The most common causes of respiratory infections are viruses, bacteria or fungal pathogens which are responsible for a high proportion of deaths worldwide. Considering this fact, early and accurate diagnosis of respiratory pathogens and a good understanding of specifics of the diagnostic methods used to identify them is crucial. In this way, we are able to control the epidemiological spread or outbreak as in the recent COVID-19 pandemic. The focus of this project is to investigate the variability in the diagnostic identification of pathogens, by comparing the results of three different diagnostic methods: qPCR and two sequencing-based methods, with the aim of evaluating the entire workflow from the initianl biological sample preparation to the final statistical and bioinformatical evaluation of the results. For our analysis, we used randomly choosen unknown nasopharyngeal swabs from 35 participants. All 35 samples were analysed using qPCR and short-read sequencing, while 15 of them were also analysed with long-read sequencing method. In this way, we compared variability of results in identification of influenza A and SARS-CoV-2 . All three methods identified these viruses equally in 76,92 % of 13 samples, qPCR and short-read sequencing in 82,86 % of 35 samples and qPCR and long read sequencing in 84,62 % of 13 samples. Furthermore, we statistically compared the diagnostic accuracy of influenza A and SARS-CoV-2 identification and concluded that the identification was 82,85 % concordant with qPCR and short-read sequencing, 84,61 % with qPCR and long-read sequencing and
84,61 % with short and long read sequencing. In relation to the above results, the highest agreement in the identification of influenza A and SARS-CoV-2 was achieved by qPCR and long-read sequencing, followed by both sequencing-based methods and qPCR and short-read sequencing with the same percentage of result variability.
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