The prolfquapp R package [github.com/prolfqua/prolfquapp] is a powerful tool for simplifying protein differential expression analysis and reporting by streamlining data processing and enhancing result visualization through dynamic HTML reports. Developed for label-free and labeled proteomics, this command-line R package leverages advanced statistical models in the R package prolfqua [https://doi.org/10.1021/acs.jproteome.2c00441] to offer a streamlined workflow from data input to insightful outputs.

One of the most intriguing features of prolfquapp is its ability to facilitate the study of how various factors influence protein expression and how these factors interact. To illustrate this, we will use an experiment with repeated measurements and two explanatory variables as an example. We will guide you through the process of specifying group differences and their interactions using the annotation file. We will also demonstrate how the visualizations in the dynamic HTML report make it easier to understand the results. Our aim is to ignite your curiosity in the capabilities of factorial designs and prolfquapp.

The prolfquapp package is designed with the user in mind, offering a user-friendly command-line tool. It enhances research efficiency by performing essential tasks like data aggregation, summarization, normalization, and differential expression analysis using just a few input files. These include the parameter file, the sample annotation file, and a folder with the outputs of quantification software like DIANN, MaxQuant, Spectronaut, or Compound Discoverer. It produces dynamic HTML reports with quality control and visualizations, along with multiple output formats, including PDF and XLSX. Its seamless integration with the interactive exploreDE [https://zenodo.org/records/10571252] Shiny application enhances the user's ability to visualize and interpret the data and create publication-ready figures. This user-friendly and efficient solution empowers researchers in protein differential expression analysis.

Prolfquapp is similar to other R applications, such as Einprot, LFQAnalyst, or MSDap, in that it reuses statistical models implemented in other R-packages, and allows non-bioinformaticians to quickly generate QC and DEA results for label-free and labeled proteomics quantification experiments. It is unique because it generates interactive HTML documents, integrates seamlessly with the Shiny exploreDE application, and allows easy analysis of experiments with factorial designs. Prolfquapp can be installed from https://github.com/prolfqua/prolfquapp.