Table of Contents

guest
2018-12-19
Skyline Targeted Mass Spec Environment
   Release Notes
Install 64-bit Skyline 4.2
   Install 64-bit Skyline 4.2 Unplugged
   Skyline 4.2 Administrator Install
Install 32-bit Skyline 4.2
   Install 32-bit Skyline 4.2 Unplugged
Videos
   Video 1: Method Editing
   Video 2: Results Analysis
   Video 3: Existing & Quantitative Experiments
   Video: Trailer
Webinars
Tutorials
   教程 (中国语文)
     靶向 方法编辑
     靶向方法优化
     分析分类研究的数据
     处理已有定量实验数据
     小分子目标
     MS1 全扫描筛选
     靶向 MS/MS (PRM)
     非数据依赖型采集
     iRT 保留时间预测
   チュートリアル(日本語版)
     ターゲットメソッドの編集
     ターゲットメソッドの最適化
     によるグループ研究データの処理
     既存データ処理および定量実験
     によるターゲットメタボロミクス解析
     MS1フルスキャンフィルタ
     ターゲットMS/MS(PRM)
     DIA、データ非依存性解析
     iRT保持時間予測
   Targeted Method Editing
   Targeted Method Refinement
   Processing Grouped Study Data
   Existing and Quantitative Experiments
   MS1 Full-Scan Filtering
   Targeted MS/MS (PRM)
   Data Independent Acquisition
   Small Molecule Targets
   Small Molecule Method Development and CE Optimization (Draft)
   Small Molecule Quantification (Draft)
   Hi-Res Metabolomics
   Absolute Quantification
   Custom and Live Reports
   Advanced Peak Picking Models
   iRT Retention Time Prediction
   Ion Mobility Spectrum Filtering
   Collision Energy Optimization
   Spectral Library Explorer
   QuaSAR Quantitative Statistics
   ETH Targeted Proteomics Course Tutorials
Tips
   Audit Logging
   Import OpenSWATH Results
   DIA (Data Independent Acquisition)
     Generating an Overlapping Window Isolation List using Skyline
     Full Spectrum Demultiplexing of Overlapped DIA Windows using MSConvert
     Slides Explaining Data Independent Acquisition
     DIA Methods for Thermo Q Exactive
   New in Skyline 4.1
   Adduct Descriptions
   Surrogate Standards
   Calibrated Quantification Support in Skyline 3.5
   Parallel Import Performance
   Skyline System Requirements
   Vendor-Specific Instrument Tuning Parameters
   Ion Mobility Separation (IMS) Data
   Chorus Cloud Chromatogram Extraction
   Working with Other Quantitative Tools
   How to Display Multiple Peptides
   Terminology Cheat Sheet
   How Skyline Builds Spectral Libraries
   ID Annotations Missing with Mascot Search Results
   How Skyline Calculates Peak Areas and Heights
   Support for Bruker TOF Instruments
   AB SCIEX Instrument Settings
   Recovering From a Broken Installation
     Recovering the .sky File Extension Association
   Sharing MS/MS Spectra with Manuscripts
   Share Skyline Documents in Manuscripts
   Export SRM Methods for a Thermo LTQ
   Skyline Source Code
Documentation
Users Meetings
Publications
   ASMS 2012 WOA am MacLean Presentation
Press
Awards
License Agreement
Other
   How You Can Help
   Get Involved
   3rd-Party Software
   Related
Funding
Dashboard
Team

Skyline Targeted Mass Spec Environment


Skyline UsersWatch presentations from the Skyline User Group Meeting
at ASMS, San Diego, CA - Sunday, June 3rd, 2018
Skyline WebinarsWatch Video of the latest Skyline Tutorial Webinar
PRM Method Development and Data Analysis

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New! Spring Targeted Proteomics Course at the Buck Institute in the Northern San Francisco Bay Area (Navato, CA). (March 18 - 22, 2019) - Register NOW!

New! Spring May Institute for computation and statistics for mass spectrometry and proteomics at Northeastern University, Boston MA. (April 29 - May 10, 2019) - Register NOW!

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Fall Skyline@Duke Short Course, Durham, NC (December 10 - 14, 2018)

Past

Fall Targeted Proteomics Course at PRBB, Barcelona (November 12-16, 2018)

Fall International Targeted Proteomics Course Shanghai (October 22 - 23, 2018)

Summer Targeted Proteomics Course at University of Washington, Seattle WA. (July 30 - Aug. 3, 2018)

Summer SWATH/DIA Course at ETH, Zurich. (July 2 - 6, 2018)

Spring Skyline User Group Meeting at ASMS in San Diego (June 3, 2018)

Spring Case Studies in Quantitative Proteomics Workshop at ASMS in San Diego (June 2 -3, 2018)

Spring Computation & Statistics for Mass Spec & Proteomics Course at Northeastern U. Boston, MA (April 30 - May 11, 2018)

Spring Targeted Proteomics Course at Buck Institute in the north San Francisco Bay area, CA. (April 2 - 6, 2018)

Spring Design and Analysis of Quantitative Proteomic Experiments at US HUPO in Minneapolis (March 10 - 11)

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Skyline

Watch the Videos
from the 2018 Skyline
User Group Meeting



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Week-long Courses
at ETH Zurich

Recently Published

MacLean, JASMS - Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions
[full-text]

Sharma, Molecular & Cellular Proteomics - Panorama Public: A public repository for quantitative data sets processed in Skyline
[abstract]

Henderson, Clinical Chemistry - Skyline Performs as Well as Vendor Software in the Quantitative Analysis of Serum 25-Hydroxy Vitamin D and Vitamin D Binding Globulin
[abstract][article]

Pino, Mass Spectrometry Reviews - The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics
[abstract]

Bereman, Journal of Proteome Research - An Automated Pipeline to Monitor System Performance in Liquid Chromatography Tandem Mass Spectrometry Proteomic Experiments
[abstract]

More Publications




Release Notes


Skyline v4.2 Releasd on 11/01/2018

  • AUDIT LOGGING - yes, really [documentation]
  • New Figures of Merit section in Peptide Settings – Quantification tab
    • New LOD and LOQ fields in reports
    • New display in Calibration Curve plot
  • New calibration features
    • Regression fit = Linear in Log Space
    • Single-replicate calibration with isotope labeled standards for system suitability
    • Added Sample Dilution Factor field to Replicates in Document Grid for dilution of a sample to bring it within the linear dynamic range
  • Support for importing OpenSWATH results through File > Import > Peptide Search - DIA wizard [details]
  • Support for using integration boundaries and peak scores from OpenSWATH and EncyclopeDIA
  • Drift time predictor training from Use Results fixed for small molecules
  • Instrument support improvements:
    • Agilint - support for negative ion mode QqQ data
    • Bruker - timsTOF support for PASEF, All Ions, and PRM
    • SCIEX - support for new SCIEX WIFF2 file format & clearer method export, CE and DP settings
    • Shimadzu - support for 9030 Q-TOF and 8045 QqQ
    • Thermo - support for Thermo FAIMS, GC-MS, Tune v3+ compatibility, and faster raw file reader DLL
    • Waters - advances in SONAR and CCS calibration and importing data from UNIFI server
  • Settings > Integrate All no longer affects Precursors.TotalArea nor other quantitative metrics. At last, it is just visual.
  • File > Import or Export > Annotations for importing or exporting annotations values directly from or to a CSV file
  • New command-line support
    • --import-document = File > Import > Document
    • --import-annotations = File > Import > Annotations
    • --share-zip = File > Share
    • --import-all-files = File > Import > Results of all files in the directory specified, but not subdirectories
    • --import-all[-files] and --import-replicate-name together to import multiple files into a new replicate
    • --reintegrate-exclude-feature = unchecking feature in mProphet model
  • New library build support
    • Mascot error tolerant searches and PASEF searches
    • MassIVE mzTab
    • MetaMorpheus mzIdentML
    • Crux Percolator pepXML
    • PEAKS pepXML/mzXML export when scans are out of order
    • Proteome Discoverer ExpectationValue support and pdResult files with multiple workflows
    • MaxQuant deuterium labeling modifications and results lacking Labeling State column
  • Added new iRT standard mix RTBEADS
  • Added ability to separate CVs in Peak Areas > CV Histogram by precursor or fragment ions in mixed MS1 and MS/MS documents
  • Added Plot Type > Residuals to Retention Times > Alignment view
  • Faster volcano pot updates and format filtering peptides by protein attributes
  • Mouse centered zooming added to some graphs that did not yet have it
  • Edit > Delete of transitions removes matching transitions in matching reference precursors
  • Edit > Refine > Advanced new option to remove peptides without a matching spectrum
  • Added find support for report link columns with text display
  • Increased maximum fragment charge state to 20 for whole protein MS/MS
  • Increased custom molecule maximum mass from 100 KDa to 160 KDa
  • Added a new copy button in the lower-left corner of message boxes to make it clearer that form contents can be copied as text
  • Many smaller bug fixes such as:
    • Fixed problem reading Thermo raw files that have scans with multiple precursors.
    • Fixed "use results" on "Edit Drift Time Predictor" form to pay attention to whether "Use high energy offset" is checked. If it's not checked, then always use 0 for the high energy offset.
    • Fixed problem where matching chromatograms to transitions does not pay attention to m/z match tolerance and double counts transitions.
    • Fixed ion mobility lookup in spectral libraries to support high precision modifications.
    • Fixed bug where documents containing the adduct "[2M+H]" cannot be opened.
    • Fixed "Remove Peak" behavior when chromatograms showing more than one file.
    • Fixed performance and background updates for Retention Times - Regression view
    • Fixed to editing small molecules with MS1 precursors that resulted in document corruption
    • Fixed to allow unchecking "Intensity" in an mProphet scoring model
    • Fixed to improve performance in a document with 500 replicates
    • Fixed to improve graphs restoring their visible state in the absence of a .view file
    • Fixed performance for large iRT libraries
    • Fixed a bug where libraries were disregarding modifications when returning retention times
    • Fixed matching spectra in SCIEX Midas data to precursors with modifications, especially heavy labeled
    • Fixed problem where a mixed polarity .raw file can result in an error about the number of times not being equal
    • Fixed obscure Thermo scanfilter parsing issue with a negative SID
    • Fixed case where ModifiedSequence would display the wrong mass if there were two modifications on the same amino acid
    • Fixed unexpected error trying to use Centroided extraction from Waters data acquired in centroid mode
    • Fixed small molecule PrecursorIonFormula vs. PrecursorNeutralFormula in small molecules with isotope labeling
    • Fixed issue with neutral loss transitions not matching spectral libraries during a settings change
    • Fixed to keep fragment ion transitions from matching chromatograms extracted from MS1
    • Fixed error message for file access denied from "Win32 Error 5" to something more helpful
    • Fixed issue with importing transition lists containing O" or 17O
    • Fixed for Waters data import to allow both centroiding and lockmass correction
    • Fixed small molecule transition list reader when Transition Settings precursor and fragment mass types are different
    • Fixed small molecule transition list import where the product columns are left empty to imp[y that the precursor is the ion of interest for this row
    • Fixed excessive memory use building a background proteome
    • Fixed issue with chromatogram extraction from mixed polarity raw data files
    • Fixed protein annotation using Uniprot to keep up with changes in their interface
    • Fixed command-line to import all samples from a multi-sample WIFF file

Skyline v4.1 Release Updated on 6/19/2018

Skyline v4.1 Release Updated on 2/18/2018
Skyline v4.1 Released on 1/11/2018

  • Improved small molecule support [detail slides]
    • Support for NIST and self-built (from SSL format) small molecule spectral libraries with fragment annotation
    • Neutral molecules with multiple precursor adducts
    • Improved support for pasting small molecule transition lists with column headers
  • Bruker TIMS support that parallels IMS support for other vendors
  • A new Document Grid pivot editor and saved report layouts [detail slides]
  • Improved Import Peptide Search wizard for DIA with DDA for the mProphet workflow
  • File > Import > Assay Library makes importing Assay Library files easier than File > Import > Transition List
  • More performance improvements (memory use and speed) for large-scale DIA data processing
  • Interactive volcano plots for group comparisons with custom formatting [detail slides]
  • Interactive peak area CV histogram plots [detail slides]
  • High precision modification delta-mass support past a single decimal place
  • Points across the peak and manual integration adjustment visualizations in chromatogram plots [detail slide]
  • New line plot modes for summary (Replicate and Peptide Comparison) plots
  • Synchronized zooming available in summary (Replicate and Peptide Comparison) plots
  • New Import Results common prefix and suffix removal UI with real-time replicate name display
  • New delete button (red X) on the Document Grid
    • allows deletion from the Targets View (proteins, peptides, precursors and transitions)
    • filter and delete.
  • Possible to rename replicates from Document Grid (including copy-paste) with "Replicate Name" field
  • New "Exclude From Calibration" column on PeptideResult
  • New Quantitative column on Transitions [detail slides]
  • New non-blocking background population of Document Grid with full support for chromatogram values (times, intensities, mass errors) in Live Reports, both interpolated and raw values
  • New Edit > Integration menu with shortcuts for Remove Peak and Apply Peak to All
  • Display an informative warning when iRT calibration fails during import
  • Improvements for library building from peptide search formats which do not support probability cutoffs to make sure they get ordered correctly
  • Many other fixes...

Skyline v3.7 Release Updated on 9/10/2017

Skyline v3.7 Released on 6/12/2017

New features include:

  • Extensive performance improvements in speed and memory use for proteomewide, label-free DIA and DDA data processing
    • If you have the hardware, Skyline should be able to use up to 100% CPU and 100% of your memory. Though we continue working on making it do more with less.
    • Performance improvements in very large DIA (6,000,000 transitions x 20 files)
    • Convergence detection in mProphet modeling and 10 iteration maximum (down from 30)
    • New --import-process-count=[num] and --import-theads=[num] arguments for SkylineRunner. The former can yield up to 10x import performance improvement on a 24-core NUMA server and 2-4x on a standard i7.
  • Reduced .sky file size by 70% for large (over 1000 transitions) files
  • Multi-peptide peak area graph
  • Customizable color schemes
  • Import isolation scheme feature from DIA data files
  • Improved iRT calibration from DDA data directly into spectral libraries
  • Storing raw chromatograms in SKYD files. This is a big one which also gives us:
    • View > Transform > Interpolated (F12) shows the chromatograms as Skyline used to show them
    • View > Transform > None (Shift+F12) shows the raw uninterpolated chromatogram
    • Skyline can now always show in Full-Scan graph every spectrum from which chromatograms were extracted. Previously interpolation could cause spectra to be skipped
    • A new report value TransitionResults.PointsAcrossPeak
    • File > Share can now create document archives in 3.6 format for sharing to Skyline 3.6
  • File > Export > Spectral library for exporting targeted results as a spectral library for your next experiment
  • Support for semi-cleavage enzymes in Peptide Settings - Digestion tab
  • Support for Associate Proteins checkbox in View > Spectral Libraries with background proteome for nonspecific cleavage
  • Run-to-run retention time correlation graph
  • New file details (score type, score cut-off, unique peptides and spectra) in Spectral Library Explorer source file details form.
  • Support BLIB files with StartTime and EndTime in the RetentionTimes table
    • Allowing external tools to provide their own peak detection and picking
    • Times are used for peak integration boundaries without further peak detection
    • Faster imports and smaller resulting files
  • File > Import > Peak Boundaries 2-10x faster
  • Add Total Ion Current Area under Results.File in reports/Document Grid
  • Add "Equalize Medians" as normalization method in Peptide Settings / Quantification for large exploratory experiments where most targets are not changing
  • Improved paste performance in the Document Grid
  • Column tips and reference help in the Live Report view editor
  • New SkylineDailyCmd.exe in same folder as Skyline-daily.exe with same command-line interface as SkylineRunner.exe, but runs Skyline in a single process, useful for ZIP-file or Administrator installations where these EXEs are placed in easily located paths
  • Proteome Discoverer 2.2 support in spectral library builder
  • Improved support for SCIEX Midas workflow
  • Improved support for Agilent IMS workflow
  • Improved handling of importing modified peptide sequences with SCIEX 3-letter modification abbreviations
  • Export transition list feature for mixed polarity small molecule documents to allow exporting different polarities separately
  • Various other fixes such as:
    • Use of .NET API to encrypt passwords for Panorama and Chorus stored by Skyline in its user.config file.
    • Fix to z ion mass calculation, which was off by one hydrogen atom
    • Fix to View > Mass Errors > Replicates graph to match colors with other replicate graphs when MS1 and MS/MS XICs are present
    • Fix y axis scaling in chromatograms which had problems when IDs or Predicted annotations were present and scale was less than 100
    • Fix tracking of changes to iRT standards to better match changes to documents
    • Fix to avoid removing iRT standards when Edit > Refine > Advanced minimum transition count is higher than they contain
    • Fix to keep from duplicating spectrum source files - especially problematic for iRT training - in spectral libraries when a DDA file is searched twice
    • Slightly more tolerant peak grouping which allows undetected peaks to be added to the group based on chromatogram correlation over the integration boundaries.
    • Fix precursor matching with SRM data in fringe case where the precursor m/z is worse, but transition matching is better
    • Fix error message reporting missing required columns in File > Import > Peak Boundaries
    • Fix to "Unable to sort because the IComparer.Compare() method returns inconsistent results"

Skyline v3.6 Release Updated on 2/21/2017

Skyline v3.6 Released on 11/7/2016

New features include:

