Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Empirical Factors Affecting the Quality of Non-Negative Matrix Factorization of Mammalian Cell Raman Spectra

Not Accessible

Your library or personal account may give you access

Abstract

Mammalian cells contain various macromolecules that can be investigated non-invasively with Raman spectroscopy. The particular mixture of major macromolecules present in a cell being probed are reflected in the measured Raman spectra. Determining macromolecular identities and estimating their concentrations from these mixture Raman spectra can distinguish cell types and otherwise enable biological research. However, the application of canonical multivariate methods, such as principal component analysis (PCA), to perform spectral unmixing yields mathematical solutions that can be difficult to interpret. Non-negative matrix factorization (NNMF) improves the interpretability of unmixed macromolecular components, but can be difficult to apply because ambiguities produced by overlapping Raman bands permit multiple solutions. Furthermore, theoretically sound methods can be difficult to implement in practice. Here we examined the effects of a number of empirical approaches on the quality of NNMF results. These approaches were evaluated on simulated mammalian cell Raman hyperspectra and the results were used to develop an enhanced procedure for implementing NNMF. We demonstrated the utility of this procedure using a Raman hyperspectral data set measured from human islet cells to recover the spectra of insulin and glucagon. This was compared to the relatively inferior PCA of these data.

© 2017 The Author(s)

PDF Article
More Like This
Application of non-negative matrix factorization to multispectral FLIM data analysis

Paritosh Pande, Brian E. Applegate, and Javier A. Jo
Biomed. Opt. Express 3(9) 2244-2262 (2012)

Study on the chemodrug-induced effect in nasopharyngeal carcinoma cells using laser tweezer Raman spectroscopy

Sufang Qiu, Miaomiao Li, Jun Liu, Xiaochuan Chen, Ting Lin, Yunchao Xu, Yang Chen, Youliang Weng, Yuhui Pan, Shangyuan Feng, Xiandong Lin, Lurong Zhang, and Duo Lin
Biomed. Opt. Express 11(4) 1819-1833 (2020)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved