prolfquapp - A User-Friendly Command-Line Tool Simplifying Differential Expression Analysis in Quantitative Proteomics

AbstractMass spectrometry is a cornerstone of quantitative proteomics, enabling relative protein quantification and differential expression analysis (DEA) of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, traditional interactive data analysis methods become impractical. The prolfquapp addresses this challenge by providing a command-line interface that simplifies DEA, making it accessible to non-programmers and seamlessly integrating it into workflow management systems. Prolfquapp streamlines data processing and result visualization by generating dynamic HTML reports that facilitate the exploration of differential expression results. These reports allow for investigating complex experiments, such as those involving repeated measurements and multiple explanatory variables. Additionally, prolfquapp supports various output formats, including XLSX files, SummarizedExperiment objects and rank files, for further interactive analysis using spreadsheet software, the exploreDE Shiny application, or gene set enrichment analysis software. By leveraging advanced statistical models from the prolfqua R package, prolfquapp offers a user-friendly, integrated solution for large-scale quantitative proteomics studies, combining efficient data processing with insightful, publication-ready outputs. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/617391v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@10930a2org.highwire.dtl.DTLVardef@57f5dborg.highwire.dtl.DTLVardef@ce0d73org.highwire.dtl.DTLVardef@1d531da_HPS_FORMAT_FIGEXP M_FIG C_FIG This visual table of contents illustrates the workflow and key features of the prolfquapp tool for differential expression analysis in proteomics. On the left are the inputs, like the CSV for annotation and quantification results, YAML for parameters, and FASTA files for protein information. In the center are the prolfquapp and prolfqua R packages and supporting tools like crosstalk and knitr, representing the core processing components. On the right side, the figure highlights the various outputs generated by prolfquapp O_LIXLSX files containing protein abundances, group summaries, and differential expression results. C_LIO_LIHTML reports with text, graphs, interactive volcano plots, and dynamic tables for data exploration. C_LIO_LIPDF documents with detailed protein boxplots and peptide-level matrix plots. C_LIO_LIIntegration with exploreDE for interactive data visualization. C_LI This diagram concisely summarizes the flow from data input to the creation of analysis-ready outputs, offering a clear overview of the prolfquapp toolset.