  • Improved results import:
    • Parallel multi-file results import (in user and command-line interfaces)
    • New results import interface for improved unattended imports
    • Greatly improved import performance for Skyline documents on network drives
  • Calibrated quantification improvements:
    • Surrogate standards for normalizing to explicit non-homologous molecules
    • Remove point right-click option in calibration curve graph
    • Explicit Global Standard Area added to replicates for explicit global normalization control with values like TIC
  • Group comparison additions and fixes to improve consistency with MSstats
  • New Detection Q Value and Detection Z Score report columns for mProphet scored peak picking
  • New Peak Rank By Level report value and Targets view showing separate peak rankings for MS1 and MS/MS transitions
  • Peptide uniqueness constraint added to Peptide Settings - Digestion tab (by protein, gene or organism)
  • New Edit > Refine > Associate Proteins for adding protein associations for targeted peptides after they have been added to the targets list
  • Ability to choose which modifictions to use when showing a library in the Spectral Library Explorer
  • New and improved plots:
    • Mass error plots (replicate and peptide comparisions and 1D and 2D histograms
    • Multi-peptide retention time plot
    • Point set selection in retention time regression plot
  • Improved small molecule support:
    • Improved support for negative ion mode
    • Improved chromatogram matching for molecules with identical precursor m/z but different scheduled retention times
    • Parsing of chemical formula with adduct syntax in Edit > Insert > Transitions
    • Support for small molecule transition list import with Edit > Paste, File > Import > Transition List, external tools and with command-line
  • Improved Transition Settings for Full-Scan
    • Centroided extraction with mass error tolerance made default, based on improvement seen with Thermo, Sciex and Bruker instruments
    • New high-selectivity extraction option (1/2 extraction width) for extraction from profile spectra, based on improvement seen with Termo and Sciex raw data files
    • Easier import of existing data with improved isolation schemes based on raw data
    • Fixed support for importing from instruments using different high- and low-resolution between MS1 and MS/MS
  • Ability to include ambiguously matched spectra in spectral libraries build by Skyline
  • Improved support for iRT:
    • Support for more iRT standard mixes
    • Automatic adding of iRT standard targets to document
    • More flexible iRT regression support (allowing 80% of standards at 0.995 correlation)
    • CiRT support
  • SkylineRunner command-line interface improvements:
    • Command-line support for importing transition lists and assay libraries
    • Command-line support for exporting isolation lists
    • Command-line support for adding decoy peptides
    • Improvements made to support AutoQC
    • mProphet model generation output to console log
  • Initial support for Sciex MIDAS data
  • Initial support fixes for Waters SONAR data
  • Fix for File > Save As bug that disabled Edit > Refine > Re-import
  • Many other smaller bug fixes

 

Skyline v3.5 Release Updated on 1/24/2016

Skyline v3.5 Released on 12/1/2015

New features include:

  • Calibrated quantification (a.k.a. absolute quantification) [see tip]
  • Impressive performance improvements for large full-scan data sets (DIA and DDA)
  • Many longer operations made much faster and showing progress form allowing cancel
  • Chromatogram extraction from centroided scans using mass accuracy in PPM (Peptide Settings - Full-Scan tab, using Centroided mass analyzer)
  • Improved small molecule support:
    • Support for negative polarity ions
    • Support for multiple ions per precursor, including isotope labeling
  • SkylineRunner command-line improvements supporting processing pipelines from raw data to Panorama uploads
  • Improved assay library and transition list import with better modification guessing
  • Full support for Panorama AutoQC system suitability run processing
  • Support for building spectral libraries from DIA-Umpire search results
  • Ability to include report templates in document with Document Settings
  • Fill Down function available on Document Grid right-click menu
  • Delete-key clears cells in Document Grid
  • Apply to All for faster manual correction of multi-replicate peak picking
  • Compensation voltage optimization for Sciex instruments with SelexION
  • Default Sciex SWATH isolation schemes and abilitly to export Sciex isolation lists
  • Automated drift-time training for Agilent and Waters IMS Q-TOF instruments
  • Lockmass correction for Waters Q-TOF data
  • Export directly to instrument methods for Shimadzu QqQ instruments
  • Many display improvements:
    • Peak area and background shading of selected transition
    • New residuals plot in Retention Times > Regression graph
    • Keep ID annotations from being hidden by chromatograms
    • Improved dotp display in Peak Areas plot
    • Option for strict scientific notation for intensity y-axis on plots
    • Graph text scaling based on right-click > Properties for all graph text

 

Skyline v3.1 Release updated on 4/13/2015

Skyline v3.1 Released on 3/16/2015

New features include:

  • Integrated Group Comparison support (see images below). Get started with:
    • View > Group Comparisons > Add
    • Settings > Document Settings - Group Comparisons tab
    • Tutorial coming soon...
  • Support for custom ions / small molecule targeted MS
    • Use Edit > Insert > Transitions - Small molecules to start a Skyline small molecule document
    • Watch Skyline Tutorial Webinar #4 - Preview of Small Molecule Support
  • Cloud chromatogram extraction from full-scan data with Chorus
  • New wizards for importing peptide searches with PRM and DIA data sets
  • Direct filtering of Document Grid views
  • Support for iRT scores in chromatogram libraries from Panorama
  • Faster start-up and file open and save progress
  • Fully enforced light-heavy ion matching and Find form support for "Mismatched transitions"
  • Improved optimization library support

 

Skyline v2.6 Release updated on 2/8/2015

Skyline v2.6 Release updated on 10/27/2014
Skyline v2.6 Released on 9/22/2014

New features include:

  • Full-Scan spectrum view for chromatograms extracted from full-scan data, with heat-map graph for IMS data
  • New Skyline start page for faster access to common start scenarios and tutorials
  • Ion mobility drift time filtering for Agilent and Waters TOF instruments
  • Optimization library support for storing optimized CE values
  • Custom fragment ion support for defining non-peptide-backbone fragments (like iTRAQ, TMT, etc.)
  • Support for isotope labeling experiments (like SILAC) without standards
  • Support for Shimadzu triple-quadrupole instruments
  • Improved chromatogram peak picking
  • Import of tabular "assay library" format
  • Support for protein details information (accession number, gene name and preferred name) queried from internet sites
  • DIA isolation scheme viewer
  • Option to exclude transitions within the DIA isolation window for the precursor

 

Skyline v2.5 Release updated on 7/10/2014

Skyline v2.5 Release updated on 5/5/2014

With:

  • Chinese and Japanese translations

Skyline v2.5 Released on 2/8/2014

New features include:

  • Live Reports - interact directly with Skyline documents through a grid interface with
    • Customizable column display
    • Sort and filter
    • Direct paste to annotation values
    • Text search
    • Much faster report generation than the original Custom Reports
  • Improved peak scoring and picking
    • Improved default peak picking
    • Integrated mProphet scores and semi-supervised learning model training
    • Edit > Refine > Reintegrate form for applying non-default peak scoring and picking models
    • Peak q value assignment
    • Model training and evaluation interface
  • Global standard type assignment
    • Right-click > Set Standard Type to assign Normalization and QC standard types
    • New icons to display iRT, Normalization and QC standard types in Targets view
    • New ratio values for peptides, precursors and transitions to global standard types in Peak Areas graph and reports
    • All global standard peptides measured in every method of multiple method documents
  • Fully integrated Tool Storeuser interface
    • Tools > Tool Store form for reviewing and installing External Tools without leaving Skyline or manually downloading files
    • Update notifications for new tool releases
    • Tools > Updates form for automatic updates to installed tools
  • Multi-peptide chromatogram graphs - use protein selection or multiple selection (shift- or ctrl-click) to see annotated chromatogram peaks for many peptides at once
  • Improved support for Scheduled Extraction of chromatograms from full-scan mass spectra
  • Improved File > Import > Peptide Search wizard
  • Thermo raw file import support on systems with European number format settings

 

Skyline v2.1 Released on 9/8/2013

New features include:

  • Support for building chromatogram libraries on Panorama and using them in Skyline
  • File > Import > Peptide Search wizard for DDA data quick start
  • Mass accuracy metrics for high resolution full-scan data
  • TIC and base peak chromatograms from MS1 survey scans
  • Installed support for Bruker TOF data, with improved performance
  • Demultiplexing of overlapped DIA/SWATH methods
  • Improved External Tool integration (see the list of available tools)
    • Install from file (Tools > External Tools - click Add button, and choose From File)
    • Automatic R installation
    • Automatic Python installation
    • Support for MSstats with new GUI form [download]
    • Support for QuaSAR with new GUI form [download]
  • Direct pasting into the Results Grid (especially useful for replicate annotations for external tools)
  • Fix to be able to distinguish peptides with the same precursor m/z in MS1 filtered data
  • Improved memory performance for large full-scan imports
  • Enhanced results data import progress interface with peak graph
  • Split chromatogram graphs for simultaneous viewing of light and heavy transitions, and precursor and product ions
  • Alignment by iRT scores in graphs
  • Improved integration with PanoramaWeb
  • Save and restore of Targets View expansion and selection state
  • Several spectral library builder fixes, including support for larger libraries and new search pipelines:
    • PEAKS pepXML/mzXML
    • MSGF+ pepXML/mzXML
  • File > Import > Peak Boundaries for importing peak selection from other tools
  • File > Export > Chromatograms for exporting chromatogram points

 

Skyline v1.4 Release Updated on 3/18/2013

With:

  • Support for building spectral libraries from Proteome Discoverer MSF
  • Support for building spectral libraries from MaxQuant Andromeda msms.txt

Skyline v1.4 Release Updated on 12/17/2012

With:

  • Support for building spectral libraries from PRIDE XML

Skyline v1.4 Released on 11/12/2012

New features include:

  • Bruker TOF support [details]
  • Export triggered MRM (a.k.a. iSRM) transition list support (Agilent and Thermo instruments)
  • Peak picking based on retention time alignment of MS/MS IDs for MS1 filtering
  • Improved retention time alignment features for MS1 filtering
  • Support for publishing Skyline documents to Panorama targeted proteomics repository web sites (server software currently in beta, available early 2013)
  • Support for MS1 filtering from SIM scans
  • Customizable Tools menu (EXE, Batch and Web site) with macro and custom reports as inputs and command-line customization for installers
  • Replicate custom annotations, e.g. Concentration, Case/Control, SubjectId, etc.
    (see the updated Existing and Quantitative Experiments tutorial pp. 30-35)
  • Replicate comparison graphs grouped by replicate annotations
  • Renaming of FASTA sequences (direct edit and Edit > Refine > Rename Proteins)

 

Skyline v1.3 Release Updated on 8/12/2012

Skyline v1.3 Released on 6/20/2012

New features include:

  • Advanced support for data independent acquisition (DIA) across vendors:
    • AB SCIEX SWATH™
    • Agilent DIA
    • Thermo DIA & Multiplexed DIA
    • Waters MSe™
  • Isolation list export for Thermo Q Exactive and Agilent TOF instruments
  • 64-bit version with higher memory limits
  • Retention time alignment for MS1 filtering
  • MS/MS retention times in built libraries for more peptide ID pipelines
  • Auto-refinement for selecting best responding peptides
  • Improved handling for high charge peptides
  • Auto-detection of modifications in the Spectral Library Explorer
  • Decoy peptide and transition generation for FDR based peak picking

 

Skyline v1.2 Release Updated on 3/27/2012

Skyline v1.2 Released on 2/15/2012

New features include:

  • Integrated display of MS/MS peptide ID spectra in MS1 chromatograms
  • Peak picking in MS1 chromatograms based on MS/MS peptide ID retention times
  • New isotope dot-product score on MS1 full-scan filtered peaks, and expected relative isotope abundance in peak area plot and reports
  • More accurate retention time prediction with integrated iRT Calculator support
  • Command-line interface for running Skyline operations in automated scripts on instrument control computers
  • Faster MS/MS library loading
  • Improved memory performance for full-scan chromatogram extraction
  • Improved full-scan method export for Thermo LTQs, including support for Accurate Inclusion Mass Spectrometry (AIMS)
  • Full-scan method export for AB SCIEX Q-TOFs, including support for AIMS
  • Data import support for Thermo Q-Exactive
  • Data import support for Waters Synapt G2-S
  • Spectral library build support for iProphet and Protein Prospector pepXML
  • New enhanced Find with Find All
  • Unexpected error form with button to report the issue
  • Manage results, minimize for reducing chromatogram data size in final documents

 

Skyline v1.1 Release Updated on 8/8/2011

Skyline v1.1 Released on 6/11/2011

New features include:

  • Import results from WIFF files much improved (50-fold faster for large scheduled runs - thanks to AB SCIEX)
  • Full-scan MS/MS ion chromatogram extraction
  • Full-scan MS1 multiple isotope ion chromatogram extraction
  • Full-scan method export for Thermo LTQ
  • Import document with multiple documents and support for merging results
  • Integrated support for Unimod modification definitions
  • Modification auto-detect support for pasted/inserted annotated peptide sequences
  • Native method export for AB SCIEX QTRAP
  • Native method export for Agilent 6400 Series
  • Spectral library build support for Scaffold, Waters MS^e and OMSSA
  • Improved Edit / Find in the Peptide View
  • Larger text sizes in the peptide tree view
  • Multi-select annotation editing
  • Multiple color annotation indicators
  • Improved scheduling for multi-replicate documents
  • Variable modification and neutral loss detection in transition list paste/insert/import
  • Peptide filter expression support for matching modifications
  • New bulk refinement operations
  • Replicate acquired time in reports and replicate plot ordering
  • New summary plots

 

Skyline v0.7 Release Updated on 3/30/2011

Skyline v0.7 Release Updated on 2/7/2011
Skyline v0.7 Release Updated on 10/30/2010
Skyline v0.7 Release Updated on 10/5/2010
Skyline v0.7 Released on 9/15/2010

New features include:

  • Variable modifications
  • Neutral loss product ion transitions
  • Native Waters file import support installed
  • Spectral Library Explorer
  • Multiple heavy label types
  • Multi-select copy-paste (text, HTML formatted, and Skyline document to Skyline document)
  • Peptide view enhancements (multiple selection, peptide modification highlighting, etc.)
  • Spectral libraries built from Protein Pilot results
  • Analysis support for fractionation replicates
  • Synchronized zooming of multiple chromatogram graphs
  • Copy data from graphs to re-plot with your favorite graphing package
  • Data import performance improvements for Agilent, AB Sciex and Thermo
  • Improved international system settings support

 

Skyline v0.6 Release Updated on 7/7/2010

Skyline v0.6 Release Updated on 5/21/2010

Now with native WIFF file import support installed.

Skyline v0.6 Release Updated on 4/21/2010
Skyline v0.6 Release Updated on 4/2/2010
Skyline v0.6 Released on 3/17/2010

New features include:

  • Improved automatic peak integration
  • Collision energy optimization
  • Peak area charts
  • Peptide summary charts
  • Manuscript ready charts
  • Results grid with per replicate annotations
  • Custom annotations
  • Auto-refinement dialog box
  • SpectraST library support
  • Unique peptides view with a Background Proteome
  • Improved support for document sharing
  • Summary result statistics in reports
  • Waters instrument native method export

 

Skyline v0.5 Release Updated on 11/8/2009

Skyline v0.5 Released on 9/24/2009
Skyline v0.5 Preview Updated on 8/14/2009
Skyline v0.5 Preview Updated on 7/7/2009
Skyline v0.5 Preview Released on 5/30/2009

The core focus of v0.5 is analysis of result data, building on the successful method creation features of v0.2. Our ASMS 2009 poster gives a broad overview of how we are using these features to extend the scope of our targeted proteomics research at the MacCoss Lab.

New features include:

  • Scheduled and unscheduled transition list support for instruments from:
    • Agilent
    • Applied Biosystems
    • Thermo Fisher
    • Waters
  • Import of results data for instruments from:
    • Agilent (native)
    • Applied Biosystems (native)
    • Thermo Fisher (native)
    • Waters (native with MassLynx 4.1 installed)
    • All of the above converted to mzML or mzXML
  • Share methods and results across labs with different instruments, using Skyline's high-performance, compact data caching
  • Build your own spectral libraries from Mascot and X! Tandem search results
  • Multiple sample replicates, and multiple replicate import
  • Chromatogram plotting with dynamic layout for multi-replicate viewing
  • Peak detection and advanced peak picking
  • Peak quality indicators
  • Isotope labeling ratios
  • Advanced peak integration editing
  • Dynamic report designer
  • Retention time analysis views:
    • Linear regression
    • Replicate comparison
    • Scheduling

 

Skyline v0.2 Released on 2/17/2009

Skyline is a Windows client application for building Selected Reaction Monitoring (SRM) methods. It aims to employ cutting-edge technologies for creating and iteratively refining SRM methods for large-scale proteomics studies. The latest version of Skyline contains support for:

  • Full featured SRM method editing
  • Transition list export for Thermo Finnigan TSQ and ABI Q-Trap
  • Retention time prediction
  • Isotope labeling
  • Spectral libraries (NIST, GPM, BiblioSpec)
  • Building spectral libraries from your results in TPP pepXML/mzXML

Skyline edits its own universal method format document (saved in XML), and can export transition lists for a variety of instruments. For large, un-refined methods these may be multiple lists per document.




Install 64-bit Skyline 4.2


Thank you for your interest in using Skyline software for your targeted proteomics research or mass spectrometer quality control.




Install 64-bit Skyline 4.2 Unplugged


Welcome to the 64-bit Skyline off-line installation page, the place to download an installer which you can use to install 64-bit Skyline on computers without internet access, such as instrument control computers used for native method export and quality control data assessment. These computers must be running a 64-bit version of Windows.

Please review the license terms before installing Skyline. If you accept the terms of the agreement, click I Agree to continue. You must accept the agreement to install Skyline.



To install Skyline without internet access:

  • Download the ZIP file from this page.
  • Extract its contents.
  • Run the setup.exe file in the extracted folder.
  • If you are told you need Windows Installer 3.2, you can download it from [here].
  • If you are told you need .NET Framework 3.5 SP1, you can download it from [here].
  • If you are told you need .NET Framework 4.0, you can download it from [here].
  • If you are told you need .NET Framework 4.5.1, you can download it from [here].
  • If you are told you need .NET Framework 4.7.2, you can download it from [here].

Remember, without internet access, Skyline will not be able to tell you about new releases and automatically perform updates. You will be responsible for making any necessary updates. You are more likely to fall behind on critical bug fixes and new features. If you have internet access, it is still preferable to use the normal web installation.




Skyline 4.2 Administrator Install


The administrator install of Skyline installs in C:\Program Files.  It is used for the rare cases where an administrator needs to install Skyline on a computer that many users have accounts on, and the administrator does not want each user to have to install Skyline themselves.

Known issues:

  • Only an administrator can install external tools in Skyline

Please review the license terms before installing Skyline. If you accept the terms of the agreement, click I Agree to continue. You must accept the agreement to install Skyline.






Install 32-bit Skyline 4.2


Thank you for your interest in using Skyline software for your targeted proteomics research or mass spectrometer quality control.

Install the 64-bit version for higher memory limits. However, you must have 64-bit Windows installed on your computer to use this version.




Install 32-bit Skyline 4.2 Unplugged


Welcome to the 32-bit Skyline off-line installation page, the place to download an installer which you can use to install 32-bit Skyline on computers without internet access, such as instrument control computers used for native method export and quality control data assessment.

Please review the license terms before installing Skyline. If you accept the terms of the agreement, click I Agree to continue. You must accept the agreement to install Skyline.



To install Skyline without internet access:

  • Download the ZIP file from this page.
  • Extract its contents.
  • Run the setup.exe file in the extracted folder.
  • If you are told you need Windows Installer 3.2, you can download it from [here].
  • If you are told you need .NET Framework 3.5 SP1, you can download it from [here].
  • If you are told you need .NET Framework 4.0, you can download it from [here].
  • If you are told you need .NET Framework 4.5.1, you can download it from [here].
  • If you are told you need .NET Framework 4.7.2, you can download it from [here].

Remember, without internet access, Skyline will not be able to tell you about new releases and automatically perform updates. You will be responsible for making any necessary updates. You are more likely to fall behind on critical bug fixes and new features. If you have internet access, it is still preferable to use the normal web installation.




Videos


Watch one of these instructional videos for a quick start using Skyline in your targeted proteomics experiments.  Although these three videos were recorded in 2009 and refer exclusively to the Skyline SRM support, they still provide a good bit of useful information about Skyline and how it may be used in setting up targeted proteomics experiments, even when using full-scan mass spectrometers.  For a more complete overview what you can do with Skyline, please refer to the Skyline tutorials.

Learn more about creating SRM/MRM methods in 28 minutes.

Video DemoVideo Demo 1

Learn more about results analysis and method refinement in 25 minutes.

Video DemoVideo Demo 2

Learn more about importing existing experiments and isotope labeled reference peptides in 27 minutes.

Video DemoVideo Demo 3

Watch the Skyline trailer video

Video TrailerVideo Trailer



Video 1: Method Editing


Try the Targeted Method Editing tutorial, and get hands-on experience.

The Camtasia Studio video content presented here requires a more recent version of the Adobe Flash Player. If you are you using a browser with JavaScript disabled please enable it now. Otherwise, please update your version of the free Flash Player by downloading here.

Download the full video for faster access to repeat viewing.

* - recorded using Skyline v0.2




Video 2: Results Analysis


Try the Targeted Method Refinement tutorial, and get hands-on experience.

The Camtasia Studio video content presented here requires a more recent version of the Adobe Flash Player. If you are you using a browser with JavaScript disabled please enable it now. Otherwise, please update your version of the free Flash Player by downloading here.

Download the full video for faster access to repeat viewing.

* - recorded using Skyline v0.5 Preview




Video 3: Existing & Quantitative Experiments


Try the Existing and Quantitative Experiments tutorial, and get hands-on experience.

The Camtasia Studio video content presented here requires a more recent version of the Adobe Flash Player. If you are you using a browser with JavaScript disabled please enable it now. Otherwise, please update your version of the free Flash Player by downloading here.

Download the full video for faster access to repeat viewing.

* - recorded using Skyline v0.5 Preview




Video: Trailer


The Camtasia Studio video content presented here requires JavaScript to be enabled and the latest version of the Adobe Flash Player. If you are using a browser with JavaScript disabled please enable it now. Otherwise, please update your version of the free Adobe Flash Player by downloading here.

Created by Alex MacLean



Webinars


The Skyline Team is excited to continue its tutorial webinar series designed to help you get the most out of Skyline targeted proteomics software. Now with sixteen sessions completed, Skyline Team members spends most of the time in these webinars explaining what the software is capable of and how best to use it to answer your research questions.

Each webinar has its own page (linked below) containing a recording of the webinar and all related information. The webinar recordings are about 90 minutes long with the last 30 minutes dedicated to Questions and Answers from the attending audience. Additionally, each webinar page contains the presentations, supporting tutorial data, written answers to the Q&A sessions and other related information. Even the most experienced Skyline users are likely to learn something new.

2018


 

2017 & 2016

 

2015

 

2014

 




Tutorials


[Chinese] [Japanese]

Try one of these tutorials, and get hands-on experience using Skyline with real data.

Introductory

 

Full-Scan Acquisition Data



 

Small Molecules

Small Molecule Quantification (23 pages, draft)
Hi-Res Metabolomics (13 pages, draft)


 

Advanced Topics

 

ETH Course Tutorials 2016 & 2018 (Skyline SRM/PRM/DIA + MSstats + mProphet tutorials with exercises)
SRM CourseETH Targeted Proteomics Course



教程 (中国语文)


[英语] [日语]

请选择尝试这些指南,以获得对实际数据运用Skyline软件的实际操作经验。

介绍性的

靶向方法编辑 (24 页)

 

靶向方法优化 (25 页)

 

小分子目标 (9 页)

 

 


全扫描采集数据

靶向 MS/MS (PRM) (39 页)

 



 


高级主题

 

更多即将推出!




靶向 方法编辑


获取针对靶向蛋白质组学实验创建Skyline文件的实际操作经验。在此指南中, 您将学会从pepXML和mzXML文件以及某个FASTA格式的背景蛋白质组文件中创建一个MS/MS谱图库。您会将这些信息与在GPM数据库网站(Gobal Proteome Machine)上的某个公共MS/MS谱图库相结合,以指导您创建一个新的Skyline文件去靶向分析一些特定的酵母蛋白质、肽段和子离子。从这个Skyline文件中,您会导出一个母离子-子离子对(transition)的列表,可以直接支持在AB公司的4000 Q Trap型质谱仪上检测分析 (24 页)。

[下载]

* - Skyline v0.6版本中开始引入, 已更新至 v1.4版本, 修订版本号为v2.5。




靶向方法优化


本教程是关于Skyline SRM数据分析的,内容涵盖导入仪器原始数据和对文档进行优化。利用多批SRM检测数据,本教程能够帮助你获得很多实际的操作经验。一开始,未优化文档给出的实验设计中,包括超过2000个需要检测的离子对,在Thermo TSQ平台上需要进行39次未预定的单次分析。在导入39次单次分析结果后,利用疏水性进行色谱保留时间回归分析,然后进行MS/MS图谱库的峰强度相关性分析,以提高检测到的色谱峰的可信度。在此基础上,可以利用Skyline进行实验设计优化,仅保留那些高可信度的色谱峰,从而筛选出精简的离子对列表。在优化完成后,对于预定实验设计,Skyline给出的离子对列表可以在一次分析中完成检测。在本教程中,这个实验设计的过程已经完成,你可以导入和查看多次重复实验检测的结果,以体验Skyline优化实验设计的效果。本教程总共有25页

[下载]

* - Skyline v0.6版本中开始引入, 已更新至 v1.4版本。

另外, 更多内容请参考我们发表在Proteomics 上的文章。(请引用)

The development of selected reaction monitoring methods for targeted proteomics via empirical refinement
[摘要]

 

了解更多 关于结果检查和优化实验设计方法的内容,可以阅读我们 ASMS 2009 的海报。

ASMS 2009 Poster




分析分类研究的数据


学习如何利用skyline有效的处理在一个生理状态下多个生物样品的实验数据。你将会使用一个可以被检测到的目标列表,并进一步优化该列表,使其可以只包含在健康和生病状态下在老鼠 (14只)的血浆中具有不同浓度的分子。在这个过程中,你讲学会如何使用skyline快速的研究和理解反常数据。你也会得到一些关于如何使用Skyline (版本3.1)来比较不同生理状态的经验。本教程总共有70页。)

[下载]

* - 根据版本3.1编写的使用说明




处理已有定量实验数据


通过本教程,你将学习如何处理已有的定量实验数据(不是由Skyline完成实验设计),包括利用稳定同位素标记肽段作为参考的实验。利用已知的离子对列表和已发布的SRM数据集,你可以获得这方面的实际操作经验,学习如何利用Skyline提供的色谱峰和色谱保留时间分析图表来进行高效的数据分析(本教程共39页)。 

[下载]

* - Skyline v0.7 版中引入, 更新至 v1.4版本。




小分子目标


学习如何利用skyline来分析小分子目标。你将会在skyline中导入一个小分子离子对的列表和14个Waters Xeve TQS 的实验数据。开始学习如何把skyline应用到小分子的实验中。本教程总共有9页。

[下载]

* - 根据版本3.1编写的使用说明




MS1 全扫描筛选


本教程将介绍如何利用Skyline完成无标记定量数据分析。在数据依赖(DDA)实验中,一般利用MS1信号强度构建离子流色谱峰(XIC),通过对比不同LC-Run中肽段的XIC面积来实现差异定量分析。在本教程中,你将学习利用Skyline从探索性实验数据集中构建图谱库,配置MS1过滤的Skyline文档,导入质谱仪原始数据文件,从MS1扫描中提取母离子的信号强度以构建XIC,然后根据MS/MS图谱肽段鉴定信息挑选合适的色谱峰,完成肽段定量。更重要的是,你还将学习如何利用Skyline进一步处理得到的定量结果。如果你对探索性实验无标记定量分析比较感兴趣,本教程将帮助你认识一个新的研究工具(本教程共37页)。 

[下载]

* - 在 v1.2版本中引入, 更新至v1.4版本, 修订版本号为v2.5。

另外, 关于Skyline无标记定量的算法和工作流程,更多内容参考我们发表在Molecular Cellular Proteomics 上的文章(请引用该文章):
Platform independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline. Application to protein acetylation and phosphorylation
[摘要]




靶向 MS/MS (PRM)


本教程将介绍利用Skyline完成高Agilent 6520 Q-TOF)低(Thermo LTQ)两种分辨率质谱平台的靶向MS/MS数据(也称为并行反应离子监测,PRM)分析,以便认识母离子-碎片离子对监测的肽段定量策略,在不同分辨率下选择性和灵敏度的差异。通过该教程,你将发现利用Skyline丰富的数据分析功能,能够帮助你理解自己的质谱数据,发现你自己质谱平台使用的新方法,以便更好地进行基于色谱分离的定量蛋白质组学分析。(本教程共39页) 

[下载]

* - 在v1.2版中引入, 更新至v1.4版, 修订版本号是v2.5。

另外, 更多信息请参考我们发表在Journal of Proteome Research 上的文章(请引用该文章)
Label-Free Quantitation of Protein Modifications by Pseudo-Selected Reaction Monitoring with Internal Reference Peptides
[摘要]




非数据依赖型采集


通过一个含有非依赖型数据采集和依赖型数据采集 (在同一个仪器上采集这两种数据)的实验方法来得到分析非依赖型数据的经验。定义和导出一个非依赖型数据采集方法的隔离方案。在进行非依赖型数据采集之前,进行依赖型数据采集,并利用其结果来建立一个质谱谱图库。根据质谱谱图库来选择对应目标蛋白质的多肽和离子对。用skyline导入并分析相关的非依赖型数据采集的结果来熟悉这个实验流程。本教程总共有40页。

[下载]

* - 根据版本2.6编写的使用说明




iRT 保留时间预测


本教程将引导你获得iRT技术的实际使用经验。iRT技术将校正过的、经验检测的肽段色谱保留时间存入一个库中,然后在预定实验中,用于离子对检测时间的确定和检测结果的验证。本教程中,你将学习如何校正自己的iRT计算器,以及更多的关于iRT-C18校正的过程。其中,iRT-C18是Biognosys在iRT-Kit中使用的肽段标准样品。本教程将引导你利用SRM数据、图谱库和探索性实验MS1过滤得到的色谱峰校正一个新的iRT计算器。同时,你将学习怎样对该iRT计算器进行再校正,以便用于洗脱梯度或者色谱柱不同的预定SRM实验。本教程将展示iRT预测的精度,以及高精度的iRT预测在色谱峰鉴定结果验证中,可以提供更高的可信度。(本教程共30页) 

[下载]

* - 在v1.2版本中引入, 更新至 v1.4版。

另外, 更多细节请参考我们发表在Proteomics上的文章 (请引用)
Using iRT, a normalized retention time for more targeted measurement of peptides
[摘要]




チュートリアル(日本語版)


[英語] [中国語]

これらのチュートリアルでは,実際のデータを用いた解析をご自身の環境で経験いただくことができます。

入門編


 

フルスキャン測定データの解析


上級者向け

iRT保持時間予測 (35ページ)

他の内容は近日公開する予定です!




ターゲットメソッドの編集


ターゲットとするプロテオミックスの実験に適したSkylineドキュメントを作成する為に必要な体験学習をする事ができます。このチュートリアルでは、pepXMLとmzXMLファイルからスペクトルライブラリを作成する方法、そしてFASTAファイルからバックグラウンドプロテオームファイルを作成する方法を学びます。これらの作成したファイルにGPM (Global Proteome Machine) 公開MS/MSスペクトルライブラリを追加することによって、選択された酵母タンパク質やペプチドそしてプロダクトイオンをターゲットするように Skylineドキュメントを更新する方法も学びます。この作成されたSkylineドキュメントからトランジションリストをエクスポートでき、AB 4000 Q Trapに使うことができます。(28ページ)

[ダウンロード]

* - Skyline v0.6にて導入。v1.4、v2.5で更新。




ターゲットメソッドの最適化


ここでは、幅広いSRMメソッドで測定されたデータをインポートし、Skylineを通じてトランジッションリストを最適化していく過程を体験することができます。ThermoのTSQでスケジュール化せず、2000を超えるトランジッションで39回の注入により測定した最適化されていないドキュメントから作業を開始していきます。まずは、39個のすべての測定データを一つの分析としてどのようにデータをインポートするかを学びます。ペプチドの疎水性度による保持時間予測やMS/MSスペクトルライブラリのピーク強度の相関性を利用して測定するピークの信頼度を高めていきます。Skylineの最適化ダイアログを使用して、最も信頼性のあるピーク以外を除外していきます。このようなステップにより、一回の注入による測定できるようにトランジッションのリストを減らしていきます。そして、一回の測定メソッドで複数の繰り返し測定の結果をインポートし確認します。(27ページ)

[ダウンロード]

* - Skyline v0.6より導入。v1.4にて更新。

私たちのProteomics誌の論文もご覧ください。(こちらを引用下さい)
The development of selected reaction monitoring methods for targeted proteomics via empirical refinement
[要約]


結果の確認やメソッドの最適化については、こちらのASMS2009のポスターもご覧ください。

ASMS 2009 Poster



によるグループ研究データの処理


大規模なデータの解析をSkylineにより効果的に処理する方法を学びます。ここでは、14匹のラットから採取した血漿での健常群と疾患群で検出したターゲットタンパク質の差がきちんと捉えられるようにしていきます。一連のデータを処理することを通じ、短時間でデータ全体を捉え、差を理解ができるSkylineの便利な画面表示を知ることができます。さらに、Skylineのバージョン3.1で導入された、Skylineによる群間の差の比較方法についても経験できます。 (73 ページ)

[download]

* - Skyline v3.1にて導入。




既存データ処理および定量実験


ここでは、公開されているSRMのトランジッションのリストと質量分析装置の測定データを用いて、Skylineにより安定同位体標識された内標準ペプチドを利用した定量分析について体験していきます。Skylineのピークエリアと保持時間のサマリーチャートを活用することで、あなた自身のデータを効果的に分析する方法を学びます。(45ページ)

[ダウンロード]

* - Skyline v0.7より導入。v1.4、v2.5にて更新。




によるターゲットメタボロミクス解析


ここでは、Skylineでの低分子化合物の解析について学びます。メタボロミクス研究で使用する低分子化合物のトランジションのリストとWaters社のXevo TQSで測定した14個のデータを使いながら、Skylineでどのように解析を行うかを習得していきます。(10 ページ)

[download]

* - Skyline v3.1にて導入。




MS1フルスキャンフィルタ


ここでは、ペプチドの発現量の差を、data dependent 測定(DDA)の実験でのMS1フィルタリングから得るための、Skylineドキュメントの作成方法について体験していきます。このチュートリアルでは、まず、探索的な実験のデータ(discovery data)からスペクトルライブラリを構築します。そして、SkylineドキュメントをMS1フィルタリング用に設定します。次に、測定したMS1スキャンデータからプリカーサーイオンのマスクロマトグラムを抽出するために質量分析装置で測定した生のデータをインポートします。クロマトグラム上の目的のピークのピッキングについては、MS/MSによるペプチド同定情報に基づき行われ、さらにSkyline上での処理を行うことで定量テータを得ることができます。もし、あなたが、探索実験のデータを用いたラベルフリーでの定量実験に興味を持っていらっしゃるなら、このチュートリアルはあなたの新しいツールとなるでしょう。(42ページ)

[ダウンロード]

* - Skyline v1.2より導入。v1.4、v2.5にて更新。

私たちのMolecular Cellular Proteomics誌の論文もご覧ください。(こちらを引用下さい)
Platform independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline. Application to protein acetylation and phosphorylation
[要約]




ターゲットMS/MS(PRM)


ここでは、ターゲットMS/MS(または、Parallel Reaction Monitoring(PRM、並列反応モニタリング))の方法について、低分解の質量分析装置であるThermoのLTQと高分解能の質量分析装置であるAgilent 6520 Q-TOFのデータを使って体験していきましょう。プリカーサーおよびフラグメントイオンを利用したペプチドの定量分析における選択性と感度について、分解能の異なる装置での測定による違いについて、理解することができるでしょう。クロマトグラフィーをベースとした定量プロテオミクスを実施する中で、Skylineが提供するさまざまな機能を活用することにより、質量分析データの理解と活用のための新しい方法を発見してください。(43ページ)

[ダウンロード]

