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.

Wednesday 13 March 2013

What does the application do? A technical description



Analysis of high-throughput sequencing data requires access to specialised computational infrastructure in terms of hardware, software and data. For example, the computational process for identifying and analysing genetic differences from the sequencing data generated by the International Cancer Genome Consortium (ICGC) involves hundreds of steps and requires many computational tools some of which have multiple versions. Access to genomic datasets of international importance and the ability to integrate them with the researcher's own clinical and genomic datasets are also critical in order to explore, discover and validate key genomic abnormality that cause cancer. Such analyses have been the reserved domain of bioinformaticians, but there is a critical need to put these tools in the hands of research biologists and clinicians.
The project enables the in-depth interrogation of cancer genomic data and allows the comparison to other genomic data by providing research biologists and clinicians with direct access to them through the Genomics Virtual Lab (GVL) of NeCTAR. It addresses the combined challenges faced by these researchers:
  • Integrated access to multiple data sources 
  • Availability of standardised analytical processes 
  • Ability to analyse easily and publish the results more quickly
Please see the post “What does the application do? The bigger picture” to get more background information of the Cancer Genomics Linkage application.


The project is composed of four interrelated components as depicted below in Figure 1:
  1. Data: a set of tools have been developed to manage data from public resources and synchronise them for use from within the GVL environment. 
  2.  Tools:  a set of command line analysis tools commonly used by cancer researchers have be deployed for use from within the GVL environment, so that they can be used without the command line. 
  3. Workflows:  a set of workflows common to cancer research have been developed using the Galaxy workflow system within the GVL environment. These workflows form the engine fundamental to the transformation and integration of multiple tools and datasets to accelerate cancer research. 
  4.  Publication: a mechanism has been developed to automatically extract required information from Galaxy in order to generate a collection description using the RIF-CS standard. A persistent identifier (DOI) can be assigned to workflows.
 
Figure 1: Component Overview

No comments:

Post a Comment