Posthandling Spectral Information Enhancement for Single Cell Raman Molecular Mapping Analysis
Ankit Raj, Nungnit Wattanavichean, Makoto Kawamukai, Tatsuyuki Yamamoto, Hiro-o Hamaguchi
TL;DR
This paper introduces a new method to improve Raman molecular mapping of single cells by reducing noise and background interference, enabling clearer identification of minor biochemical features.
Contribution
A novel objective data analysis workflow for Raman spectroscopy that enhances minor peak detection and mapping accuracy in single-cell studies.
Findings
The proposed workflow enables precise identification of minor Raman peaks in single-cell molecular maps.
Automated background subtraction improves the accuracy of biochemical component extraction in complex cell environments.
The method allows quantitative analysis of cellular components without subjective interpretation.
Abstract
Biochemical analysis of living systems such as single cells benefits greatly from the label-free and low-invasive molecular mapping with Raman microspectroscopy. Sets of Raman spectra at different spatial points are analyzed to generate Raman molecular maps corresponding to specific chemical species. However, human error and subjective data analysis can be technical issues that limit interpretation and its validity. Here, we present an objective data analysis scheme for postprocessing large data sets of Raman spectra for molecular mapping of living cells. The process comprises three steps: (i) Denoising the spectral data set using low-rank approximation; (ii) obtaining an objective background from data points outside the target cell; (iii) subtracting the thus obtained background using Hypothetical Addition Multivariate Analysis with Numerical Differentiation (HAMAND) via an…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsSpectroscopy Techniques in Biomedical and Chemical Research · Spectroscopy and Chemometric Analyses · Metabolomics and Mass Spectrometry Studies