* - Skyline v1.2より導入。v1.4、v2.5にて更新。

私たちのJournal of Proteome Research誌の論文もご覧ください。(こちらを引用下さい)
Label-Free Quantitation of Protein Modifications by Pseudo-Selected Reaction Monitoring with Internal Reference Peptides
[要約]




DIA、データ非依存性解析


ここでは、Data-independent acquisition(DIA、データ非依存性解析)について、同一装置で取得したDIAとDDAの測定データを利用していく方法で学んでいきます。まずは、SkylineでDIAデータを処理するための「Isolationスキーム」(DIAでのプリカーサーイオンのウィンドウ幅)の設定を行い、メソッドへエキスポートします。また、実験で使用するスペクトルライブラリをDDAのデータから、DIAの測定データの取得前に作成しておきます。そして、そのスペクトルライブラリからターゲットタンパク質を分析するためのペプチドやトランジションを選択します。そして、関連するDIAのデータをSkylineにインポートし、解析することで、DIAでの作業を始めるための基本的な流れを習熟していきます。 (43 ページ)

[download]

* - Skyline v2.6にて導入。




iRT保持時間予測


ここでは、スケジュール化された測定やピーク同定のための保持時間予測を行うためのiRT値について学んでいきます。校正された実測のペプチドの保持時間をライブラリーに蓄積することで、将来的に活用することができます。このチュートリアルでは、iRTカリキュレータによる校正方法や、Biognosys社により提案されているiRT-C18というキャリブレーションについて、iRT-Kitのペプチド標準品を用いて詳細に学んでいきます。さらに、SRMの測定データやスペクトルライブラリ、また、探索実験におけるMS1スキャンの測定データから得られたクロマトグラムピークからもiRT値を校正していきます。さらに、新しく設定したグラジエント条件で、新しいカラムを使用してスケジュール化したSRM測定をする際の、iRT値の再校正の方法も学習していきます。また、これらを通じて、iRT値に基づいて、保持時間を正確に予測することにより、クロマトグラムのピーク同定における信頼性が向上することもわかるでしょう。(35ページ)

[ダウンロード]

* - Skyline v1.2より導入。v1.4、v2.5にて更新。

私たちのProteomics誌の論文もご覧ください。(こちらを引用下さい)
Using iRT, a normalized retention time for more targeted measurement of peptides
[要約]




Targeted Method Editing


Get hands-on experience creating a Skyline document for a targeted proteomics experiment. In this tutorial, you will create a MS/MS spectral library from pepXML and mzXML and a background proteome file from a FASTA format file. You will combine these with a public MS/MS spectral library from the Global Proteome Machine to guide creation of a new Skyline document targeting selected yeast proteins, peptides and product ions. From this document, you will export a transition list, ready to run on a AB 4000 Q Trap. (26 pages)

[download]

* - written on Skyline v0.6, updated for v1.4, updated for v2.5, updated for v3.7

On February 10th, 2015, the Skyline Team produced Webinar #4: Targeted Method Design with Skyline, another great resource for this foundation topic.
[webinar]




Targeted Method Refinement


Get hands-on experience starting with a broad set of SRM measurements, importing instrument data, and refining the document. Start with an unrefined document requiring over 2000 transitions and 39 injections to measure unscheduled on a Thermo TSQ. Learn how to import all 39 injections into a single replicate. Use a hydrophobicity to retention time regression and ms/ms spectral library peak intensity correlation to improve confidence in measured peaks. Use the Skyline refinement dialog to remove all but the best transitions for the highest confidence peaks. Step through the scheduling process to reduce the document to a transition list that can be measured in a single injection. Import and view multiple replicates of the single-injection method. (26 pages)

[download]

* - written on Skyline v0.6, updated for v1.4, updated for v3.7

Also, see our paper in Proteomics (please cite)
The development of selected reaction monitoring methods for targeted proteomics via empirical refinement
[abstract]

On March 10th, 2015, the Skyline Team produced Webinar #5: Targeted Method Refinement with Skyline, another great resource for this topic.
[webinar]


Learn more about reviewing results and refining your methods by reading the ASMS 2009 poster.

ASMS 2009 Poster



Processing Grouped Study Data


Learn how to process multi-replicate study date effectively with Skyline. You will take an initial set of targets already refined as detectable and further refine this set for evidence of differential abundance between healthy and diseased subjects a study of plasma from 14 rats. In the process you will learn to use the powerful Skyline interactive displays to quickly investigate and understand data anomalies. You will also gain experience with the Skyline Group Comparison framework introduced in Skyline version 3.1. (70 pages)

[download]

* - written on v3.1

On April 7th, 2015, the Skyline Team produced Webinar #6: Effective Data Processing and Interrogation with Skyline, another great resource learning this material.
[webinar]




Existing and Quantitative Experiments


Get hands-on experience working with quantitative experiments and isotope labeled reference peptides, by starting with experiments with published transition lists and SRM mass spectrometer data. Learn effective ways of analyzing your data in Skyline using several of the available peak area and retention time summary charts. (41 pages)

[download]

* - written on Skyline v0.7, updated for v1.4

On December 1, 2015, the Skyline Team produced Webinar #12: Isotope Labeled Standards in Skyline, another great resource for this topic.
[webinar]




MS1 Full-Scan Filtering


Get hands-on experience creating a Skyline document to measure quantitative differences in peptide expression using the MS1 scans from your data dependent acquisition (DDA) experiments. In this tutorial, you will generate a spectral library from a discovery data set, set up a Skyline document for MS1 filtering, import raw mass spectrometer data to extract precursor ion chromatograms from MS1 scans, with peak picking guided by MS/MS peptide identifications, and further process the resulting quantitative data in Skyline. If you are interested in label-free quantitative analysis of discovery data sets, this tutorial will give you a new tool set for your investigation. (38 pages)

[download]

* - written on v1.2, updated for v1.4, revised for v2.5

Also, see our paper in Molecular Cellular Proteomics (please cite)
Platform independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline. Application to protein acetylation and phosphorylation
[abstract]

On October 21st, 2014, the Skyline Team produced Webinar #1: Getting the Most Out of DDA Data with Skyline, another great resource for working with DDA data in Skyline.
[webinar 1]
For an in-depth discussion peptide modifications, see Webinar #10: Working with Modifications in Skyline which was produced on September 29, 2016 by the Skyline Team and features importing PTMs, isotope labeling and importing large assay libraries, among other topics.
[webinar 10]

If you run into trouble seeing ID annotations in your chromatograms, be sure to consult Tip: ID Annotations Missing with Mascot Search Results. Even if you did not use Mascot, this tip may contain useful information.
[tip]




Targeted MS/MS (PRM)


Get hands-on experience working with targeted MS/MS (also referred to as parallel reaction monitoring - PRM) data acquired on a low resolution Thermo LTQ and a high resolution Agilent 6520 Q-TOF. Gain new understanding of the selectivity and sensitivity differences between peptide quantification using precursor and fragment ions measured on low and high resolution instruments. Discover new ways to work with and understand your own mass spectrometry data using the rich feature set provided by Skyline for working with chromatography-based quantitative proteomics. (40 pages)

[download]

* - written on v1.2, updated for v1.4, revised for v2.5

Also, see our paper in Journal of Proteome Research (please cite)
Label-Free Quantitation of Protein Modifications by Pseudo-Selected Reaction Monitoring with Internal Reference Peptides
[abstract]

On January 13th, 2015, the Skyline Team produced Webinar #3: PRM Targeted Proteomics Using Full-Scan MS and Skyline, another great resource for producing and working with PRM data in Skyline.
[webinar 3]
For a more advanced discussion see Webinar #9: PRM for PTM Studies which was produced by the Skyline Team on July 21, 2015 and covered using PRM data from a study of modifications on histones.
[webinar 9]




Data Independent Acquisition


Get hands-on experience working with data independent acquisition (DIA) data, using a workflow that utilizes DIA and DDA runs acquired on the same instrument in series. Define and export a DIA isolation scheme. Build a spectral library from DDA data acquired before the DIA runs for the experiment. Choose peptides and transitions for a target set of proteins based on the spectral library. Import and analyze related DIA runs in Skyline to master a simple workflow for beginning to work with DIA. (40 pages)

[download]

* - written on v2.6

On November 18th, 2014, the Skyline Team produced Webinar #2: Jump Start DIA Analysis with DDA Data in Skyline, another great resource for working with DIA data in Skyline.
[webinar]

On January 25, 2017 the Skyline Team produced Webinar #14: Large Scale DIA with Skyline, which highlighted the additional research and workflows developed in the 28 months since our first DIA webinar.
[webinar]




Small Molecule Targets


Learn how to target non-proteomic small molecule ions with Skyline. You will import a small molecule transition list used in a metabolomics experiment and import 14 runs from a Waters Xevo TQS. Start learning how to apply the power of the Skyline interface for small molecule experiments.(9 pages)

[download]

* - Originally written for Skyline 3.1; Updated for Skyline 3.6

On February 10th, 2015, the Skyline Team produced Webinar #4: Targeted Method Editing with Skyline, with a sneak peak of small molecule support.
[webinar]

On November 7th, 2017, the Skyline Team produced Webinar #16: Small Molecule Research with Skyline, with new material on small molecule support.
[webinar]


Learn more about using Skyline for small molecule quantification by reading this MSACL 2015 poster.

MSACL 2015 Poster



Small Molecule Method Development and CE Optimization (Draft)


Learn how how to create a Skyline document that targets stable isotope labeled small molecules from a literature citation, specified as only precursor m/z, product ion m/z, and collision energy values. Perform retention time scheduling and collision energy optimization for small molecules by importing a multi-replicate data set from a Waters Xevo TQ-S using initial CE values from a Sciex triple quad. Learn how many existing Skyline features created initially for targeted proteomics use can now be applied to small molecule data.(28 pages, draft)

[download]

* - Originally written for Skyline 4.1

On February 10th, 2015, the Skyline Team produced Webinar #4: Targeted Method Editing with Skyline, with a sneak peak of small molecule support.
[webinar]

On November 7th, 2017, the Skyline Team produced Webinar #16: Small Molecule Research with Skyline, with new material on small molecule support.
[webinar]




Small Molecule Quantification (Draft)


Learn how to create a Skyline document that targets small molecules specified as precursor ion chemical formulas and adducts, and product ion m/z values. Import a multi-replicate data set collected using LC-MS/MS on a triple quadulpole, and see how many existing Skyline features created initially for targeted proteomics use can now be applied to small molecule data.(23 pages, draft)

[download]

* - Originally written for Skyline 4.1

On February 10th, 2015, the Skyline Team produced Webinar #4: Targeted Method Editing with Skyline, with a sneak peak of small molecule support.
[webinar]

On November 7th, 2017, the Skyline Team produced Webinar #16: Small Molecule Research with Skyline, with new material on small molecule support.
[webinar]




Hi-Res Metabolomics


Learn how to create a Skyline document that targets small molecules specified as precursor ion chemical formulas and adducts. Import a multi-replicate data set collected on a Q Exactive Orbitrap mass spectrometer for a set of plasma samples, and see how many existing Skyline features created initially for targeted proteomics use can be applied to small molecule data. 

[download]

* - written on Skyline v4.1




Absolute Quantification


Get hands-on experience using Skyline with Excel to estimate the absolute molecular quantities of peptides in your experiments. (15 pages)

[download]

* - written on Skyline v1.1, updated for v1.4, updated for calibration features in v3.5

On December 1, 2015, the Skyline Team produced Webinar #12: Isotope Labeled Standards in Skyline, another great resource for this topic.
[webinar]

On April 15, 2016, the Skyline Team produced Webinar #13: Calibrated Quantification with Skyline, another great resource for this topic.
[webinar]

Also, see our paper in Nature Methods
Rapid empirical discovery of optimal peptides for targeted proteomics
[abstract]




Custom and Live Reports


Get hands-on experience working with the power of Skyline custom Live Reports to view, edit and export a wide range of values from your Skyline documents. These reports are perfect for use in Excel or with custom code written in R, Matlab, Java, C++ and other languages for doing deep statistical analysis after processing your instrument output with Skyline. Also learn to use the Skyline Results Grid view to gain access to these values and to add custom annotations while inspecting your data in Skyline. Follow this tutorial to greatly increase the scope of experiments you can achieve with Skyline. (38 pages)

[download]

* - written on Skyline v0.6, updated for v1.4, revised for v2.5




Advanced Peak Picking Models


Learn more about creating and testing advanced models for matching target peptides with chromatogram peaks in Skyline. With the 2.5 release, Skyline now supports creating linear combinations of individual peak scores using the mProphet semi-supervised learning algorithm.  In this tutorial, you will learn to generate decoy peptides and transitions, create and assess mProphet scoring models, and apply them to Skyline chromatogram peak picking, both for SRM and DIA/SWATH data.  You will learn about mProphet assigned q values (adjusted p values, based on FDR) and how you can associate them with your picked peaks and export them in a custom report. (28 pages)

[download]
 

* - written on Skyline v2.5

On January 25, 2017, the Skyline Team produced Webinar #14: Large Scale DIA with Skyline which included a fairly lengthy section on current peak picking strategies in DIA.
[webinar]





iRT Retention Time Prediction


Get hands-on experience with iRT, a technique for storing calibrated, empirically measured peptide retention times in a library for future use in retention time prediction for scheduled acquisition and peak identity validation. In this tutorial, you will calibrate your own iRT calculator and also learn more about the iRT-C18 calibration proposed by Biognosys for the peptide standards in their iRT-Kit. You will calibrate new iRT values from SRM data, a spectral library and chromatogram peaks filtered from MS1 scans in a discovery experiment. And, you will learn how to recalibrate these iRT values to schedule SRM acquisition on a new column with a new gradient. You will see how more accurate retention time prediction based on iRT can give you higher confidence in your chromatogram peak identity validation. (31 pages)

[download]

* - written on v1.2, updated for v1.4

On May 12, 2015, the Skyline Team produced Webinar #7: iRT Retention Time Prediction with Skyline, another great resource to learn more about iRT retention time normalization and library building concepts in Skyline.
[webinar]

On January 25, 2017, the Skyline Team produced Webinar #15: Large Scale DIA with Skyline with updated, advanced DIA workflows and using larger data sets. Webinar #14 also touches on iRT integration into method development.
[webinar]

Also, see our paper in Proteomics (please cite)
Using iRT, a normalized retention time for more targeted measurement of peptides
[abstract]




Ion Mobility Spectrum Filtering


Get hands-on experience using Skyline to work IMS-TOF data. Train a drift-time predictor for BSA spiked into yeast, and see how ion mobility separation improves the selectivity of chromagram extraction in complex data. Learn how to work with ion mobility data in Skyline and explore the 3D (m/z, IMS, intensity) spectra produced by IMS-enabled mass spectrometers.(26 pages)

[download]

* - written on Skyline v3.7

Also, see Brendan's presentation at the 2015 Agilent User Meeting at ASMS
Also, see Erin's presentation slides from the 2015 Skyline User Meeting at ASMS
Also, see the full data set on Panorama Public




Collision Energy Optimization


Get hands-on experience using Skyline to work with empirically measured optimal collision energy (CE) values. In this tutorial, you will create scheduled CE optimization transitions lists for a document with 30 peptide precursors. Using supplied RAW files from a Thermo TSQ Vantage, you will recalculate the linear equation used to calculate CE for that instrument. You will also export a transition list with CE values optimized separately for each transition. (12 pages)

[download]

* - written on Skyline v0.6, updated for v1.4

Also, see our paper in Analytical Chemistry (please cite)
Effect of Collision Energy Optimization on the Measurement of Peptides by Selected Reaction Monitoring (SRM) Mass Spectrometry
[abstract]




Spectral Library Explorer


Get hands-on experience working with the Skyline Spectral Library Explorer, new in v0.7. Learn more about working with isotope labels and product ion neutral losses using MS/MS spectral libraries containing 15N labeled and phosphorylated peptides. Use the Library Explorer to accelerate the transition between shotgun discovery experiments and targeted investigation. (22 pages)

[download]

* - written on Skyline v0.7, updated for v1.4




QuaSAR Quantitative Statistics


Preferred use of QuaSAR has changed from a GenePattern web page to a Skyline External Tool, installable and directly integrated into Skyline.

[download]




ETH Targeted Proteomics Course Tutorials


In 2016, members of the Aebersold lab at ETH, Zurich - with help from CRG, University of Washington, Purdue and Biognosys - presented the last week long course on targeted proteomics with SRM, PRM and DIA to 30 participants. During the course, the participants worked through 9 tutorials with follow-up exercises. This material has been made freely available on the Targeted Proteomics Course web site, providing a great resource to anyone interested in learning more about Skyline method editing and data processing (8 Skyline + MSstats + mProphet tutorials)

[go there] (2016)

Targeted Proteomics CourseETH Targeted Proteomics Course

* - written on Skyline v3.5

You can also watch the presentation videos.


In 2018, many of the same instructors with some new additions presented the second week long course on DIA/SWATH for proteomics to 50 participants. That course included new tutorials and lectures aimed at teaching DIA/SWATH data processing and use in proteomics research, with some very nice examples using Skyline. You can download them form the same location.

[go there] (2018)

DIA/SWATH CourseETH DIA/SWATH Course

* - written on Skyline v4.1

You can also watch the DIA/SWATH Course presentation videos.




Tips





Audit Logging


(This tip applies to Skyline-Daily 4.1.1.18257 and later.)

When enabled, the audit log will keep track of all changes that are made to the current document. The audit log is stored as a separate file (.skyl), alongside with the skyline document.

The audit log can be accessed from the View menu. The audit log is displayed in a grid, similar to the document grid. In the top right corner audit logging can be enabled or disabled.

For new documents, audit logging is enabled by default.

Reasons to enable Audit Logging

•Reproducibility: The audit log makes it easy to see what changes were made to a document and can be used to reproduce a document step-by-step. 
•Collaboration: If multiple people are working on the same document it can be helpful to have a record of what each person has done to the document. 
•Troubleshooting: If the user encounters an error in Skyline, the audit log can be helpful for the Skyline team to diagnose and fix the issue.

