Speakers include Dr Denis Bauer, Head Cloud Computing Bioinformatics, CSIRO, Dr Alejandro Metke who leads the Health Data Interoperability Team at the Australian e-Health Research Centre, and Garvan Institute Head of Data Science Sarah Kummerfeld.
Cloud-based genomics: where to from here?
Denis Bauer CSIRO
The ever-growing volumes of genomic data along with the increased requirements on data security and privacy have prompted many genomics initiatives to re-think their IT infrastructure. Public cloud providers resolve scalability issues and alleviate data compliance pressure by providing encryption, obfuscation, and layered infrastructure out of the box. However, these benefits come at the cost of autonomy and the added complexity of having to integrate data sources and services across multiple external providers.
This talk will outline how CSIRO has developed genomic analysis and data exchange services using cloud-computing across several human health disciplines, such as disease gene detection, advanced therapeutics, and infectious disease tracking. It highlights the successes in achieving unprecedented scale and speed as well as open new commercialisation avenues through cloud-based marketplace deployment. It also outlines the design consideration for a cloud-first mindset and discusses some of the limitation current cloud-platforms needs to overcome to fully cater for the demands of digital health applications.
Interoperable clinical information: A case study with the Australian Genomics Mitochondrial Flagship
Dr Alejandro Metke Australian e-Health Research Centre
Patient clinical information, including phenotypic data, is a fundamental aspect in genomics research. Capturing, storing and sharing this type of data poses a very different set of challenges compared to genomic data. This presentation gives an overview of these challenges and introduces new cloud-based tools that can be used to overcome them. A case study with the Australian Genomics Mitochondrial Flagship is presented to highlight the benefits of making clinical data interoperable through the use of standards.
Massively scalable genomic analysis
Sarah Kummerfeld Garvan Institute
The mainstreaming of whole genome sequencing for research and clinical applications has led to a rapid increase in the rate of data generation. This is driving demand for scalable systems to process and analyse large WGS datasets. We set out to investigate the scalability and features of a fully cloud-based genomic processing and analysis workflow, leveraging the Google Cloud Platform (GCP) for computing, the Terra platform for workflow management, the Hail platform for joint variant-calling and analysis, and seqr for analysis of genomic data. We demonstrated the capabilities of these systems on the largest genomics data set ever examined in Australia, reprocessing and variant-calling 14,000 whole genomes simultaneously from raw fastq files through to gVCFs over a two-week period.
Register here or for more information contact Carla Carroll.