NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.

Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.

U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

PUBLICATIONS

compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets

Published

Author(s)

Rob Marissen, Jeroen Laros, Josef Rasinger, Madhushri Varunjikar, Ben Neely, Magnus Palmblad

Abstract

It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.
Citation
ACS Journal of Proteome Research
Pub Type
Journals

Download Paper

https://doi.org/10.1021/acs.jproteome.2c00457
Local Download

Keywords

compareMS2, distance metric, molecular phylogenetics, quality control, spectral clustering, distance metric, tandem mass spectrometry
Proteomics and Bioscience

Citation

Marissen, R. , Laros, J. , Rasinger, J. , Varunjikar, M. , Neely, B. and Palmblad, M. (2022), compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets, ACS Journal of Proteome Research, [online], https://doi.org/10.1021/acs.jproteome.2c00457, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935035 (Accessed October 11, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created September 29, 2022, Updated November 29, 2022
Was this page helpful?