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.

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
8R01GM103551-02
Application #
8332840
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Sheeley, Douglas
Project Start
2011-09-14
Project End
2016-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
2
Fiscal Year
2012
Total Cost
$386,250
Indirect Cost
$136,250
Name
University of Washington
Department
Genetics
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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
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
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
Egertson, Jarrett D; MacLean, Brendan; Johnson, Richard et al. (2015) Multiplexed peptide analysis using data-independent acquisition and Skyline. Nat Protoc 10:887-903
Ting, Ying S; Egertson, Jarrett D; Payne, Samuel H et al. (2015) Peptide-Centric Proteome Analysis: An Alternative Strategy for the Analysis of Tandem Mass Spectrometry Data. Mol Cell Proteomics 14:2301-7
Whiteaker, Jeffrey R; Halusa, Goran N; Hoofnagle, Andrew N et al. (2014) CPTAC Assay Portal: a repository of targeted proteomic assays. Nat Methods 11:703-4
Bateman, Nicholas W; Goulding, Scott P; Shulman, Nicholas J et al. (2014) Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA). Mol Cell Proteomics 13:329-38
Broudy, Daniel; Killeen, Trevor; Choi, Meena et al. (2014) A framework for installable external tools in Skyline. Bioinformatics 30:2521-3
Sharma, Vagisha; Eckels, Josh; Taylor, Greg K et al. (2014) Panorama: a targeted proteomics knowledge base. J Proteome Res 13:4205-10
Bereman, Michael S; Johnson, Richard; Bollinger, James et al. (2014) Implementation of statistical process control for proteomic experiments via LC MS/MS. J Am Soc Mass Spectrom 25:581-7

Showing the most recent 10 out of 21 publications