Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Mass spectrometry (MS)-based proteomics data, including Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA), are widely used in biological research. However, the application of these datasets in validation studies is still limited due to the lack of clear demonstrations on how to effectively search and analyze proteomic data. To fill this gap, we selected one DDA and one DIA dataset deposited in the PRoteomics IDEntifications Database (PRIDE) data repository to better illustrate the proteomic data analysis workflow and downstream post-processing of protein search results. For demonstration purposes, we used two free computational tools: FragPipe (v22.0) for DDA datasets and DIA-NN (2.1.0) for DIA datasets. Post-processing steps, such as generating volcano plots and lists of dysregulated proteins, were demonstrated using R code. This study provides basic protocols for searching and analyzing proteomic data, serving as an essential beginner's guide to effectively handle proteomic datasets. Through this work, we aim to empower researchers with the knowledge necessary to leverage proteomic data in their biological investigations.