HPC Enabling of R Application Software for High Throughput Post Genomic Data. (360G-Wellcome-086696_Z_08_Z)

Existing methods for allowing the statistical programming language R to use High Performance Computing (HPC) resources require specialist knowledge of parallel programming in order to handle common analytical tasks such as correlation between all variables in a dataset. The technology proposed here is a user-friendly software suite to enable biological researchers to more easily exploit supercomputers or even a cluster of personal computers to run computationally expensive R scripts. This will e nable researchers to use R/Bioconductor to perform extensive statistical and combinatorial analyses of high-dimensional biological data otherwise considered intractable. This intractability is in part due to the necessity for in-depth knowledge of HPC programming techniques which are rare to non-existent amongst biological researchers. This software will produce a step change in both the complexity and size of analysis that can be performed in a reasonable time as well as significantly reduce the execution time for existing analyses on current bioinformatics computational infrastructures. Development will proceed in tandem with research that will use the software to exploit HPC to conduct new combined analyses of previously studied datasets. This will ensure the resulting application contains the functionality immediately relevant to biological research groups and importantly, is easily usable by such researchers.