 

Full details can be found here (PDF).




Import OpenSWATH Results


NEW! in Skyline 4.2: You can now import OpenSWATH results either from TSV or OSW file into Skyline for data visualization and beginning the targeted method refinement process.

See the PowerPoint slides attached below and watch the video from the ETH DIA/SWATH course:




DIA (Data Independent Acquisition)





Generating an Overlapping Window Isolation List using Skyline


(This tip relates to Skyline v 4.2 or later.)

This is a quick demonstration on how to use Skyline to generate an overlapping-window isolation window list suitable for acquisition using the approach described in this manuscript and downstream computational demultiplexing.

To begin this demo, start with a blank Skyline document: 

  • From the Skyline landing page, click Blank Document

  • On the Settings menu, click Transition Settings and in the Transition Settings dialog box, click the Full Scan tab.

SkylineFullScan 

  • Under MS/MS filtering, click the Acquisition method dropdown and select DIA. 
  • For the Isolation scheme, select Add ...

 SkylineAddIsolation

  • In the Edit Isolation Scheme dialog, enter a name for the Isolation scheme such as '20mz_overlap' and then click the Prespecified isolation windows radio button.  

SkylineIsolationScheme 

  • Click the Calculate ... option and enter parameters for the method.  
  • Enter '500' for Start m/z.
  • End m/z is '500'.
  • Window width should be '20'.
  • Be sure that Deconvolution is set to Operlap and that Optimize Window Placement is checked.

SkylineCalculationIsolation

  • Click OK to close the Calculate Isolation Scheme dialog and OK to close the Edit Islation Scheme window.
  • Click OK once again to close the Transition Settings dialog.
  • From the main Skyline menu, select File and then Export.  From the flyout menu, click the Isolation List ... option. 

SkylineExport1

  • In the Export Isolation List window, select the appropriate instrument (for this example, 'Thermo Q Exactive') and choose a file location in which to save the list of isolation windows.

SkylineExport2 

The resulting isolation list contains the isolation centers of each isolation window in the order that they should be acquired. NOTE: the isolation centers will need to be regenerated using this approach if any of the other acquisition parameters such as isolation width or m/z range covered are changed.





Full Spectrum Demultiplexing of Overlapped DIA Windows using MSConvert


(This tip relates to Skyline 4.2 and later.)

This is a quick demonstration on how to use MSConvert to generate a demultiplexed dataset from an input datafile(s) containing spectra with overlapping data independent acquisition windows. In the case of the overlapped window approach described in this manuscript, the output from MSConvert will contain twice as many spectra as the input (two demultiplexed spectra are generated from each acquired MS/MS spectrum). This tutorial uses MSConvert distributed with ProteoWizard version 3.0.18328 with vendor libraries downloadable here: http://proteowizard.sourceforge.net/download.html

 

  • Open MSConvert and select the Browse option to select the input overlap-multiplexed files.  
  • Select the SIM as spectra option.

msconvert1

 

  • OPTIONAL: Change the output format for the file using the Output format drop-down menu. This tutorial outputs mzML.
  • Add a Peak Picking filter to the data by selecting the options indicated below and clicking the Add button below the Filters section:

msconvert2

This causes the MS2 data to be centroided prior to demultiplexing, which is currently a requirement for full-spectrum demultiplexing using MSConvert. If the data were acquired with centroiding enabled, this step will have no effect and demultiplexing will proceed as expected.

 

  • In the Filters section, add a Demultiplex filter with optimization set to Overlap Only  with the settings shown below. 
  • Click the Add button.

msconvert3

 

Note that the mass error may need to be adjusted depending on instrument platform. The mass error should be set to the maximum error expected in m/z measurement of the same analyte in subsequent spectra. Note that this measurement is of expected deviation of a measurement from spectrum to spectrum, not its deviation from the correct theoretical m/z (mass accuracy).

  • Click Start to output demultiplexed files.





Slides Explaining Data Independent Acquisition


Powerpoint slides with useful information on the fundamentals of Data Independent Acquisition (DIA) are provided below.

Introduction to Data Independent Acquisition

DIA Method Design

DIA Data Analysis

Future Directions of DIA

Please note that these slide decks are incomplete because slides containing unpublished data have been removed.  If you would like the full slide deck for your personal use, or would like to use some of these slides in your own presentation, please contact the MacCoss Lab at: info@maccosslab.org

Additional material on DIA:

DIA Tutorial

DIA Methods for Thermo Q Exactive

DIA Webinar




DIA Methods for Thermo Q Exactive


The attached mini-tutorials explain how to set up DIA methods for the Thermo Q Exactive instrument:




New in Skyline 4.1


Attached are a collection of slides created by the developers as they added new features in Skyline 4.1 which required a bit of explanation:

  • Small molecule spectral libraries, improved adducts, and identifier (InChiKey, InChi, CAS, and HMDB)
  • Document Grid and Live Report pivot and layout support
  • Group comparison volcano plot with formatting
  • Peak Area CV histogram plots
  • Quantitative property for transitions
  • Points across the peak visualization in chromatogram plots



Adduct Descriptions


(This tip applies to Skyline-Daily 3.7.1.11357 and later)

Ionization in Peptides vs Ionization in Small Molecules

Skyline assumes protonation for peptides so we can simply speak about "charge" or "charge states". For generalized molecules, we have to think about all kinds of ionization so we speak in terms of "adducts". Adduct descriptions may also specify isotope labels applied to the neutral molecule description. As such, "adducts" are similar to the idea of "modifications" in the peptide regime. 

Describing Ionizing Adducts

Skyline uses the defacto standard notation for ionizing adduct descriptions, as found at the Fiehn Lab's MS Adduct Caclulator and the GNPS Spectral Library. This notation has a few major parts:

Usually beginning with a left brace "[",

then an optional  dimer/trimer/etc specification,

then an "M"

then an optional isotope label specification,

then the chemical formula of the adduct,

then a closing right brace "]".

Simple Examples

Singly protonated: [M+H]

Doubly deprotonated: [M-2H]

Sodiated: [M+Na]

N-Mer Examples:

Sodiated dimer: [2M+Na]

Deprotonated trimer: [3M-H]

Isotopic Label Examples

Sodiated, and two carbons per molecule replaced with C13: [M2C13+Na]

Sodiated, and two carbons per molecule replaced with C13, and three nitrogens replaced with N15: [M2C133N15+Na]

Charge-Only Examples:

Often transition lists are presented as m/z values with integer charges only, and the actual mode of ionization can not be inferred. In these cases we just give an integer charge value.

Unknown ionization mode, charge = 1: [M+] or [M+1]

Unknown ionization mode, charge = -2: [M-2]

Charge-Only Examples with Isotope Labels:

Sometimes a transition list indicated different precursor m/z values for the same named molecule, Skyline reads this as an isotope label of unknown formula, and expresses the mass shift as a number.

Unknown ionization mode, charge = 1, and mass shift due to unknown isotopes of total mass 5: [M5.0+]

 

 

 




Surrogate Standards


Sometimes you want to normalize a particular analyte against a different molecule. Skyline supports this with the "Surrogate Standard" feature.

To designate that a molecule can be used as a surrogate standard, right click on the molecule in the Targets tree and choose "Set Standard Type > Surrogate Standard".

You have to use the Document Grid to change the normalization method of the analyte. The "Normalization Method" column is not shown by default, so you need to customize a view in the Document Grid and add that column. You can start by choosing "Peptides" from the Views dropdown on the Document Grid. Then, choose "Customize View" and add the "Normalization Method" to the view. The Normalization Method column is under "Proteins > Peptides". (also note the button at the top with the binoculars icon can be used to find columns by name)

If you have surrogate standards in your document, then the "Normalization Method" column will have options of the form "Ratio to surrogate..."




Calibrated Quantification Support in Skyline 3.5


Calibrated quantification (a.k.a. absolute quantification) has been added to Skyline in version 3.5. We plan on extending documentation of this feature in the future in a number of ways:

  1. Updating the existing Absolute Quantification tutorial
  2. Writing a new tutorial on calibrated quantification that covers all of the available applications
  3. Including a detailed demonstration of the functionality in a future webinar

Until this work can be completed, however, you can find attached to this page a set of PowerPoint slides which hopefully provide enough of a rough overview of what is now possible that anyone interested can at least get started with the new functionality.

Also, the Skyline Tutorial Webinar #12 gives some initial coverage on this feature near the end of the recording (and in presentation slides).




Parallel Import Performance


Attached to this page you will find a thorough study of how Skyline scales importing large scale DIA data with parallel file import of various file types on either a standard Intel i7 comptuer with 16 GB of RAM versus a Dell PowerEdge with 48 logical processors 196 GB of RAM, using either multiple threads or multiple processes.

General findings include:

  • Multiple process import can scale past mutiple threads in the same process (which we think is related to garbage collection)
  • Only multi-process import can take advantage of the true potential of a NUMA system with 24+ logical cores
  • The difference is much less pronounce on an i7 an may not be worth the effort to go multi-process
  • Many formats pay only a percentage increment for spinning disk versus SSD
  • The mz5 format, otherwise the fastest format to import, has serious problems scaling with parallel file import on a spinning drive

At the time of this writing, only the Skyline command-line interface (presented by SkylineRunner or SkylineCmd) can take advantage of multi-process import by using the --import-process-count argument.




Skyline System Requirements


OPERATING SYSTEM:

Skyline runs on Windows 7 or later. 

Skyline is tested nightly on 64-bit Windows 7 and 64-bit Windows 10. Most of our development is on Windows 10 (and 7), but we know of no reason Windows 8 and 8.1 shouldn't work. 

We test the 32-bit Skyline build, but not regularly on a 32-bit OS, and < 10% of Skyline use is now 32-bit. We are likely to phase out 32-bit builds sometime in 2018.

Skyline 2.6 was the last version to support Windows XP. (All versions of Skyline since 1.4 can be downloaded from "Unplugged" installation pages by clicking "I Agree" and then the "Archive" link.)

 

PROCESSOR, MEMORY AND DISK:

There is no minimum requirement, but for performance reasons a large fast hard drive is desirable.  The amount of memory needed depends on the size of your experiments, but 4GB is a good start. Skyline is frequently taught on relatively average modern laptops. But, for larger-scale processing we recommend a more powerful desktop system with dual 24-inch monitors to take full advantage of Skyline display capabilities.

We recommend modern i7 quad-core processors, running at 3.5 to 4.0 Ghz work well, with 16 to 64 GB of RAM and a fast SSD (e.g. 500 GB) + a spinning HD with more room (e.g. 2 TB).

Recent orders for Skyline developers have been the following configuration for $1829 USD:

Dell XPS 8900 Desktop - Intel Core i7-6700 6th Generation Quad-Core Skylake up to 4.0 GHz, 64GB DDR4 Memory, 1TB SSD + 4TB SATA Hard Drive, 2GB Nvidia GeForce GT 730, DVD Burner, Windows 10

https://amzn.com/B01DUVEZ6K

For really large-scale projects, like hundreds of DIA or DDA files with many hundreds of thousands of transitions, Skyline now makes effective use of highly multi-processor (NUMA) servers with 192+ GB of RAM. We have been using Dell PowerEdge R630 with 48 logical processors and 192 GB (spec attached - purchased for under $10,000 USD). For best import performance, use SkylineRunner command-line interface with --import-process-count=12 (or similar). Be sure to run tests. Mileage may vary depending on the import file format and disk drive type and speed.

With a large server like this, make sure the power profile is configured for "maximum performance", both in Windows and UEFI/BIOS. (Check Power Options and make sure this is not set to "Balanced", but "High performance" and check with your IT about BIOS settings.)



Vendor-Specific Instrument Tuning Parameters


As of release 3.5, Skyline's small molecule support includes the ability to explicitly set many vendor-specific instrument tuning parameters on a per-precursor basis.

The "Insert Transition List" dialog for small molecules now has columns for importing various vendor-specific values such as "S-Lens", "Cone Voltage", "Declustering Potential" and "Compensation Voltage", along with the previously implemented ability to explicitly set "Collision Energy", "Retention Time" "Retention Time Window", "Drift Time", and "Drift Time High Energy Offset". These values can also be modified in the Document Grid.

These values can also be modified in the document grid for peptides (formerly this was only possible for small molecules).

By default S-Lens values are not written: a new checkbox in the Export Method dialog enables this for appropriate Thermo outputs. On the commandline side, there is a new argument "exp-use-s-lens" for this.




Ion Mobility Separation (IMS) Data


Skyline supports IMS data for Waters, Agilent and Bruker instruments.  Using an ion mobility predictor can help Skyline ignore unwanted signals and improve data quality.  By specifying the predicted ion mobility for each molecule of interest you can tell Skyline to ignore other scans that might contribute noise.

To add or change an ion mobility predictor, use the Settings|Peptide Settings menu item and select the Prediction tab, then the Ion Mobility Predictor button to bring up the Ion Mobility Predictor table editor.  

The easiest way to set up an ion mobility predictor table is to start with a Skyline document with imported results, then use the "Use Results" button in the Ion Mobility Predictor editor.  This simply scans the existing imported results and determines the ion mobility value of the scan containing the most intense peak.  Once you have that, you can reimport the data and Skyline can ignore scans at the proper retention time but wrong ion mobility.

There is a risk, of course, that the most intense peak at a given retention time isn't actually that of the precursor you are interested in, in which case you will be making the noise situation worse instead of better.  The ideal way to use this training feature is with simple training sets that elute one precursor at a time.  If you do not have that capability then you should go through and verify the ion mobility selections manually using the chromatogram viewer's intensity heat map of mz vs ion mobility.




Chorus Cloud Chromatogram Extraction


Skyline 3.1 introduces the ability to query raw data files stored in the Chorus raw data repository for chromatograms and spectra. Hopefully we will have a more detailed tutorial on this soon, but in the meantime you can download and watch this video comparison of extracting chromatograms from raw DIA on a local hard-drive and the same data on Chorus.

You can also consult the slides from Brendan's ASMS 2014 presentation:

Start a project on Chorus and upload your full-scan (DIA, PRM or DDA) data to get started today.

NOTE: Remote chromatogram access not yet supported for SRM data or MSX data.
NOTE: We are currently working on supporting Agilent and Waters full-scan IMS data.




Working with Other Quantitative Tools


The Skyline project has implemented integration with many tools and instrument platforms.  Skyline supports building spectral libraries from the outputs of nearly 20 different peptide spectrum matching pipelines.  It exports methods to and imports data from the instruments of 6 different vendors.  And, Skyline integrates with a number of external tools and the Panorama targeted proteomics knowledge base.

Here are two brief tutorials describing how Skyline also integrates with other chromatography-based quantitative tools and information they may produce:

Importing Integration Boundaries from Other Tools
This tutorial covers Skyline support for importing the start and end integration times determined for peptide elution by tools other than Skyline.  You can use this feature to benchmark or visualize the performance of other tools, or simply to incorporate their results into a Skyline-based workflow.

Importing Assay Libraries
Several tools have begun to use enhanced transition lists (with added relative product ion abundance and normalized retention times - iRTs) called "assay libraries".  To better support this format, Skyline will now suggest creating an iRT calculator and a minimal spectral library during transition list import when these extra columns are detected.  Learn what to expect and what to watch out for when using this feature. 




How to Display Multiple Peptides


Skyline allows you to compare chromatograms of different peptides by selecting them in the Targets  panel shown by default on the left side of the Skyline window.

For example, to see all the peptides belonging to a particular protein, click on the protein name in the Targets panel:

Skyline generates a color for each peptide based on the peptide sequence and modifications.  This provides a quick way to identify the matching chromatogram in the graph.  A peptide will always have the same color, even in different Skyline documents, unless there is another peptide within the same protein that generates the same color.  That doesn’t happen too often, but when it does, Skyline picks one of the conflicting peptides and assigns it a new color that is easier to differentiate.

Color swatches are shown in the Targets panel next to only those peptides which are shown in the graph.  In the example above, only the peptides under the selected protein are shown in the graph.

The peptides are also labeled in the graph with a unique abbreviation.  If the first three letters of the peptide’s name are unique (among the peptides being graphed), then only three letters will be used in the abbreviation.  If the first three and last three letters together are unique, the abbreviation will use those (see ASL…KGK in the example above).  More complicated abbreviation schemes are used if the first and last three letters are not unique.  Note that a peptide’s abbreviation can change depending on what other peptides are being displayed at the same time.

Graphing peptide subsets

The Targets panel allows you to select any subset of peptides you want.  You can select just a few peptides (from one protein, or across different proteins) by clicking on the first, and then holding the CTRL key down while clicking on additional peptides.  You can toggle a peptide by clicking on it multiple times with the CTRL key depressed.

You can select individual peptides by clicking on their names, or you can select all the peptides belonging to a protein by clicking on the protein name.

 

 

All peptides

To see every peptide in the document graphed, click somewhere in the Targets panel to transfer focus there, then type CTRL-A (or choose Select All from the Edit menu):

Note that this can take some time to display if your document contains a large number of peptides.

Displaying all the peptides will produce a graph that looks similar to the progress displayed during data import:

But you can see differences between this graph and the one above.  Peptide colors will usually match, but occasionally they don’t if a different color is needed to disambiguate two peptides in the same protein.  Peak values can also differ, because different summation criteria are used during import than later when more processing has been done on the raw data.




