Section: Application Domains

Joint genetic and neuroimaging data analysis on Azure clouds

Joint acquisition of neuroimaging and genetic data on large cohorts of subjects is a new approach used to assess and understand the variability that exists between individuals. It has remained poorly understood so far. Both neuroimaging- and genetic-domain observations include a huge amount of variables (of the order of millions). Performing rigorous statistical analyses on such amounts of data is a major computational challenge that cannot be addressed with conventional computational techniques only. On the one hand, sophisticated regression techniques need to be used in order to perform significant analysis on these large datasets; on the other hand, the cost entailed by parameter optimization and statistical validation procedures (e.g. permutation tests) is very high.

The A-Brain (AzureBrain) Project was carried out within the Microsoft Research-Inria Joint Research Center. It was co-led by the KerData (Rennes) and Parietal (Saclay) Inria teams. They jointly address this computational problem using cloud related techniques on the Microsoft Azure cloud infrastructure. The two teams bring together their complementary expertise: KerData in the area of scalable cloud data management, and Parietal in the field of neuroimaging and genetics data analysis. This project is a typical multi-disciplinary Data Science project which serves as background for several on-going research activities.

In particular, KerData brings its expertise in designing solutions for optimized data storage and management for the Map-Reduce programming model. This model has recently arisen as a very effective approach to develop high-performance applications over very large distributed systems such as grids and now clouds. The computations involved in the statistical analysis designed by the Parietal team fit particularly well with this model.