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Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...

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Related Experiment Video

Updated: May 31, 2025

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

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

Witold E Wolski^1,2, Jonas Grossmann^1,2, Leonardo Schwarz^1,2

¹Functional Genomics Center Zurich (FGCZ) - University of Zurich/ETH Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.

Journal of Proteome Research

|January 24, 2025

Summary

This summary is machine-generated.

Mass spectrometry is key for quantitative proteomics. The prolfquapp tool simplifies differential expression analysis (DEA) for complex experiments, offering accessible, integrated data processing and visualization for researchers.

Keywords:

differential expression analysis proteomics statistical software workflows

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Area of Science:

Proteomics
Bioinformatics
Computational Biology

Background:

Mass spectrometry is fundamental for quantitative proteomics, enabling relative protein quantification and differential expression analysis (DEA).
Interactive DEA tools become impractical for complex experiments with numerous samples, groups, and identified proteins.

Purpose of the Study:

To develop a command-line interface tool, prolfquapp, that simplifies DEA for large-scale quantitative proteomics.
To enable nonprogrammers to perform DEA and integrate it into workflow management systems.
To streamline data processing and result visualization for complex proteomics experiments.

Main Methods:

Prolfquapp provides a command-line interface for DEA.
It generates dynamic HTML reports for exploring differential expression results.
It leverages advanced statistical models from the prolfqua R package.

Main Results:

Prolfquapp simplifies DEA, making it accessible to nonprogrammers.
Dynamic HTML reports facilitate the exploration of complex experimental results, including repeated measurements and multiple explanatory variables.
Supports multiple output formats (XLSX, SummarizedExperiment, rank files) for further analysis.

Conclusions:

Prolfquapp offers a user-friendly, integrated solution for large-scale quantitative proteomics.
It combines efficient data processing with insightful, publication-ready outputs.
Facilitates further interactive analysis using spreadsheet software, Shiny applications, or gene set enrichment analysis tools.