The Cancer Genomics Linkage Application will enable the integration and re-use of the cancer genomics data available from public repositories such as the International Cancer Genome Consortium (ICGC). This will be accomplished through the capability being developed by the “Early Activity” of the Genomics Virtual Laboratory (GVL-EA). It will enable researchers, such as Professors Andrew Biankin, John Mattick (Garvan Institute for Medical Research) or Sean Grimmond (Queensland Centre for Medical Genomics), to access genomic datasets of international importance and to integrate them with their own clinical and genomic datasets in order to explore, discover and validate key genomic abnormality that cause cancer. The product will further provide the mechanism for such researchers to publish and to make available their analysis for re-use by the community.
The product aims to provide the ability for biologists and clinicians to easily integrate their own research data with datasets from multiple data sources. The Integration of the datasets into a common location and enabling access and mining using best practice workflow tools will enable the Australian cancer researchers to accelerate their discovery processes and to be internationally competitive. Although this project will have a particular focus on pancreatic cancer research as carried out by the Australian Pancreatic Cancer Genome Initiative (APGI), the application can also support the wider cancer research community.
Download the application from here.
The Cancer Genomics Linkage Application will
enable the in-depth interrogation of cancer genomic datasets and allow the comparison to other genomic datasets by providing research Biologists and Clinicians with direct access to them through the Genomics Virtual Lab-Early Activity (GVL-EA).
This application will focus on the research being carried out by the Australian Pancreatic Cancer Genome Initiative (APGI) and aims to:
- Provide local access to a collection of selected public data sources e.g. the ICGC open access data, the 1000 Genomes (pilot 2 trios alignment)
- Enable researchers to transform and integrate these datasets along with user uploaded data via the Galaxy workflow system as part of the GVL-EA
- Provide tool wrappers for somatic mutation analysis
- Provide exemplar workflows using Galaxy that demonstrates how to integrate the tools and datasets
- Enable APGI researchers to share their workflows, making them available for re-use and to obtain a persistent identifier for publication
- Enable automatic generation of compliant RIF-CS for publication to Research Data Australia
- Assists researchers in accelerating their discovery process, reducing the time to publication
- Make these integration and analysis workflows available through the GVL-EA to the APGI researchers and the cancer research community more broadly
