About the research topic
Background Many SARS-CoV-2 patients in intensive care were presented with hypercoagulation causing fatal thrombosis. Analysis of SARS-CoV-2 infected lungs revealed post-infection immunological responses. Further research on the interactions between SARS-CoV-2 and its receptors has led to novel prevention and treatment strategies. To accelerate such research on the pathogenesis in other infectious diseases, a streamlined data management and analysis platform is needed.
Galaxy is an open-source bioinformatics workflow platform, supported by ELIXIR-NL, which has been used for automated SARS-CoV-2 genome surveillance (https://www.infectious-diseases-toolkit.org/showcase/).
XNAT is an open-source imaging data management platform, supported by BIGR as Euro-BioImaging Population Imaging Flagship node. It is optimized for radiological imaging modalities (e.g. MRI, CT), but does not yet support Digital Pathomics (DP) and Spatial Transcriptomics (ST) data types that are used in pathogenesis research.
Aim and objectives To develop a data management and analysis platform, called PATH2XNAT, built on top of XNAT and Galaxy, to accelerate research on the pathogenesis of infectious diseases. To this end, the PATH2XNAT project has three objectives:
- To extend XNAT for use with DP and ST data.
- To connect XNAT to Galaxy.
- To showcase the utility of PATH2XNAT in a study on SARS-CoV-2 pathogenesis.
Besides the mentioned BIGR members, this project involves close collaboration with the PHANTOM group of the Department of Pathology.
Funding This project funded by the ISIDORe JRA PROGRAMME.