MS Amanda

MS Amanda is a scoring system to identify peptides out of tandem mass spectrometry data using a database of known proteins.

About

This algorithm is especially designed for high resolution and high accuracy tandem mass spectra. One advantage of MS Amanda is the high speed of spectrum identification, especially since MS Amanda 2.0. In addition, MS Amanda is also very accurate, as we observe a high overlap of identified spectra with gold-standard algorithms Mascot and SEQUEST.
To cite MS Amanda and for more detailed information on the algorithm please refer to Dorfer et al. J Proteome Res. 2014, 13(8):3679-84 (see bibtex) and Dorfer et al. Rapid Commun Mass Spectrom. 2021, 35(11).

Installation of MS Amanda 2.0 for Proteome Discoverer 2.1-2.5 and 3.0, and MS Amanda 3.0 for PD 3.1

We have developed a new, significantly faster version of our MS Amanda algorithm: MS Amanda 2.0.

The Proteome Discoverer Node of MS Amanda 2.0 can be used with Thermo Scientific Proteome Discoverer. To install MS Amanda 2.0, please perform the following steps:

  1. Close Proteome Discoverer
  2. Please download the latest installer here:
  3. Follow the installation instructions and carefully read the license agreement
  4. Restart Proteome Discoverer

MS Amanda 2.0/3.0 should now be successfully installed on your computer.
Attention: this is the new version of MS Amanda, your old MS Amanda workflows will not work with this version! If you want to use your old workflows, please install MS Amanda 1.0 available within the PD Nodes Collection.

Installation of MS Amanda 3.0 Standalone

MS Amanda 3.0 Standalone can be used from the command line or called from any already established proteomics pipelines.

To install MS Amanda 3.0 please perform the following steps:

  1. Carefully read the license agreement and proceed only if you agree to the terms and conditions.
  2. Please download the latest version for Windows, Linux, and Mac here:

  3. Please check our google group for further information about latest changes.
  4. Windows:
    • Right click on the downloaded .zip file and select the menu item "Properties" in the context menu.
    • If visible, click "Unblock" at the bottom right of the Properties window.
    • Click "OK" to close the Properties window.
    • Extract the downloaded .zip file.
    • Open a commandline and navigate to the extracted MS Amanda folder.
    • Run MS Amanda by calling:
      "MSAmanda.exe -s spectrumFile -d proteinDatabase -e settings.xml [-f fileformat] [-o outputfilename]"
  5. Linux:
    • The new version of MS Amanda no longer requires mono
    • Extract the MS Amanda archive and navigate to the extracted folder in a terminal.
    • MS Amanda for linux can be used the same way as on windows platforms.
      To run MS Amanda please call:
      "./MSAmanda -s spectrumFile -d proteinDatabase -e settings.xml [-f fileformat] [-o outputfilename]"
  6. Mac:
    • The new version of MS Amanda no longer requires mono
    • Extract the MS Amanda archive and navigate to the extracted folder in a terminal.
    • MS Amanda for Mac can be used the same way as on windows platforms. To run MS Amanda please call:
      "./MSAmanda -s spectrumFile -d proteinDatabase -e settings.xml [-f fileformat] [-o outputfilename]"

MS Amanda 3.0 Standalone is now ready for use! For detailed documentation please refer to the user manual for MS Amanda Standalone.

In addition, MS Amanda Standalone is also integrated in SearchGUI and PeptideShaker!

A detailed description on how to use MS Amanda for Proteome Discoverer, on the parameters provided by MS Amanda, and how to filter results obtained with MS Amanda can be found in the MS Amanda Manual for PD.

A typical MS Amanda PD workflow can be found here.

Contact

This research project is a collaboration of the Protein Chemistry Group at IMP and the Bioinformatics Research Group at FH Upper Austria, Hagenberg Campus.
For any further questions, bug reports, ideas,... please contact Viktoria Dorfer, Marina Strobl, Stephan Winkler, or Karl Mechtler or post your comment in the MS Amanda Google Group.

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