A graphical user interface (NWUSA) for Raman spectral processing, analysis and feature recognition.

Area of Science:

• Analytical Chemistry
• Biophysics
• Spectroscopy

Background:

• Interpreting biologically derived Raman spectral data requires specialized expertise for accurate results.
• Developing user-friendly tools is crucial for broader adoption of Raman spectroscopy in biological and clinical fields.

Purpose of the Study:

• To develop an integrated, user-friendly Raman spectral analysis software (NWUSA) for non-professional users.
• To enable accurate spectral processing, analysis, and feature recognition of biological samples.

Main Methods:

• Development of the NWUSA software with a graphical user interface.
• Implementation of preprocessing techniques: spectral range selection, cosmic ray removal, background subtraction, smoothing, normalization, and mean-centering.
• Integration of multivariate analysis algorithms: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Partial Least Squares-Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), and PCA-SVM.

Main Results:

• The NWUSA software successfully processed and analyzed a spectral dataset from two different samples.
• The software demonstrated rapid and accurate performance in spectral data processing and feature recognition.
• Evaluation confirmed the software's ability to meet functional requirements for Raman spectral analysis.

Conclusions:

• The developed NWUSA software effectively supports non-professional users in interpreting Raman spectral data.
• The open-source nature allows for customization and extension, benefiting various Raman-based investigations, particularly in clinical settings.
• NWUSA enhances the accessibility and utility of Raman spectroscopy for biological and medical research.