are an important type of mutation in cancer and disease. SVs can occur through a variety of biological mechanisms leading to insertions, deletions, duplications, inversions, translocations and complex rearrangements in the genome. These mutations are the cause of some cancers and affect response to therapy.
SV calling is a challenging problem (e.g. Cameron et al, Nat Commun 2019, 10:3240) and many methods are available for identifying SVs, but these often need to be hand tuned to account for different biases and noise properties in different datasets, leading to variable performance on different datasets.
This project will refine machine learning methods to optimise performance for whole genome tumour-normal sequencing data and long read sequencing for each patient. We have demonstrated that this idea works well with single pure samples, such as normal tissue or cell lines. To apply this to cancer will involve handling purity, ploidy, subclonality, and multiple samples. Solutions to the above problems will be developed and evaluated, with opportunities to apply these methods in whole genome sequencing data from patients with rare cancers and other cancer types.
Genomic rearrangement detection using short and long reads
Supervisors: Tony Papenfuss & Justin Bedo
Cancer, along with other genetic diseases, can be caused by genomic rearrangements or structural variants (SVs). This project will build on previous state-of-the-art bioinformatics methods developed in the lab to detect such mutations. It will involve developing algorithms to integrate new long read sequencing technology such as Oxford Nanopore sequencing, as well as Genomics 10X linked reads or Bionano Genomics optical maps, into SV calling.
This project would suit a student with a background in computer science, mathematics or statistics and an interest in algorithm development. You will have the opportunity to be involved in major national and international cancer genomics projects.
Cameron et al, Genome Research 2017, 27:2050
Cameron et al Nature Commun 2019, 10:3240
Cameron et al, Genome Biology 2021, 22:202
Characterisation of extreme genomic instability in cancer
Supervisor: Tony Papenfuss
Giant neochromosomes are complex mutations found in some cancers that lead to high level amplifications as well as deletions. We have previously investigated giant neochromosomes in cancer using sequencing (Garsed et al, 2014) and optical maps (Chan et al, 2018), revealing the dynamic mutational processes that shape the chromosomal structure in sarcoma.
Other mechanisms can also lead to high levels of amplification and rearrangements: random segregation of extra-chromosomal DNA (ecDNA; smaller circular chromosomes that lack centromeres), recombination of ecDNA and breakage-fusion-bridge.
This project will investigate mechanisms of extreme amplification in our cancer cohorts using mathematical modeling and signature classification approaches (Alexandrov et al, 2020) to understand the mechanisms underpinning these mutational processes.
Relevant publications & resources:
Alexandrov, L.B., Kim, J., Haradhvala, N.J. et al. The repertoire of mutational signatures in human cancer. Nature 578, 94–101 (2020).
Chan, E. K. F., Cameron, D. L., Petersen, D. C., Lyons, R. J., Baldi, B. F., Papenfuss, A. T., … Hayes, V. M. (2018). Optical mapping reveals a higher level of genomic architecture of chained fusions in cancer. Genome Research, 28(5), 726–738.
Cortés-Ciriano, I., Lee, J. J.-K., Xi, R., Jain, D., Jung, Y. L., Yang, L., … PCAWG Consortium. (2020). Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nature Genetics, 52(3), 331–341.
Garsed DW*, Marshall OJ*, Corbin VDA*, Hsu A*, Di Stefano L, Schröder J, Li J, Feng Z-P, Kim BW, Kowarsky M, Lansdell B, Brookwell R, Myklebost O, Meza-Zepeda L, Holloway AJ, Pedeutour F, Choo KHA, Damore MA, Deans AJ, Papenfuss AT**, Thomas DM**, Architecture and Evolution of a Cancer Neochromosome, Cancer Cell 2014 Nov 10;26(5):653-67 (*/** joint authors)
Rosswog, C., Bartenhagen, C., Welte, A. et al. Chromothripsis followed by circular recombination drives oncogene amplification in human cancer. Nat Genet (2021).
Sub-typing cancers using multi-omics data