Molecular diagnostic software

Peter Mac has designed a Molecular Genomics Diagnostic Reporting Package (PathOS) that uses cutting edge bioinformatics tools, federation of databases and a clinical information exchange platform to provide the clinician with a comprehensive account of the patient’s genomic landscape, a list of “actionable” mutations (e.g. mutations that can be specifically targeted using so-called designer drugs).

PathOS is a unique, in-house automated software solution that provides clinical decision support tools for understanding genetic mutations. PathOS enables bioinformatics filtering, classification of variants, annotation, curation and clinical reporting all in a ISO15189 accredited framework.

Sequencing is now delivered as turnkey hardware and is rapidly becoming commoditised, but pipelines and curation rely on software and global databases that are still immature. Peter Mac is at the forefront of interpretation via the development of PathOS and associated skills and expertise in bioinformatics.

PathOS integrates a patient’s genetic data and cancer type with global databases to provide clinicians with reports to match patients with optimal treatments. It is also used in clinical trials to improve patient care and evaluate new therapies.

NEXT GENERATION SEQUENCING

PathOS reports on two key parts of next generation sequencing:

  • data quality review – PathOS report on key data quality metrics arising from the sequencing output enabling an accurate review of the test data
  • clinical report – reports on the mutations with actionable treatment outcomes and highlights any applicable clinical trials. Peter Mac’s experts ensure that PathOS data is up-to-date with the latest in clinical treatment and trials

MOLECULAR DIAGNOSTIC SOFTWARE

DATABASE

The PathOS data base size is 8.8m variants with 3,900 curated variants from 119,000 sequenced samples. Peter Mac has in-house capabilities to review and curate any unknown variants to decipher whether they are pathogenic and have actionable treatment outcomes. A cloud instance has been set up here for demonstration. Access can be arranged through the project contact.

Peter Mac is interested in collaborating to expand and develop PathOS.

PARTNERS

The development of PathOS is also targeted at institutions beyond Peter Mac that perform high throughput clinical sequencing. To make the capabilities of PathOS available to other groups and extend the features of PathOS, a number of collaborations have begun with the Children’s Cancer Institute, the Murdoch Children Research Institute, the Garvan Institute of Medical Research, the Melbourne Genomics Health Alliance and the Australian Genomics Health Alliance.

THE CORE TEAM

  • Dr Kenneth Doig – MPhil – Data Scientist – Research interests in clinical translation, clinical informatics automation, bioinformatic algorithms, cancer genetics and microbial genetics.
  • Dr Thomas Conway – Bioinformatics Researcher & Bioinformatician – Research interests in bringing together insights from theoretical computer science, statistics, and biology to unlock the potential of high throughput sequencing for for both research, and clinical practice. Experience in software engineering, advanced data structures, de novo assembly, k-mer methods, cancer genomics, and bacterial genomics.
  • Dr Christopher Love – Bioinformatician – PhD (Bioinformatics), MSc. (Bioinformatics) , BSc(Hons) Biology. Research interests include functional genomics, cancer genetics and clinical pipeline development.
  • Mr Andrei Seleznev – BCompSc(SE), MSc (Bioinformatics) – Bioinformatician – Research interests in bioinformatics software development, data architecture, high-performance computing, NGS pipeline analysis, genetics and cancer genomics.
  • Mr David Ma – BEng (Bioinformatics) – Bioinformatician – Research interests in user experience, data visualisation and bioinformatics.

CONTACT DETAILS

  • Dr Kenneth Doig, Data Scientist, Molecular Pathology​​​​​​
  • Email: [email protected]

KEY PUBLICATIONS

  1. Doig, K., Papenfuss, A. T. & Fox, SB. Clinical cancer genomic analysis: data engineering required. The Lancet. Oncology 16, 1015-1017, doi:10.1016/S1470-2045(15)00195-3 (2015)
  2. Doig KD, Ellul J, Fellowes A, Thompson ER, Ryland G, Blombery P, Papenfuss AT, Fox SB: Canary: an atomic pipeline for clinical amplicon assays. BMC Bioinformatics 2017, 18:555.
  3. Doig, K. D. et al. PathOS: a decision support system for reporting high throughput sequencing of cancers in clinical diagnostic laboratories. Genome medicine 9, 38, doi:10.1186/s13073-017-0427-z (2017)
  4. Succinct data structures for assembling large genomes, TC Conway, AJ Bromage, Bioinformatics 27 (4), 479-486​​​​
  5. Short read sequence typing (SRST): multi-locus sequence types from short reads, M Inouye, TC Conway, J Zobel, KE Holt, BMC genomics 13 (1), 338
  6. Epigenetic regulation of cell type–specific expression patterns in the human mammary epithelium, R Maruyama, S Choudhury, A Kowalczyk, M Bessarabova, ..., PLoS Genet 7 (4), e1001369
  7. Xenome—a tool for classifying reads from xenograft samples, T Conway, J Wazny, A Bromage, M Tymms, D Sooraj, ED Williams, ..., Bioinformatics 28 (12), i172-i178

NEWS

Community generosity powers next generation cancer genomics at Peter Mac ​​​​