prolfquapp

prolfquapp performs differential expression analysis of mass spectrometry–based quantitative proteomics datasets using statistical models from the prolfqua R package.

Key Features:

• Statistical modeling: Implements differential expression models provided by the prolfqua R package.
• Support for complex experimental designs: Handles repeated measurements and multiple explanatory variables across samples, groups, and proteins.
• Output formats: Exports results as dynamic HTML reports, XLSX files, SummarizedExperiment objects, and rank files.
• Downstream compatibility: Produces outputs compatible with exploreDE Shiny and gene set enrichment analysis workflows.
• Scalability: Processes large-scale quantitative proteomics datasets with numerous samples, groups, and proteins.

Scientific Applications:

• Differential protein expression analysis: Identify differentially abundant proteins from mass spectrometry-based quantitative proteomics experiments.
• Preparation for gene set enrichment analysis: Generate rank files and expression matrices for gene set enrichment analysis.
• Integration with Bioconductor workflows: Provide SummarizedExperiment objects for downstream analyses and tools such as exploreDE Shiny.

Methodology:

Performs differential expression analysis using statistical models from the prolfqua R package and exports results as dynamic HTML reports, XLSX files, SummarizedExperiment objects, and rank files.