Terminology Cheat Sheet


At the recent Targeted Proteomics Course at UW 2014, participants claimed that the many terms we have in mass spec proteomics with exactly the same meaning made the course much more difficult to follow.  They requested a glossary or cheat sheet that might help them translate between these various terms.  Here it is:

SRM - Selected Reaction Monitoring (sometime confused as Single Reaction Monitoring - no such thing).  Common synonym MRM (Multiple Reaction Monitoring).  Performed on triple-quadrupole instruments, where the instrument cycles through a pre-specified set of precursor m/z (Q1), product m/z (Q3) pairs called 'transitions', using the quadrupoles as filters (usually 0.5 to 1.0 m/z range).  Cycle time is determined by the sum of the dwell times of all transitions in the set.
MRM - Multiple Reaction Monitoring, a synonym for SRM created and trademarked by AB SCIEX, but extremely popular because of early popularity of AB Q TRAP instruments for performing this method.
scheduled-SRM = scheduled-MRM = dMRM = dynamic-MRM - In order to allow measuring a greater number of transitions in a run, transitions are specified with start and end times (or retention times and windows) to allow the instrument to measure each transition for only a fraction of the entire gradient.  Cycle time at any given time is determined by the sum of the dwell times of all transitions being measured at that time.
iSRM = intelligent-SRM = triggered-SRM = triggered-MRM = tMRM - In order to gain more confidence in the correct identification of a chromatogram peak in SRM without overly sacrificing quantitative throughput, the instrument measures a set of primary transitions, as in normal SRM/MRM until the intensity on those transitions exceeds some threshold.  When the threshold is exceeded, the instrument takes one or more measurements of a secondary set of transitions usually used only for peak identity confirmation, and not quantification. 

Targeted MS/MS = tMSMS = PRM = MRM-HR - Like SRM, but performed on a full-scan instrument (ion-trap or Q-TOF).  The instrument cycles through a pre-specified set of precursor m/z values, using quadrupole or ion trap isolation as a filter (usually 1.0 to 2.0 m/z range) and collects a full MS/MS fragment ion spectrum for each.  Cycle time is determined by the sum of the dwell/accumulation or scan times of all scans in the set.  Software is used to extract chromatograms from the resulting MS/MS spectra.  If the spectra are high-resolution, then extraction can be done using 50-100pm range, making it more selective than SRM.  Common synonyms PRM (Parallel Reaction Monitoring), MRM-HR (HR = High Resolution), pSRM (Pseudo Selected Reaction Monitoring).

MS1 [Full-Scan] Filtering - Chromatograms are extracted from the MS1 scans of normal DDA (Data Dependent Acquisition) data.  Because of the semi-random sampling approach, for MS/MS, of DDA, it is not possible to extract product ion chromatrams (time, intensity) with meaningful peaks for quantification.  Chromatogram-based quantification from DDA runs is limited to extracted ion chromatograms from the MS1 survey scans of such runs.  Common synonym Label Free Quant.

DIA = SWATH = HRM - Data Independent Acquisition is a technique where ranges of precursor m/z are isolated and subjected to fragmentation in a consistent pattern over cycles of time.  In this way a mass spectrometer can be set up to gather fragment ion spectra for large regions of precursor m/z space, independent of the actual precursor ions being fragmented, which may include fragments for multiple precrusors in any given scan.  Software can be used to extract product ion chromatograms from the acquired MS/MS spectra.  Cycle time is determined by the sum of the dwell/accumulation or scan times of all scans in the set.  (e.g. 20 ranges x 10 m/z = 200 m/z total range, 30 ranges x 20 m/z = 600 m/z total range)
SWATH - Popular synonym for DIA coined in Gillet, et al. MCP 2012, but also trademarked by AB SCIEX, originally specified as 32 x 25 m/z ranges covering 400 - 1200 m/z.
HRM - Hyper Reaction Monitoring, less common synonym for DIA/SWATH.
MSe - Type of DIA where ions are collected without prior filtering in alternating low- and high-energy scans (all precursors and fragments of all precursors respectively), coined and trademarked by Waters.  Common synonym All-Ions DIA.




How Skyline Builds Spectral Libraries


Skyline builds spectral libraries using a separate program called BiblioSpec, which has two main components. BlibBuild is called to build the redundant library, which is then filtered by BlibFilter to create the non-redundant library. The BlibBuild page contains information on the various search engines that are supported, along with information about their respective file formats and the scores used with the cut-off value specified in Skyline.

BlibFilter chooses the best spectrum within a group by simply using the one with the best score. If there are multiple spectra tied for the best score, the one with the highest TIC is selected. In the past, BlibFilter chose the spectrum with the highest average dot product when compared to all other spectra within the same group, but this method occasionally produced poor results. A similar method, computing a consensus spectrum and its dot product against the related spectra, also produced inferior results as it sometimes resulted in high-noise spectra being chosen.

Skyline with BiblioSpec supports building libraries from the following peptide spectrum matching pipeline outputs:

  • Mascot (DAT)
  • ByOnic (mzIdentML / MGF)
  • Comet (sqt / ms2, pepXML / mzXML)
  • Myrimatch / IDPicker (mzIdentML / mzML)
  • MaxQuant Andromeda (msms.txt with modifications.xml)
  • Morpheus (pepXML / mzXML)
  • MSGF+ (mzIdentML / mzML)
  • OMSSA (pepXML / mzXML)
  • Peaks (pepXML / mzXML)
  • PeptideShaker (mzIdentML)
  • PRIDE XML
  • Protein Pilot (group or group.xml)
  • Protein Prospector (pepXML / mzXML)
  • Proteome Discoverer (MSF / pdResult)
  • Scaffold (mzIdentML / MGF)
  • Spectrum Mill (pepXML / mzXML)
  • TPP (pepXML / mzXML)
  • X! Tandem (xml output)
  • PLGS - Waters MSe (final_fragment.csv)
  • Custom (SSL)

 

Importing Existing Spectral Libraries

Skyline can also read existing spectral libraries including:

  • SpectraST (.sptxt) 
  • theGPM  X! Hunter (.hlf) 
  • Shimadzu (.mlb)
  • NIST (.msp)

Working with NIST files

If your library contains spectra for multiple instruments and conditions (e.g. various CE values) it is important to use the NIST-supplied filtering tools to produce a subset of spectra appropriate to your experimental conditions. Each molecule+adduct (or peptide+charge) pair can appear in a .blib file only once, and without thoughtful filtering you will almost certainly produce a .msp file that can't be used by Skyline because it contains more than one instance of a molecule+adduct (or peptide+charge) pair.




ID Annotations Missing with Mascot Search Results


Skyline supports several workflows where the retention time of peptide search identified MS/MS spectra are used to help it pick chromatogram peaks, and for subsequent visual inspection.  The most visible effect of when this extra information is present and usable by Skyline is the addition of ID annotations to the chromatogram graphs, as shown below:

If you build a spectral library or use the Import Peptide Search wizard to import Mascot search results for use with full-scan chromatogram extraction, and find that you do not see ID annotations in your chromatograms as you would expect, the problem most likely originates with the MGF converter you used to create MGF files as input to Mascot.

For Skyline to be able to place an identified spectrum on an extracted chromatogram, it needs two things, beyond the peptide identification itself:

  1. A spectrum source file name that Skyline can match with the data file used to extract chromatograms.
  2. A retention time at which the spectrum was measured.

The spectrum source file name does not need to match exactly with the file specified in the Import Results form.  Skyline uses base name matching, which counts all of the following files as matching:

  • spectrum_source.raw
  • spectrum_source.mzXML
  • spectrum_source.c.mzXML
  • spectrum_source.ms2
  • spectrum_source.mzML

Note also that Skyline completely ignores any path information included with the spectrum source file name. Many converters will include a full path, but this is not necessary, and Skyline will match chromatogram data imported from any path, as long as the file basenames match.

The first place to look for clues on contents of any library is the Skyline Spectral Library Explorer (View > Spectral Libraries).  A library built from search results that contain the necessary information will look like this:

If you click the button beside the Library drop down list, Skyline will display the Library Details form with a list of the spectrum source files from which there are identified spectra in the library:

The most common issue you will see with a Mascot DAT file is that it does not contain spectrum source file information in a format that Skyline can understand.  That format can be traced back to the TITLE lines in your original MGF file.  Thanks to a lack of standardization in this area, a long stream of bug reports has lead to Skyline handling a number of different TITLE line formats, but the most flexible and robust format are:

TITLE=...File: "path/to/file.raw"...

or slightly less robust:

TITLE=...File: path/to/file.raw ...
TITLE=...[path/to/file.raw]

Since the first does not allow spaces in the path, and the second does not allow brackets in the path.  Note again that the path information will be ignored by Skyline in matching with imported chromatogram files, though characters in the path can have a negative impact on parsing of some formats (e.g. spaces in format that relies on a space as a terminal character).

The retention times are provided by RTINSECONDS lines in the MGF like:

RTINSECONDS=3006.0281

Problems in either of these can cause issues that show up like the following Spectral Library Explorer figures:

Issue 1: The TITLE line in the MGF file did not contain a recognizable format (described above) from which the spectrum source file can be parsed, causing the DAT file name to be used instead.  If your DAT file contains the search results for a single file, this can be corrected by simply renaming the DAT file to have the same base name as the data file you will import for chromatogram extraction (e.g. spectrum_source.dat).

Issue 2: The RTINSECONDS line in the MGF file was missing, causing the spectrum RT value to be set to zero.

Issue 3: A time outside the gradient length is shown.  Something has gone wrong with the library builder parsing this file.  You should report something like this to the Skyline team.

Issue 4: Every spectrum has a different source file not representative of files on disk.  Something has gone wrong with the library builder parsing this file.  You should report something like this to the Skyline team.

If you run into any problems like this, we always recommend installing ProteoWizard and using MSConvertGUI to create your MGF files, as shown below:

Note that you must make sure the TPP compatibility check box is checked.

If the MGF converter you used comes from an instrument vendor or professional software company, and you want help communicating with them what is required for full integration with a workflow that includes Skyline, either point them to this page, or post your issue to the Skyline support board.




How Skyline Calculates Peak Areas and Heights


Definition:

  1. Background height: minimum intensity at peak boundaries
  2. Background area (named Background):
    • rectangular area of background height times the length between peak boundaries (pre-v1.4 patch 1)
    • total integrated area of the minimum of background height and intensity at each point (v1.4 patch 1 and later)
      (Note: the unit of RT time is second for this calculation)
  3. Peak height (named Height): maximum intensity between peak boundaries minus background height
  4. Peak area (named Area): total integrated area within peak boundaries minus background area (Note: the unit of RT time is second for this calculation)
    • area can be zero and background greater than total raw area (pre-v1.4 patch 1)
    • area plus background always equals raw area (v1.4 patch 1 and later)

NOTE: Skyline uses points that have been linear interpolated from the raw data onto a uniform interval over the duration of the chromatogram in detecting its peak boundaries and calculating its peak areas. These are also the points Skyline displays in its chromatogram graphs. Skyline uses several types of smoothing (1st derivative, 2nd derivative and Savitzky-Golay) in order to place its automatically calculated peak boundaries. These smoothed curves are available for display in the Skyline chromatogram graphs. Skyline does not, however, use smoothed data in calculating peak areas (or area under the curve - AUC). It always uses the raw interpolated points presented in the unsmoothed graphs.

Example of calculation of peak height and background area:

 

Note: with v1.4 patch 1 and higher the light blue areas are not included in the background area.





Support for Bruker TOF Instruments


Skyline v2.1 introduces fully integrated support for Bruker micrOTOF-Q and maXis series instruments.  The Skyline support for working with full-scan mass spectra has been extended to Bruker TOF instruments, and data acquired with them in several modes:

  • MS1 Filtering - chromatogram extraction from MS1 scans in data dependent acquisition (DDA) experiments
  • Targeted MS/MS (PRM) - chromatogram extraction from MS/MS scans in pseudo-SRM experiments
  • Data Independent Acquisition (DIA) - chromatogram extraction from MS/MS scans acquired in various isolation schemes
    • Consecutive wide windows
    • All Ions - alternating low energy and high energy scans of the entire instrument range

For more information on working with Skyline and Bruker TOF instruments, consult the following resources:

  • HUPO 2012 Bruker Lunch Seminar [PowerPoint][PDF]
  • Targeted Proteomics with Bruker TOF Instruments tutorial [PDF]

The following supporting files may also be useful:

  • Skyline template documents for Bruker TOF data analysis [ZIP]
  • Script for adding retention times to MGF files for peptide searches [Script]



AB SCIEX Instrument Settings


Attached to this page you will find Skyline settings files created by AB SCIEX as helpful defaults for the QTRAP and TripleTOF instruments.

To load these settings files into Skyline, perform the following steps:

  • On the Settings menu, click Import.
  • Select one of the .skys files.
  • Click the Open button.

This will add a new menu item to the Skyline Settings menu, either QQQ_QTRAP_Environment or TripleTOF_Environment depending on which file you imported.  To change the settings on your current document, simply choose one of these menu items.  This will change the document settings to the defaults that AB SCIEX has created for their instruments.




Recovering From a Broken Installation


If you know your current release is out of date, but Skyline has not asked to upgrade after two restarts, you should first try simply manually installing again from the web page over the top of your existing installation. If this does not work, read on.

At times a Skyline installation may become so broken that you cannot install a new release over the top of your existing installation.  In this case, you will need to find the Skyline installation files on your computer, save your Skyline settings, and then either uninstall or potentially even delete the Skyline files before you can re-install and subsequently restore your settings.  This tip will walk you through doing just that.

Finding and Saving Your Settings

First, you need to find your Skyline installation.  On Windows 7 or Windows Vista, you first want to find the folder:

C:\Users\brendan\AppData\Local\Apps\2.0

On Windows XP, it will be something like:

C:\Documents and Settings\brendan\Local Settings\Apps\2.0

If you are unable to find either the AppData (Windows 7 and Vista) or the Local Settings (Windows XP) folder, you may need to do the following in Windows Explorer:

  • Press Alt+T, O to open the Folder Options form.
  • Click the View tab.
  • Under the Hidden files and folders item, click the Show hidden files and folders option.
  • Click the OK button.

You should now be able to see the necessary folder in Windows Explorer.

To save your Skyline settings before removing the Skyline files, do the following:

  • Use Windows Explorer to search within the Apps\2.0 folder for the file 'user.config'. (Starting at C:\ will be a very long search!)
  • If you find more than one, look at the Date Modified and In Folder fields to determine which is the most recent under a folder beginning with 'skyl..'.
  • Hold down the Ctrl key on your keyboard, click the mouse cursor on the file and drag it to your desktop.

Now you have a copy of your Skyline settings on your computer desktop.

Removing Skyline From Your System

The next thing you should try is to simply uninstall Skyline, using the Control Panel ("Uninstall a program" in Windows 7 & Vista, and "Add/Remove Programs" in Windows XP).  If the uninstall fails, then you have no option but to clean up manually.

Before attempting to delete your Skyline installation, you should expand the folders below the '2.0' folder, so that you seem something like the folder tree shown in the image below:

Skyline installation folders

If your '2.0' folder looks much the same as the one above, then you can simply delete the entire '2.0' folder now, but be very careful with this option, as you may have other software in here.  If you see any differences, delete only the folders beginning in 'skyl..'.

Re-installing Skyline and Restoring Settings

You have removed Skyline from your system.  After restarting the system, try again to install Skyline from the Skyline web site or stand-alone installers.

After you have installed successfully, close the Skyline window.  Then again find the 'user.config' under '2.0', belonging to a folder beginning with 'skyl..' and copy the user.config you saved to your desktop over the top of the new user.config, which will contain only the default settings.

You should now be able to start Skyline and see that your settings have been preserved, and continue working with Skyline as normal.




Recovering the .sky File Extension Association


If you end up in a state where you can no longer double-click in the Windows Explorer on .sky or .skyd files and have Skyline open the files for you, do the following:

  • Run regedit.exe and delete the following keys if any are present (they may not all be)
  • Delete the keys HKEY_CLASSES_ROOT\.sky and HKEY_CLASSES_ROOT\.skyd
  • Delete the keys HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Explorer\FileExts\.sky and .skyd
  • Delete the keys HKEY_CLASSES_ROOT\Skyline.Data.0 and HKEY_CLASSES_ROOT\Skyline.Document.0
  • Reboot your computer
  • Wait for an update or reinstall Skyline (see also Recovering From a Broken Installation)

Thanks to Stack Overflow for this entry:

https://stackoverflow.com/questions/6489112/clickonce-deployment-file-association-not-registering




Sharing MS/MS Spectra with Manuscripts


If you are looking for a MS/MS spectrum viewer, you may not be familiar with Skyline, a tool developed primarily to aid targeted proteomics investigation.  Skyline does, however, provide features that make it ideal for sharing MS/MS spectra with manuscripts before and after publication.  Skyline displays fully annotated spectra for peptides with post translational modifications (PTMs) and neutral losses extremely quickly, and the Skyline software itself is freely available and easy to install. [Install Now]

If you already have a Skyline document that was submitted as part of a manuscript follow the steps below to use Skyline to view these spectra:

  • On the File menu, click Open (ctrl-O).
  • Select the shared file you are working with (usually .sky.zip).
  • Click Open.

Once the file is open in Skyline, it should look something like this:

If you do not see the MS/MS spectrum graph:

  • On the View menu, click MS/MS Spectra.

If you want to see different precursor charge states for the peptides in the document:

  • On the Edit menu, choose Expand All and click Peptides.

Select peptides or precursors in the Peptide View on the left to see the corresponding MS/MS spectrum.

For PTMs in the Peptide View, any modified amino acid is bold and underlined.

If you hover over a protein name, the positions of the peptides it contains are highlighted in bold colored text.  If a peptide is selected in the Peptide View, it is highlighted in red.

 If a peptide of interest contains post translational modifications (as in this case Ser-348 phosphorylation) you can see the modified amino acid bold and underlined in the Peptide view.  You can also hover over the peptide and Skyline will present more information in a tip, including the delta-mass of each modification specified in brackets in a field labeled “Modified”.

The MS/MS spectrum is interactive and one can zoom into the spectrum, using the mouse scroll wheel or by clicking and dragging a box around a region of interest, to see further fragmentation details.

In the above case of MS/MS for GSLAS348LDSLR [344, 353], zooming in clearly shows that Ser-348 is phoshorylated, and that there is no site ambiguity as the y5 ion and the y6/y6-98 ions clearly determine the position of the phospho group on Ser-348.

