Eveleth, J.
, Moorthy, A.
and Kearsley, A.
(2026),
HDCMS: a package for computing high-dimensional consensus mass spectral similarity scores, Technical Note (NIST TN), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.TN.2331, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959586 (Accessed April 30, 2026)
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HDCMS: a package for computing high-dimensional consensus mass spectral similarity scores
Published
Author(s)
Jason Eveleth, Arun Moorthy,
Abstract
Identification of unknown mass spectra is a fundamental task in analytical chemistry. The unambiguous identification of mass spectra remains a challenge for compounds similar in structure. A novel mathematical approach incorporating measurement variability in replicate mass spectra was proposed in Roberts et al., [1]. The method shows potential in discriminating similar compounds given replicate mass spectra, and has been imple-mented in a software package called HDCMS (high dimensional consensus mass spectra). In this work, we describe the algorithmic considerations underpinning the HDCMS pack-age, including: data preprocessing, constructing HDCMS from replicate measurements, and comparing pairs of HDCMS. We then demonstrate use of the software and summarize the performance on two lab collected data sets.Citation
Technical Note (NIST TN) - 2331
Report Number
2331
NIST Pub Series
Pub Type
NIST Pubs
Download Paper
Keywords
C programming language, Cheminformatics, Mass spectrometry, Python, Similarity scores
Citation
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Created April 29, 2026