Rationale: Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is a powerful method for identifying viruses via nucleic acid detection. The data processing method is critical in recognizing nucleic acid obtained by MALDI-TOF-MS. Therefore, new development of data algorithm is needed for virus identification.
Methods: In this work, we developed a new data processing algorithm of MALDI-TOF-MS to identify respiratory viruses and deafness gene mutation sites. The algorithm includes denoising, baseline correcting, peak identification, and extraction features for processing the MS spectrum.
Results: Standard nucleic acid and respiratory virus samples were used to evaluate the performances of the newly developed algorithms. The errors of peak detection were found to be less than 200 ppm. Excellent sensitivity (91.67%-100%) and specificity (96.88-100%) were obtained by identifying 305 virus samples in this work, showing excellent performances. Additionally, accurate identification of the mutation sites of deafness genes was also obtained by the presented method.
Conclusions: Overall, our data showed that this method is accurate, sensitive, and specific for nucleic acid identification, showing the potential applications for qualitative analysis of respiratory viruses and deafness gene mutation screening.
Keywords: MALDI‐TOF‐MS; data processing; qualitative analysis; respiratory virus.
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