If there is phosphorylation site ambiguity, and the PTM site is indistinguishable, Skyline can be used to simulate both peptide isoforms and to easily indicate site ambiguity:

Such as the peptide

R.GEPNVSYICSR.Y [272, 282], phosphorylation simulated at Ser-277  

and the isoform

R.GEPNVSYICSR.Y [272, 282], phosphorylation simulated at Ser-281

In the Skyline document shown below, both isoforms have a pink triangle in the upper right corner of the peptide label.  This triangle indicates an annotation on the peptide.

To view the peptide annotation, right-click on the peptide sequence in the Peptide View and click Edit Node to view a form like the one displayed below.  (In version 1.2 and later, these annotations are shown in the peptide details tip mentioned above, and also by themselves if you hover the mouse over the colored triangle.)

Skyline Custom Annotation can be used to indicate the site ambiguity as demonstrated above with the “TRUE/FALSE” check mark within the peptide note.  These Annotations can easily be exported into custom Skyline reports (csv files).  For more information on annotations and reports, consult the Skyline Custom Reports & Results Grid tutorial.

Publishing a Skyline document for MS/MS spectrum viewing as part of manuscript submission allows the reader to interactively view MS/MS spectra.  Skyline can help with assessment of site ambiguity and allow you to indicate, using custom annotation, cases where site ambiguity of PTMs exists.

These Skyline spectral libraries can be further used to design targeted assays and may provide a valuable resource for researchers interested in a certain data set.

For manuscript submission, Skyline spectral libraries can easily be generated from many common peptide identification search engine outputs, for further details see the Skyline Spectral Library Explorer tutorial. 




Share Skyline Documents in Manuscripts


Skyline documents provide the ideal way to share targeted proteomics methods and results as supplementary material in your manuscripts.

Skyline has the following advantages available in no other targeted proteomics software:

  • Open source
  • Freely available and easy to install
  • Able to produce transition lists for and import results from the triple quadrupole instruments of
    • AB Sciex
    • Agilent Techonologies
    • Thermo Scientific
    • Waters
  • Human readable XML document format
  • Compact, high-performance, easily shared data cache file format

Once you have created a Skyline document (.sky) and its companion data cache file (.skyd), your entire method and acquired results can be easily shared with the proteomics community.  You are guaranteed that others will have freely available and rich access to your method design and results data.

To create a sharable ZIP file that includes:

  • Skyline document (.sky)
  • Skyline data cache file (.skyd)
  • Skyline display information (.sky.view)
  • Either all used spectral libraries or the fraction used by the document (.blib & .redundant.blib)
  • The backgound proteome file (.protdb - optional)

Simply perform the following steps in Skyline:

  • On the File menu, click Share.
  • If the document uses spectral libraries or a background proteome:
    • Click the Minimal button to share only the library spectra used in your document.
    • Click the Complete button to share the libraries and background proteome files as they exist on your system.
  • Enter the file name of your choice in the File name field (or accept the default).
  • Click the Save button.

You now have a compact file that can be shared publicly or upon request with any manuscript in which your methods and data are included.

Your readers will have open access to:

  • View your methods and data in Skyline's rich visual environment
  • Export transition lists for their own instruments
  • Export custom reports for deeper analysis of your data

You can also share the report template(s) you found most useful in analyzing your data by doing the following:

  • On the File menu, choose Export, and click Report.
  • Click the Share button.
  • Check the checkboxes beside the names of the reports you wish to share.
  • Click the OK button.
  • Enter the file name of your choice in the File name field.
  • Click the Save button.

The resulting Skyline report template file (.skyr) can also be shared with your manuscript along with R scripts to make it easy for readers to repeat your analysis on the systems in their labs, with their own samples.

Skyline helps you give the proteomics cummunity full, open access to your methods and results.




Export SRM Methods for a Thermo LTQ


You may know that Skyline documents can be exported to MRM/SRM transition lists for all of the major triple quadrupole instruments available today.  You may even know that Skyline documents can be exported directly to native methods for some of these instruments.  But, Skyline can also export SRM method files for the Thermo-Scientific LTQ.

An ion trap instrument like the LTQ may not have the sensitivity of a triple quadrupole, but you can still use one for targeted proteomics, and you can use SRM on the LTQ as a quality control measure for your liquid chromatography.

While you can export an existing Skyline document to a native LTQ method for SRM, you should be aware of a couple settings before you do.  To prepare your document for use with the LTQ, perform the following steps:

  • On the Settings menu, click Transition Settings.
  • Click the Instrument tab.
  • Check Dynamic min product m/z.
  • Enter the correct value (e.g. 2000) for your instrument into the Max m/z field.
  • Click the OK button.

The first setting will restrict the product m/z values Skyline will allow to being greater than a dynamic minimum, based on the precursor m/z, consistent with the limits the LTQ imposes.  The second setting will restrict both the precursor and product m/z values Skyline allows to be consistent with what your LTQ is calibrated to allow.

If you have done this on an existing document, you should probably review your transitions to be sure Skyline has not removed anything important.  Small product ions may no longer be measurable on the LTQ, which could cause some precursors to contain fewer transitions than you want for your experiment.

If this is a new document, you can now enter the peptides you are interested in targeting as you would normally, understanding that some smaller product ions that you would normally see will no longer be available in the Skyline user interface.

When you are ready to export a LTQ method file for your Skyline document, you must transfer your Skyline document to the instrument control computer for your LTQ instrument, where you will also need to have Skyline installed.  If you are using a complex document involving spectral libraries, you may want to consider using the Share command on the File menu, as described in the tip on Sharing Skyline Documents in Manuscripts.

Once you have your Skyline document open on the LTQ instrument control computer, you are ready to export it to a native LTQ method or .meth file.  To do this, preform the following steps:

  • On the File menu, choose Export, and click Method.
  • Choose 'Thermo LTQ' from the Instrument type list.
  • Click the Browse button beside the Template file field.
  • Browse to a .meth file you will use as a template for all settings other than the m/z values to monitor.
  • Click the Open button in the Method Template form.
  • Choose options in the rest of the Export Method form as you would for exporting a transition list or a TSQ native method.
  • Click the OK button.
  • Enter a name for your method, or root name if creating multiple methods.
  • Click the Save button.
This will create a LTQ method or multiple methods which you can use to make SRM measurements on your LTQ.  Once these are complete, you can import the resulting Thermo .RAW files as you would .RAW files from a TSQ triple quadrupole instrument.

Using SRM for Liquid Chromotography Quality Control on the LTQ

Issues with chromatography can easily go unnoticed on systems performing predominantly shotgun data dependent analysis (DDA).  They can, however, still greatly effect performance, especially if you are hoping to use tools that analyze MS1 scan data for quantification and feature detection.  At the MacCoss lab, we are using SRM methods generated with Skyline to monitor LTQ system performance.  Every tenth run on our LTQ instruments, we inject a known standard mix and measure its abundant peptides using SRM.  We find that measured retention times and peak shapes of known peptides give us increased visibility into system performance of the LTQ.

At present we are injecting the "6 Bovine Tryptic Digest Equal Molar Mix PTD/00001/63" from Michrom Bioresources, Inc., running SRM methods generated with this Skyline document:

Bovine_Mix_QC.sky

Below are examples of Skyline displaying both failing and passing runs on our LTQ Velos. Each QC replicate displayed in Skyline was taken as every tenth injection with the other 9 injections used for normal shotgun MS/MS measurement.

Failing:
In the QC runs shown below, chromatography issues first appear between runs 9 and 12. By QC13, the system is clearly not functioning acceptably.

Passing: In the 33 QC runs shown below, both a retention time drift of about 2 minutes and decreasing intensity are visible, but measurements remain within an acceptable range throughout.




Skyline Source Code


The Skyline project is developed in open source, under Apache 2.0 License, though released under a modified Apache 2.0 License, due to the inclusion of third party libraries with licensing restrictions.

The source code for Skyline is made available through the ProteoWizard GitHub Repository. The main Skyline project can be found under:

pwiz_tools/Skyline




Documentation


Most of the existing Skyline user documentation can be found in the Videos, Tutorials and Tips sections.  Here, however, are a few documents which do not fit into those categories, but still provide useful information on advanced topics in using Skyline for targeted proteomics data analysis:




Users Meetings


Since 2012, the Skyline team has been holding an annual User Group Meeting the Sunday before the annual ASMS conference.  Made possible by the generosity of our vendor sponsors, the User Group Meeting has showcased the creative and innovative ways that Skyline has been used in mass spectrometry research.  

To view a recording from a talk during a past Skyline User Group Meeting, select from one of the years below and then chose a speaker.  The session recording (if available) and presentation slides will appear below the abstract for the talk. 

2018 - San Diego

2017 - Indianapolis

2016 - San Antonio

2015 - St. Louis

2014 - Baltimore

2013 - Minneapolis

2012 - Vancouver




Publications


If you use Skyline in your experiments, please cite our Bioinformatics 2010 Application Note, listed below.
If you use Skyline for calibrated quantification, please cite our Clinical Chemistry 2017 Letter, listed below.
If you use Skyline MS1 filtering, please cite our Mollecular Cellular Proteomics 2012 paper, listed below.
If you use Skyline for collision energy optimization, please cite our Analytical Chemistry 2010 paper, listed below.

Peer reviewed manuscripts:

  • MacLean, Bioinformatics 2010 article (cited by 1754)
    Skyline: An Open Source Document Editor for Creating and Analyzing Targeted Proteomics Experiments
    [abstract][pdf]
  • Henderson, Clinical Chemistry 2017 letter
    Skyline Performs as Well as Vendor Software in the Quantitative Analysis of Serum 25-Hydroxy Vitamin D and Vitamin D Binding Globulin
    [abstract][pdf]
  • Pino, Mass Spectrometry Reviews 2017 article (cited by  15)
    The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics
    [abstract]
  • Bereman, Journal of Proteome Research 2016 article (cited by 13)
    An Automated Pipeline to Monitor System Performance in Liquid Chromatography Tandem Mass Spectrometry Proteomic Experiments
    [abstract][pdf]
  • Sharma, Journal of Proteome Research 2014 article (cited by  87)
    Panorama: A Targeted Proteomics Knowledge Base
    [abstract][pdf]
  • Sharma, Mollecular & Cellular Proteomics 2018 article
    Panorama Public: A public repository for quantitative data sets processed in Skyline
    [abstract]
  • Broudy, Killeen, Bioinformatics 2014 article (cited by 29)
    A framework for installable external tools in Skyline
    [abstract]
  • Schilling, Analytical Chemistry 2015 article (cited by 41)
    Multiplexed, Scheduled, High-Resolution Parallel Reaction Monitoring on a Full Scan QqTOF Instrument with Integrated Data-Dependent and Targeted Mass Spectrometric Workflows.
    [abstract]
  • Egertson, Nature Protocols 2015 article (cited by 77)
    Multiplexed peptide analysis using data-independent acquisition and Skyline
    [abstract]
  • Abbatiello, Mollecular Cellular Proteomics 2015 article (cited by 97)
    Large-scale inter-laboratory study to develop, analytically validate and apply highly multiplexed, quantitative peptide assays to measure cancer-relevant proteins in plasma
    [abstract]
  • Egertson, Nature Methods 2013 article (cited by 177)
    Multiplexed MS/MS for improved data-independent acquisition
    [abstract]
  • Abbatiello, Mollecular Cellular Proteomics 2013 article (cited by 97)
    Design, Implementation, and Multi-Site Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in LC-MRM-MS
    [abstract]
  • Schilling, Mollecular Cellular Proteomics 2012 article (cited by 240)
    Platform independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in Skyline. Application to protein acetylation and phosphorylation
    [abstract]
  • Choi, Journal of Proteome Research 2017 article (cited by 8)
    ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC-MS/MS Experiments.
    [abstract]
  • Sherrod, Journal of Proteome Research 2012 article (cited by 52)
    Label-Free Quantitation of Protein Modifications by Pseudo-Selected Reaction Monitoring with Internal Reference Peptides
    [abstract]
  • Escher, Proteomics 2012 article (cited by 220)
    Using iRT, a normalized retention time for more targeted measurement of peptides
    [abstract]
  • Bereman, Proteomics 2012 article (cited by 65)
    The development of selected reaction monitoring methods for targeted proteomics via empirical refinement
    [abstract]
  • Stergachis, Nature Methods 2011 article (cited by 105)
    Rapid empirical discovery of optimal peptides for targeted proteomics
    [abstract]
  • MacLean, Analytical Chemistry 2010 article (cited by 172)
    Effect of Collision Energy Optimization on the Measurement of Peptides by Selected Reaction Monitoring (SRM) Mass Spectrometry
    [abstract]
  • Prakash, Journal of Proteome Research 2009 article (cited by  150)
    Expediting the Development of Targeted SRM Assays: Using Data from Shotgun Proteomics to Automate Method Development
    [abstract]

Presentations and posters:

  • Pratt, ASMS 2017 Poster
    Recent Advances in Skyline: Further Improvements in Small Molecule Targets and Ion Mobility
    [pdf
  • Pratt, ASMS 2015 Poster
    Recent Advances in Skyline: Small Molecule Targets and Ion Mobility Filtering
    [pdf]
  • Thompson, MSACL 2015 Poster
    Skyline for small molecules: a flexible tool for cross-platform LC-MS/MS method creation and data analysis for metabolomics
    [pdf]
  • MacLean, ASMS 2014 Presentation
    Rapid Processing of Large Scale Quantitative Proteomics Projects: Integration of Skyline with the CHORUS Cloud
    [pdf]
  • Amodei, ASMS 2014 Poster
    A multi-site, Skyline-based comparison of DIA peptide detection and statistical confidence tools
    [pdf]
  • MacLean, ASMS 2013 Poster
    Integration of mProphet chromatogram peak identification probability model into Skyline
    [pdf]
  • Amodei, ASMS 2013 Poster
    An Instrument-Independent Demultiplexing Method for Computationally Improving the Specificity of Data-Independent Acquisition
    [pdf]
  • Eckels, ASMS 2013 Poster
    Sharing targeted proteomics assays using Skyline and Panorama
    [pdf]
  • MacLean, ASMS 2012 Presentation
    Targeted Proteomics Quantitative Analysis of Data Independent Acquisition MS/MS in Skyline
    [pdf] [PowerPoint] [video]
  • Sharma, ASMS 2012 Poster
    Panorama: A private repository of targeted proteomics assays for Skyline
    [pdf]
  • Egertson, ASMS 2012 Poster
    Multiplexed Data Independent Acquisition for Comparative Proteomics
    [pdf]
  • MacLean, ASMS 2011 Poster
    Skyline: Targeted Proteomics with Extracted Ion Chromatograms from Full-Scan Mass Spectra
    [pdf]
  • Tomazela, ASMS 2011 Poster
    Developing system suitability criteria and evaluation methods for proteomics experiments
    [pdf]
  • MacLean, ASMS 2010 Presentation
    Skyline: Sharing SRM/MRM Method Creation and Results Analysis Across Laboratories and Instrument Platforms
    [pdf]
  • Tomazela, ASMS 2010 Poster
    Effect of Collision Energy Optimization on the Measurement of Peptides by Selected Reaction Monitoring (SRM) Mass Spectrometry
    [pdf]
  • MacLean, ASMS 2009 Poster
    Automated Creation and Refinement of Complex Scheduled SRM Methods for Targeted Proteomics
    [pdf]

Invited reviews:

  • US HUPO News 2011 TechTalk - Skyline: A Bridge Between Discovery and Targeted Proteomics
    [article]



ASMS 2012 WOA am MacLean Presentation


Watch the video recording of Brendan MacLean's ASMS 2012 presentation Targeted Proteomics Quantitative Analysis of Data Independent Acquisition MS/MS in Skyline

The Camtasia Studio video content presented here requires JavaScript to be enabled and the latest version of the Adobe Flash Player. If you are using a browser with JavaScript disabled please enable it now. Otherwise, please update your version of the free Adobe Flash Player by downloading here.




Press


 

  • Journal of the American Society for Mass Spectrometry (Volume 27, Number 11) lead front page story about Michael MacCoss receiving the 2015 ASMS Biemann Award from his work in bioinformatics and software for "omics" researchers (Skyline and Panorama). 
    [html] [cover pdf]
  • NCI eProtein feature
    Viewing the Targeted Proteomics Horizon with Skyline
    [html]
  • Nature Methods chooses targeted proteomics as Method of the Year in 2012
    Targeted proteomics
    [html]
  • NCI eProtein feature
    Open Source Software Tool Skyline Reaches Key Agreement with Mass Spectrometer Vendors
    [html]
  • PROTEOMICS article
    Free computational resources for designing selected reaction monitoring transitions
    [abstract]
  • Q-MOP Symposium review
    Quantitative proteomics: A central technology for systems biology
    [html]
  • NCI eProtein spotlight
    Skyline: Building a Bigger Net for Targeted Proteomics
    [pdf]



Awards


2016

  • Mike wins HUPO award Professor Mike MacCoss awarded the HUPO Discovery in Proteomic Sciences Award for his developments in methodology and software for the quantitative analysis of complex protein mixtures. The focus of his lab is the development of high-throughput quantitative proteomic methods and their application to model organisms. To enable this research, Mike and his research team have developed a software program Skyline -- a free, openly available software package for the design and interpretation of targeted proteomics experiments -- which as had a remarkable impact and is widely adopted within the proteomics community. This has placed Mike as a leader in the field of quantitative proteomics. [pdf]

  • Brendan MacLean wins inaugural Gilbert S. Omenn Computational Proteomics Award - In 2016, US HUPO announced the Gilbert S. Omenn Award for computational proteomics and the first recipient was no other than the MacCoss Lab's own Skyline Principal Developer, Brendan MacLean. The Omenn award recognizes the specific achievements of scientists that have developed bioinformatics, computational, statistical methods and/or software used by the proteomics community.

