Development on Skyline started in 2008 to fill a critical need for a software tool that enabled targeted proteomics experiments. Since then, Skyline has grown into an entire ecosystem of tools, expanding well beyond targeted proteomics. The Skyline software ecosystem is one of the most widely used software platforms in all of mass spectrometry, supporting thousands of investigators in their research. The synergy between Skyline software development and its vast and thriving user community uniquely generate exciting new opportunities for quantitative mass spectrometry. Skyline has been a key factor in the success and growth of this new field, with Skyline itself becoming one of the most significant software tools in mass spectrometry. Since 2015, we have expanded Skyline software, from just the traditional targeted proteomics experiments that used selected reaction monitoring (SRM) with triple quadrupole (QQQ) mass spectrometers, to broadly encompass ALL types of quantitative proteomics experiments, including data dependent acquisition (DDA) experiments using MS1 peak areas (aka MS1 filtering), targeted tandem mass spectrometry (aka parallel reaction monitoring or PRM) experiments and data independent acquisition (DIA). As of Oct 2019, Skyline has been installed >97,500 times (117% increase since 2015), has over 14,000 registered users (122% increase since 2015) on its website (http://skyline.ms) and is booted up >9,000 times per week (exceeding 17,500 bootups in a single week). The Skyline project has grown beyond the bounds of a single tool. Currently, there are 14 Skyline external tools (55% increase since 2015) that rely on a formalized framework in Skyline and available through its tool store, with more still in development. The prior grant cycle has greatly expanded a community of users and developers working with a common set of tools to analyze quantitative data from all six major mass spectrometry vendors. Specifically, our proposal has five aims. 1) Improve Skyline?s analysis of DDA data, 2) Improve Skyline?s analysis of DIA data, 3) Expand support of new molecule types within Skyline, 4) Support for new quantitative data types, and 5) Provide continued support and training for the Skyline ecosystem.

Public Health Relevance

Mass spectrometry has been a fundamental technology for the analysis diverse molecule types in health and disease. Targeted mass spectrometry measurements offer a promising alternative to immunological based assays that are the standard for quantitative protein measurements in clinical and basic research laboratories. Critical to these experiments is our software, Skyline and the associated ecosystem of tools, which have been developed to handle the generation of instrument methods and the subsequent analysis of the resulting data.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM103551-10
Application #
10049625
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Gindhart, Joseph G
Project Start
2011-09-14
Project End
2024-08-31
Budget Start
2020-09-23
Budget End
2021-08-31
Support Year
10
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Washington
Department
Genetics
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Sharma, Vagisha; Eckels, Josh; Schilling, Birgit et al. (2018) Panorama Public: A Public Repository for Quantitative Data Sets Processed in Skyline. Mol Cell Proteomics 17:1239-1244
MacLean, Brendan X; Pratt, Brian S; Egertson, Jarrett D et al. (2018) Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions. J Am Soc Mass Spectrom 29:2182-2188
Henderson, Clark M; Shulman, Nicholas J; MacLean, Brendan et al. (2018) Skyline Performs as Well as Vendor Software in the Quantitative Analysis of Serum 25-Hydroxy Vitamin D and Vitamin D Binding Globulin. Clin Chem 64:408-410
Pino, Lindsay K; Searle, Brian C; Bollinger, James G et al. (2017) The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. Mass Spectrom Rev :
Bereman, Michael S; Beri, Joshua; Sharma, Vagisha et al. (2016) An Automated Pipeline to Monitor System Performance in Liquid Chromatography-Tandem Mass Spectrometry Proteomic Experiments. J Proteome Res 15:4763-4769
Whiteaker, Jeffrey R; Halusa, Goran N; Hoofnagle, Andrew N et al. (2016) Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays. Methods Mol Biol 1410:223-36
Bollinger, James G; Stergachis, Andrew B; Johnson, Richard S et al. (2016) Selecting Optimal Peptides for Targeted Proteomic Experiments in Human Plasma Using In Vitro Synthesized Proteins as Analytical Standards. Methods Mol Biol 1410:207-21
Kawahara, Rebeca; Bollinger, James G; Rivera, C├ęsar et al. (2016) A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva. Proteomics 16:159-73
Egertson, Jarrett D; MacLean, Brendan; Johnson, Richard et al. (2015) Multiplexed peptide analysis using data-independent acquisition and Skyline. Nat Protoc 10:887-903
Abbatiello, Susan E; Schilling, Birgit; Mani, D R et al. (2015) Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma. Mol Cell Proteomics 14:2357-74

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