Dear Skyline Users:

The Skyline Team is pleased to announce the Third Annual Skyline User Group Meeting, which will be held in Baltimore, MD on Sunday afternoon before ASMS.  We would like to thank the event sponsors (see below) for their generosity and interest in collaborating with the Skyline project on exciting new targeted and quantitative proteomics techniques.  Thanks to them, the meeting attendance is free, though registration is required.  We are also especially grateful to the investigators who have been deeply involved in helping to create some of the most exciting Skyline features available today or coming in the next version of Skyline, and who have agreed to speak about the research they are achieving with Skyline, described below. Finally, we thank the National Institute of General Medical Sciences (NIGMS) without which the past two years of Skyline development could not have happened.

--Brendan

When: Sunday, June 15th, 2014
               12:00 - 1:00 pm : Lunch served
               1:00 - 2:30 pm : Presentations
               2:30 - 3:00 pm : Snacks and break-out discussions
               3:00 - 4:30 pm : Presentations

Where: Westminster Hall (http://www.westminsterhall.org/), 519 W Fayette St, Baltimore, MD (map) (directions)

[registration closed]

Confirmed Speakers

Michael J. MacCoss, Ph. D. (University of Washington): Introduction and event host

Dario Amodei, Ph. D. (Mallick Lab, Stanford University): Multi-Instrument, Skyline-Based Comparison of DIA Peptide Detection and Statistical Confidence Tools
Data Independent Acquistion (DIA) promises sensitive, reproducible proteome-wide measurements, but also presents serious challenges of peptide detection and statistical confidence. This presentation will focus on the new advanced chromatogram peak picking model, based on mProphet, released with Skyline 2.5. It will compare Skyline automated peak picking with other available tools and algorithms and provide insights from the latest advances in Skyline peak picking to be available in the next version. (More info...)

Michael Bereman, Ph. D. (North Carolina State University): Statistical Process Control for Accessing Data Quality Throughout an LC MS/MS Experiment
Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. Its power as a quality control procedure lies in its primary focus on early detection of a process performing outside defined thresholds and the subsequent determination of the cause of that variation. In this presentation the method of statistical process control is discussed, how it can be used to monitor data quality in proteomics via LC MS/MS, and its implementation into Skyline as an external tool. (More info...)

Meena Choi (Vitek Lab, Purdue University): MSstats as an external tool in Skyline – an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments
MSstats is an open-source R package for statistical relative quantification of proteins and peptides in mass spectrometry-based proteomics. Recently MSstats became available to the users of Skyline as an external tool. This presentation will discuss the functionalities of MSstats, illustrate its practical use, and highlight plans for future development. (More info...)

Christopher M. Colangelo, Ph. D. (Yale University): The Integration of Skyline, Panorama, and LabKey Server Interface for R to Analyze the 2013-2014 ABRF sPRG Research Group Study
The ABRF Proteomics Standards Research Group (sPRG) is reporting the progress of a two-year study (2012-2014) which focuses on the development and characterization of a proteomics normalization standard consisting of 1,000 Stable Isotope Labeled Peptides. 40+ labs utilized Skyline and labs published their results to PanoramaWeb. Utilizing the data stored in Panorama we developed custom R scripts to characterization the standard across numerous instrumental platforms. (More info...)

Richard C. King, Ph. D. (PharmaCadence Analytical Services): Skyline: Everyday tool for protein quantification 
The workflow supported by Skyline has proven to be an effective and efficient way to developuseful quantitative LC-MS/MS assays for target proteins in support of pharmaceutical research and development. We present two examples of using Skyline in our daily work. (More info...)

Christopher Kinsinger, Ph.D. (National Cancer Institute): The Skyline software project for clinical proteomics: lessons learned 
In a world where thousands of software projects start up and fail each year, what factors distinguish highly adopted software like Skyline from the rest? Aside from having good code, what is the bigger picture that allowed Skyline software development to take off? A history of Skyline will be presented, within the context of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), where Skyline grew from an idea to critical enabling technology. Both sociological and investment considerations will be explored. (More info...)

Brendan MacLean (MacCoss Lab, University of Washington): Status of the Skyline open-source software project five years after its inception
The Skyline project started just after ASMS 2008 as a 2-year effort to bring better SRM/MRM software tools to the NCI-CPTAC Verification Working Group that could support the variety of mass spectrometers in use in participating laboratories. Nearly 6 years later, the Skyline project is a thriving proteomics community open-source collaboration supporting 6 mass spec instrument vendors, integrated with a wide variety of external software, with thousands of users worldwide and many thousands of instances started each week. In this presentation, the Skyline lead software engineer will present recent developments and a roadmap for the project's future. (More info...) 

New! Stephen Pennington, Ph. D. (University College Dublin): Label-free LC-MS and MRM assay development for discovery and verification of biomarkers for organ confined prostate cancer
Prostate cancer is a major cause of cancer deaths in men but many men live for relatively asymptomatic with the disease for years. Existing diagnostic tests, including PSA, are not ‘fit for purpose’ in that they do not support the key treatment (or no treatment) decisions that need to be made in the management of patients with prostate cancer. We’ve assembled a panel of protein biomarkers in blood that might support one such treatment decision and are using Skyline developed MRM assays to validate and advance a clinically useful protein biomarker signature. (More info...)

Jeffrey Whiteaker, Ph. D. (Paulovich Lab, Fred Hutchinson Cancer Research Center): CPTAC Assay Portal: a community web-based repository for well-characterized quantitative targeted proteomics assays
The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as a public repository of well-characterized quantitative, targeted proteomic assays. The purpose of the CPTAC Assay Portal is to facilitate widespread adoption of targeted MS assays by disseminating SOPs, reagents, and assay characterization data (linked to the portal through Panorama, https://panoramaweb.org). This resentation will describe the content and features of the assay portal, as well as how users can download and contribute targeted assays. (More info...)

New! Kristin R. Wildsmith, Ph. D. (Genentech): Skyline & Panorama Case Study: Targeted proteomics enables Alzheimer’s disease biomarker development
Developing biomarkers is no easy task, yet they are critical for successful drug development and for clinical diagnostics. To help fill the gap between discovery and clinical validation, with the help of Skyline, we developed a targeted-proteomic, multiple reaction monitoring (MRM) assay for the quantitation of 39 peptides corresponding to 30 cerebrospinal fluid (CSF) proteins. The candidate biomarkers were selected from multiple proteomic discovery experiments and biology that linked them to Alzheimer’s disease (AD). (More info...)

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