Proteomics is a field of study focused on analysis and identification of protein, with mass spectrometry being the method of choice. Various software tools are available for analyzing experimental peptide data, utilizing different algorithms and settings for identification. In this master's thesis, we focused on the comparison of four open source tools: MSFragger, MetaMorpheus, MaxQuant, and AlphaPept. The programs were evaluated using default settings on publicly available mass spectrometry data, assessing multiple aspects of their performance, including user experience, documentation, analysis speed, and the success of identifying peptides, modified peptides, and peptides with mutations. The results showed that MSFragger and MetaMorpheus performed best in the identification of modified peptides and mutations, with MetaMorpheus having the shortest analysis runtime. MaxQuant performed worse than these two programs but was still better than AlphaPept, which proved to be the least robust and often failed to identify peptides. An important finding was that the identification of mutations was not particularly successful, emphasizing the need for further development in this area. When selecting an appropriate tool, it is crucial to consider the presence of false-positive results, which can affect data interpretation. Our results provide insight into the differences between these programs and offer researchers useful guidelines for choosing the right tool for peptide identification and analysis.
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