2015

  • Dr. Mike MacCoss wins ASMS Biemann Award for 2015 Professor Michael MacCoss received the 2015 American Society for Mass Spectrometry (ASMS) Biemann Award, in part, from the creation of software for "omics" researchers.  In their award announcement, ASMS cited Mike's philosophy on making high quality, freely available software -- Skyline and Panorama -- and providing for their long term support. This has enables many others to greatly benefit and has advanced the field of proteomic sciences, ASMS stated. 
    [html]



License Agreement


ADDENDUM TO APACHE LICENSE

To the best of our ability we deliver this software to you under the Apache 2.0 License listed below (the source code is available in the ProteoWizard project).  This software does, however, depend on other software libraries which place further restrictions on its use and redistribution.  By accepting the license terms for this software, you agree to comply with the restrictions imposed on you by the license agreements of the software libraries on which it depends:

AB SCIEX WIFF File Reader Library
Agilent Mass Hunter Data Access Component Library
ALGLIB numerical analysis and data processing library
Shimadzu QQQ Data Reader Library
Thermo-Scientific MSFileReader Library
Waters Raw Data Access Component Library
Mascot Parser
 
NOTE:  If you do not plan to redistribute this software yourself, then you are the "end-user" in the above agreements.

 

Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
 

TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

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END OF TERMS AND CONDITIONS




Other


Other topics that may be of interest:




How You Can Help


At the MacCoss Lab, we believe that a strong community around an open source software project can produce world-class software.  Examples abound: Firefox, Linux and projects of the Apache Software Foundation.  We are working hard to see Skyline and its parent project, ProteoWizard, live up to the standard set by these examples.  Already our efforts have been greatly aided by others inspired by our initial work.  We encourage anyone who feels they benefit from the Skyline project to consider helping improve and sustain it in any of the following ways:

  1. Sign up as a registered user of the software to help us prove the broad appeal of our software and keep development and support funded.
  2. Post a statement explaining how your work has benefitted from using Skyline to encourage further growth in the project community.
  3. Publish or present your targeted proteomics work citing the Skyline manuscript, using Skyline graphs in your figures, and/or making your Skyline documents publicly available.
  4. Help a friend or collaborator get started using Skyline.
  5. Post to the support board your questions and comments.
  6. Take the time to work through an issue with the Skyline team and explain how the software might be improved to avoid others encountering it.
  7. Contribute a tutorial or tip.  Follow the example of existing tutorials and tips, and explain how to use features that are important to you.
  8. Contribute development time to the open source project, if you are a programmer.

Join the growing community of contributors that have helped to make Skyline what it is today.




Get Involved


Jobs
The Skyline jobs board helps employers and job seekers interested in Skyline, Panorama and targeted mass spectrometry connect.

Contribute
Make a tax-deductible contribution to the Skyline project this year through the University of Washington Foundation

Comment
See what the community is saying about Skyline - and add your statement!

Share
Other ways you can help




3rd-Party Software


Software Support: 

The following organizations have made crucial software contributions to the Skyline project.

SCIEXAgilent Technologies
Shimadzu
Thermo ScientificWaters
 
The Most Intelligent Add-In To Visual Studio
A cross-platform numerical analysis and data processing librarySubversion plug-in for Visual Studio



Related


Dashboard
Skyline adoption and use information

Panorama
Create a new project for your lab or group on PanoramaWeb hosted by the University of Washington

ProteoWizard
Skyline source code is available under Apache 2.0 License and part of the ProteoWizard project (mzML and mzXML conversion)

Spectral Library Links
PeptideAtlas
NIST
GPM




Funding


Current Financial Support:

Title: Skyline Targeted Proteomics Environment
R01 GM103551 (PI: MacCoss) 9/14/2011 – 8/31/2020
The grant provides support for the continued development and maintenance of the widely used Skyline targeted proteomics software tool.

Title:There and Back Again: Epigenetic Reinforcement of Cellular Signaling States
U54 HG008097 (MPI: Jaffe); 7/1/2014 – 6/30/2020
This is a LINCS program grant to derive molecular signatures resultant from cellular perturbation.  We will develop a repository to disseminate multiplex mass spectrometry based assays via the Skyline client for use on all major mass spectrometry vendors.

Title: Comprehensive Biology: Exploiting the Yeast Genome
P41 GM103533 (PI: Davis)                                                                9/1/2011 – 12/31/2016
This is a biotechnology resource center.  Dr. MacCoss’ role in the center is to develop quantitative mass spectrometry based technology for the measurement of protein dynamics.  This center will support training in the use of Skyline to the proteomics community. Furthermore, it supports the development of a webservices interface to access data within the Yeast Resource Center public data repository via Skyline.

Title: Self Correcting Nanoflow LC-MS for Clinical Proteomics
R01 GM107806 (PI: MacCoss)                                                            7/1/13 – 4/30/2017
The primary goal of this project is to improve the quality, reliability, and interlaboratory comparability of peptide mass spectrometry data. We are adding quality control capabilities to the Skyline software tool.  Furthermore, we are improving the interaction of Skyline with the instrument hardware and chromatography system.

Title: Support of Agilent Mass Spectrometers within the Skyline and Panorama Software Projects
Industry Gift from Agilent (PI: MacCoss)           5/1/2012 – 12/31/2019
We are continuing to extend our analytical software tools to support Agilent mass spectrometers.

Title: Support of Bruker Mass Spectrometers within the Skyline and Panorama Software Projects
Software Engineering Contract from Bruker (PI: MacCoss)           8/1/2012 – 1/31/2019
We are continuing to extend our analytical software tools to support Bruker mass spectrometers.

Title: Support of SCIEX Mass Spectrometers within the Skyline and Panorama Software Projects
Software Engineering Contract from SCIEX (PI: MacCoss)           1/1/2015 – 12/31/2018
We are continuing to extend our analytical software tools to support SCIEX mass spectrometers.

Title: Support of Shimadzu Mass Spectrometers within the Skyline and Panorama Software Projects
Software Engineering Contract from Shimadzu (PI: MacCoss)           1/15/2014 – 1/14/2019
We are continuing to extend our analytical software tools to support Shimadzu triple quadrupole mass spectrometers.

Title: Support of Thermo Fisher Mass Spectrometers within the Skyline and Panorama Software Projects
Software Engineering Contract from Thermo Fisher (PI: MacCoss)           3/14/2014 – 3/13/2019
We are continuing to extend our analytical software tools to support Thermo Fisher mass spectrometers.

Title: Support of Waters Mass Spectrometers within the Skyline and Panorama Software Projects
Software Engineering Contract from Waters (PI: MacCoss)           9/1/2013 – 12/31/2021
We are continuing to extend our analytical software tools to support Waters mass spectrometers.

Prior Financial Support:

Title: Data Acquisition and Analysis Strategies for Improving the Analysis of Peptide Mixtures Using Thermo Fisher Mass Spectrometers
Industry Sponsored Research Agreement (PI: MacCoss)           6/15/2010 – 6/15/2014
We are developing methods of analyzing mass spectrometry data on ThermoFisher mass spectrometers and Pierce reagents using Skyline.  This agreement is renewed yearly and we expect that the funding will be extended.

Title: Validating Protein Pathway Information – Integrating Proteomic Data with Transcriptomic or Metabolomic Data Sets
Industry Gift (PI: MacCoss)                                                              10/1/2011 - 9/31/2012
We are improving the interface between Agilent’s popular expression analysis software GeneSpring GX and Skyline.

Title: Genetic Regulation of Surfactant Deficiency
R01 HL082747 (PI: Cole  PI Subcontract: MacCoss)                        5/1/2011 – 3/31/2012
Goal was to understand the genetic and molecular mechanisms that disrupt pulmonary surfactant metabolism.  This project has supported the development of software and methodology for establishing targeted protein assays for Surfactant Protein-B.

Title: Label Free Differential Protein Analysis
University of Pittsburgh Contract                                                  7/1/2011 – 9/15/2011
Bridging funding to support the addition of label free MS1 quantitative analysis capabilities within Skyline.

Title: Clinical Proteomic Technology Assessment for Cancer (CPTAC)
U24 CA126479-S2 (PI: Liebler  PI Subcontract: MacCoss)               8/1/2009 – 7/31/2011
Funding provided to develop software to support the CPTAC centers for targeted proteomics method development and data analysis.




Dashboard


Learn more about the adoption and growth of Skyline use for targeted proteomics around the world.

View the Skyline 500 Report to see how the cities of the world rank for visits to the Skyline web site. The Skyline web site has seen over 39,000 users over the past 6 months, only 41.5% of which came from the United States

Skyline 500

There have been over 89,000 new installations of Skyline since it was first publicly released at ASMS 2009, with 1000 installations on average each month over the past 6 months.

Skyline Installations
* - Individuals may have installed more than once or to multiple computers in this time

 

Skyline version 4.1 released to record interest (over 15,000 instances in 7 days).

Skyline Current Use
* - Individuals may start multiple instances of Skyline in a day or use a single instance for longer than a week




Team


The following team members have made invaluable, direct contributions to the effort to build Skyline:


Brendan MacLean Brendan MacLean - principal developer
Brendan worked at Microsoft for 8 years in the 1990s where he was a lead developer and development manager for the Visual C++/Developer Studio Project. Since leaving Microsoft, Brendan has been the Vice President of Engineering for Westside Corporation, Director of Engineering for BEA Systems, Inc., Sr. Software Engineer at the Fred Hutchinson Cancer Research Center, and a founding partner of LabKey Software. In this last position he was one of the key programmers responsible for the Computational Proteomics Analysis System (CPAS), made significant contributions to the development of X!Tandem and the Trans Proteomic Pipeline, and created the LabKey Enterprise Pipeline. Since August, 2008 he has worked as a Sr. Software Engineer within the MacCoss lab and been responsible for all aspects of design, development and support in creating the Skyline Targeted Mass Spec Environment and its growing worldwide user community.

Mike MacCoss Michael J. MacCoss, Ph.D. - principal scientist
Mike became interested in biomedical applications of mass spectrometry while working in Dr. Patrick Griffin’s protein mass spectrometry lab at Merck Research Laboratories. He obtained a Ph.D. with Professor Dwight Matthews and pursued a postdoc with Professor John R. Yates III. In 2004 he started the MacCoss lab at the University of Washington and it became obvious that while mass spectrometry data could be collected quickly and robustly, the lack of computational tools for the visualization and analysis of these data was a stumbling block. In 2008 he hired Brendan MacLean with the goal of developing professional quality software tools for quantitative proteomics. Mike has worked closely with the Skyline development team and our outstanding group of laboratory scientists and collaborators to ensure that our software uses analytical approaches that have been thoroughly vetted by the mass spectrometry community.
Josh Aldrich Josh Aldrich development
Josh began working in mass spectrometry (proteomics) starting in 2010 as a Research Associate at Pacific Northwest National Laboratory under Liljana Pasa-Tolic. Here he developed software aiding identification and post translational modification site detection as well as developing pipelines to aid in large scale reproducible data analysis. Following this he joined Amazon, building backend and frontend software for what eventually became Amazon:Go, the cashierless grocery store. Now he has returned to the field of proteomics on the Skyline team to help the team grow into the cloud in addition to other work.


Yuval Boss Yuval Boss (University of Washington) - development
Yuval has worked on the Skyline team since leaving high school in 2013 on and off with breaks for rock climbing and salmon fishing in Alaska. He has been responsible for features in Panorama and Skyline, the Skyline tool store, several external tools and the Skyline nightly test results module tracking over 1 million tests run on Skyline each week. He is now also pursuing an undergraduate degree in CS at the University of Washington.
 

Nat Brace - project manager - outreach & user education
Nat worked full-time for Microsoft from 1991 through 2000 where he led a team of system engineers who were helping organizations plan for and integrate Microsoft’s advanced server solutions including network and database products, as well as software development tools. He continued at Microsoft as a consultant from 2000 to 2011, with several internal teams as a technical project owner, customer outreach lead and marketing manager. More recently, Nat joined a social innovation start-up piloting a global educational reform initiative where he served as the lead project manager in delivering a collaboration platform for use by the initiative’s participating educators, researchers and sponsors. As project manager for the Skyline team, Nat is responsible for outreach programs, like webinars, courses and user meetings, foreign language translation, and instrument vendor interactions.

Matthew Chambers Matthew Chambers - development (ProteoWizard)
Matt has worked in mass spectrometry informatics (mostly proteomics) since 2005; the first ten years he worked for David Tabb and Bing Zhang at Vanderbilt University Medical Center, and since then he has continued working as an independent consultant. He has worked in many subfields within MS, including shotgun proteomics database search, sequence tagging, spectral library search, and protein assembly. Along with Darren Kessner (director: Parag Mallick), Matt developed ProteoWizard, a free open-source library for mass spectrometry data processing. Since 2009, he has been its principal developer. The ProteoWizard tool msconvert is widely used for converting mass spectrometry data by users all over the world. For Skyline, he has focused on being able to read data directly from vendor proprietary data formats.
Rita Chupalov Rita Chupalov development
Rita’s experience with software and computers goes back to a Russian clone of DEC’s PDP-11 in 1991. She finished her degree in Organic Chemistry from Saint-Petersburg State University in 1996 where she wrote her first mass-spectrometry software: identification of halogen isotopic multiplets in low-resolution mass-spectra. Since then she worked for multiple software development companies specializing on database-centric applications, analytics and data warehousing. Her most recent job was with Amazon where she learned big data and cloud technologies.

Brian Connolly Brian Connolly - IT
Over the years Brian has worked for a number of companies in the Seattle area including Microsoft, BEA Systems and Cray. In 2007 Brian joined LabKey where he wore a number of hats. He helped LabKey's customers design and operate their LabKey Servers and pipelines. He architected and operated all of LabKey's Servers running in the public cloud (AWS and other cloud vendors) and became an expert in FISMA and HIPAA regulations. As part of the Skyline Team, Brian is responsible for managing growth of the PanoramaWeb.org and Skyline.ms servers and helping the team grow its use of the AWS cloud.
Brian Pratt Brian Pratt - development, support
Brian's love affair with computing started the day he and his dad unboxed that brand new Apple II. Since then he's been involved with software development for, and started a couple of companies around, such varied applications as robot-assisted surgery, circuit board manufacturing and test, internet firewalls, and proteomics. Brian's proteomics work prior to joining the Skyline team included contributions to TPP, X!Tandem, LabKey's CPAS, and ProteoWizard. He's excited to be on a team of software professionals that value performance, reliability, and usability in the support of science.
Tobias Rohde Tobias Rohde (University of Washington) - development intern
Tobias is currently a student at the University of Washington. He joined the Skyline team after graduating Roosevelt High School in 2017 and quickly developed an interest for proteomics and mass spectrometry. Tobias primarily works on graph related features and among other things has been responsible for the group comparison volcano plot and the peak area CV histogram graphs.
Birgit Schilling Birgit Schilling, Ph.D. (Buck Institute for Research on Aging) - software design, data acquisition, scientific consulting, documentation
Birgit joined the Chemistry Core and Mass Spectrometry Laboratory at the Buck Institute for Research of Aging in Novato, CA in 2000 and is now director of that department. Research projects include investigations of neurodegenerative diseases, cancer, mitochondrial damage, protein oxidative posttranslational modifications, the role of surface glycoconjugates in bacterial pathogenesis etc., but also mass spectrometric method development. Birgit is interested in oxidative damage of proteins, protein phosphorylation, glycosylation, acetylation, and other posttranslational modifications, as well as differential expression of proteins during disease and aging processes. In recent years Birgit worked extensively in the field of protein quantitation to assess differential protein expression, particularly using multiple reaction monitoring stable isotope dilution mass spectrometry (MRM-SID-MS), and other chemical labeling quantitative workflows (i.e., iTRAQ and SILAC), however she also used label free protein/peptide quantitation approaches to investigate discovery mass spectrometric data sets (based on MS1 intensity).
Vagisha Sharma Vagisha Sharma - development, support, documentation (Panorama)
Vagisha got involved with proteomics at UC San Diego where she worked with Prof. Vineet Bafna. During that time she built her first tools for visualizing Mass Spectrometry data while working at ActivX Biosciences. Since moving to Seattle Vagisha has worked on Mass Spectrometry pipelines for the Aebersold group at the Institute for Systems Biology, and developed a data management system while at the University of Washington Proteomics Resource and the Yeast Resource Center. She joined the Skyline team in October, 2011. Vagisha enjoys developing tools that help researchers get stuff done.

Nicholas Shulman Nicholas Shulman - development, support
Nick worked from 1995-2000 at Microsoft on the Microsoft Access team, leaving to join Westside Corporation with Brendan to create browser-based database design tools. After Westside was acquired by BEA Systems, Nick created a new graphical JSP designer for Weblogic Workshop, an award winning Integrated Development Environment for enterprise Java applications. At LabKey Corporation, Nick created the flow cytometry module and the graphical query designer. Since March, 2009 he has worked in the Maccoss lab on Skyline and Topograph, a quantitative analysis tool for protein turnover experiments.

 

Previous contributors:

  • Susan E. Abbatiello, Ph.D. - software design, data acquisition, scientific consulting (now Thermo Scientific)
  • Dario Amodei - development - Stanford (Baidu, Google, now OpenAI, SF)
  • Eva Baker - development (now UW Med. School)
  • Daniel Broudy - development intern - Harvard (now Google, Seattle)
  • John Chilton - development intern - UW
  • Jarrett Egertson - develpment - UW (MSX and overlapped demux)
  • Gregory Finney, Ph.D. - development - UW (Crawdad)
  • Barbara Frewen - development - UW (BiblioSpec, Thermo BRIMS, now Zymergen)
  • Mimi Fung - development intern - UW (now Microsoft)
  • Max Horowitz-Gelb - development intern - U. Wisconsin (now Google)
  • Shannon Joyner - development intern - CMU (Cisco Meraki, now Cornell)
  • Randall Kern - development architecture consulting (Microsoft, now SalesForce.com)
  • Alana Killeen - development intern - UW (Microsoft, now DropBox)
  • Trevor Killeen - development intern - UW (now Facebook)
  • Alex MacLean - development intern - Roosevelt High School (intern - Microsoft Research)
  • Don Marsh - development (now Whitemarsh Forests)
  • Kaipo Tamura - development (spectral library building and import peptide search wizard)
  • Daniela Tomazela, Ph.D. - software design, data acquisition, scientific consulting (now Merck)
Rita Chupalov