Skip to main content
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.

A scoring metric for multivariate data for reproducibility analysis using chemometric methods



David A. Sheen, Werickson Fortunato de Carvalho Rocha, Katrice A. Lippa, Dan Bearden


Process quality control and reproducibility in emerging measurement fields such as metabolomics is normally assured by interlaboratory comparison testing. As a part of this testing process, spectral features from a spectroscopic method such as nuclear magnetic resonance (NMR) spectroscopy are attributed to particular analytes within a mixture, and it is the metabolite concentrations that are returned for comparison between laboratories. However, data quality may also be assessed directly by using binned spectral data before the time-consuming identification and quantification. Use of the binned spectra has some advantages, including preserving information about trace constituents and enabling identification of process difficulties. In this paper, we demonstrate the use of binned NMR spectra to conduct a detailed interlaboratory comparison and composition analysis. Spectra of synthetic and biologically- obtained metabolite mixtures, taken from a previous interlaboratory study, are compared with cluster analysis using a variety of distance and entropy metrics. The individual measurements are then evaluated based on where they fall within their clusters, and a laboratory-level scoring metric is developed, which provides an assessment of each laboratory’s individual performance.
Chemometrics and Intelligent Laboratory Systems


Nuclear magnetic resonance, metabolomics, interlaboratory comparison


Sheen, D. , Fortunato, W. , Lippa, K. and Bearden, D. (2016), A scoring metric for multivariate data for reproducibility analysis using chemometric methods, Chemometrics and Intelligent Laboratory Systems, [online], (Accessed July 23, 2024)


If you have any questions about this publication or are having problems accessing it, please contact

Created December 23, 2016, Updated November 10, 2018