# Skyline Targeted Proteomics Environment

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2020 · $258,335

## Abstract

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.

## Key facts

- **NIH application ID:** 10049625
- **Project number:** 2R01GM103551-10
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Michael MacCoss
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $258,335
- **Award type:** 2
- **Project period:** 2011-09-14 → 2021-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10049625

## Citation

> US National Institutes of Health, RePORTER application 10049625, Skyline Targeted Proteomics Environment (2R01GM103551-10). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10049625. Licensed CC0.

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