Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computing

项目总结

Project Summary Mass spectrometry (MS) based proteomics is currently the most widely used technology for the analysis of complex protein mixtures. It has the ability to detect and quantify the abundance of thousands of proteins and their variants, post-translational modifications, protein:protein and protein:drug interactions per experiment. The Trans-Proteomic Pipeline (TPP) is a free and open-source suite of software tools for the analysis of mass spectrometry (MS) proteomics data that has been widely used by the community for over 15 years. Our ongoing award for the maintenance and development of the TPP has four aims in which we 1) enhance the TPP to process datasets from emerging workflows, 2) add statistical analysis and visualization capabilities for large datasets, 3) respond to the needs of the community with functional and usability enhancements, and 4) expand our user base with improved training and on-line learning. Great progress has been made on these aims during the project period. However, current development for one of the main tools that we are currently focusing on has been severely hindered by aging computational servers purchased in 2012 and inadequate development of computing resources. We propose to address this problem via the purchase and deployment of a pair of high- memory, high-core count, fast-disk compute servers, substantially accelerating our development cycle so that the algorithm development can be completed more rapidly, and the completed algorithm can be further rapidly optimized to run with more modest hardware requirements routinely. Deployment of these machines will streamline our software development by providing rapid feedback on software changes and further developments and their impact on search speed and enable us to provide tools to our users more rapidly, accelerating the progress of many other research programs that use the TPP for data processing.