Sensible Functional Linear Discriminant Analysis Effectively Discriminates Enhanced Raman Spectra of Mycobacterium Species
| Autor: | Ci-Ren Jiang, Wei Chih Cheng, Yuh-Lin Wang, Chi Hung Lin, Lu Hung Chen, Da-Wei Wang, Juen-Kai Wang, Yu Ming Deng, Ruwen Jou |
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| Rok vydání: | 2021 |
| Předmět: |
biology
Chemistry 010401 analytical chemistry Computational biology bacterial infections and mycoses 010402 general chemistry Linear discriminant analysis biology.organism_classification 01 natural sciences 0104 chemical sciences Analytical Chemistry Mycobacterium tuberculosis complex Principal component analysis Nontuberculous mycobacteria Mycobacterium species |
| Zdroj: | Analytical Chemistry. 93:2785-2792 |
| ISSN: | 1520-6882 0003-2700 |
| Popis: | Tuberculosis caused by Mycobacterium tuberculosis complex (MTBC) is one of the major infectious diseases in the world. Identification of MTBC and differential diagnosis of nontuberculous mycobacteria (NTM) species impose challenges because of their taxonomic similarity. This study describes a differential diagnosis method using the surface-enhanced Raman scattering (SERS) measurement of molecules released by Mycobacterium species. Conventional principal component analysis and linear discriminant analysis methods successfully separated the acquired spectrum of MTBC from those of NTM species but failed to distinguish between the spectra of different NTM species. A novel sensible functional linear discriminant analysis (SLDA), projecting the averaged spectrum of a bacterial specie to the subspace orthogonal to the within-species random variation, thereby eliminating its influence in applying linear discriminant analysis, was employed to effectively discriminate not only MTBC but also species of NTM. The successful demonstration of this SERS-SLDA method opens up new opportunities for the rapid differentiation of Mycobacterium species. |
| Databáze: | OpenAIRE |
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