With the maturation of proteomics technologies, these tools are being used to improve our understanding of many basic and clinical questions in human and model organism biology - with the ultimate goal of an improved workflow for biomarker candidate validation. To handle this, laboratories have shown that targeted mass spectrometry measurements offer a promising alternative to immunological based assays. Critical to these experiments is software to handle the generation of instrument methods and the consequent analysis of the resulting data. We have developed a client software tool to handle these analyses called Skyline. In the last 2-3 years, Skyline has become one of the most widely software tools in proteomics. In this grant, we propose to continue the development and maintenance of Skyline, which currently supports hundreds of investigators in their basic science, pre-clinical, and translational research. Specifically, our proposal has five aims. 1) Add support for complex experiment models within Skyline's data structure and graphical user interface. 2) Support calibration curves, complex isotopomer deconvolution, routine statistical analyses within Skyline, and new algorithmic developments by the community within the Skyline architecture. 3) Support the analysis of full scan MS1 and MS/MS data. 4) Support targeted proteomics libraries and implement a repository to store and disseminate targeted proteomics methods. 5) Support automatic method optimization and real-time automatic acquisition parameter updates on ThermoFisher triple quadrupole mass spectrometers.
Mass spectrometry has been a fundamental technology for the analysis of proteins in health and disease. Laboratories have shown that targeted mass spectrometry measurements offer a promising alternative to immunological based assays that are the standard for quantitative protein measurements in clinical laboratories as well as basic research laboratories. Critical to these experiments is software to handle the generation of instrument methods and the consequent analysis of the resulting data so our software Skyline is a critical component to making targeted proteomics routine.
|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, César 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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