Seattle Quant: A Resource for the Skyline Software Ecosystem

Development on Skyline started in 2008 to fill a critical need for a software tool to enable targeted proteomics experiments. The development of Skyline grew into an entire ecosystem of tools and has since expanded beyond targeted proteomics to support a variety of acquisition methods (e.g. DDA, DIA, PRM, and PASEF) and other molecule types. The Skyline software ecosystem is one of the most widely used software platforms in all of mass spectrometry. The current software and its thriving community create exciting new opportunities for quantitative mass spectrometry. The Skyline project has grown beyond the bounds of a single tool. There are now 17 Skyline external tools that rely on a formalized framework in Skyline, with more in development. Some of these tools have been installed >10,000 times. We have also created the Panorama Knowledgebase and Panorama Public, a platform allowing Skyline users to organize, share, and disseminate processed quantitative proteomics data, as well as tools like AutoQC and Skyline Batch that take advantage of the Skyline command-line interface for automated bulk processing. In this grant, we propose creating a resource that will enable the continued development, maintenance, and support of these community tools and their dissemination within the community. These tools support 1000s of registered users in their basic science, pre-clinical, and translational research. Seattle Quant is a resource funded by the National Institute for General Medical Sciences (R24 GM141156) with the goal to support this community, maintain the tools, and expand the capabilities of the ecosystem of tools. Specifically, Seattle Quant has four aims. 1) Expand our test infrastructure to improve the robustness, stress test the software, confirm compatibility across computer systems, and track performance over time. 2) Improve support for both proteomics and non- proteomics workflows. 3) Improve the collection, sharing, annotation and dissemination of mass spectrometry data and Skyline documents. 4) Provide continued support and training for the Skyline ecosystem.

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