LFQ-Analyst: An Easy-To-Use Interactive Web Platform To Analyze and Visualize Label-Free Proteomics Data Preprocessed...

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Label-free quantification (LFQ) using MS1 signal intensities is a common method for global protein quantification in shotgun proteomics.
• Software like MaxQuant facilitates spectral feature extraction and quantitative reporting, but downstream analysis tools are lacking for non-experts.
• Interpreting complex proteomics data and performing statistical analysis requires specialized bioinformatics and statistical expertise.

Purpose of the Study:

• To develop an accessible, interactive web application for the statistical and exploratory analysis of label-free quantitative proteomics data.
• To provide researchers, particularly those with limited bioinformatics or statistical experience, with a user-friendly tool for differential expression analysis.
• To facilitate the visualization and interpretation of proteomics datasets preprocessed with MaxQuant.

Main Methods:

• Development of LFQ-Analyst, an interactive web application.
• Integration of "one-click" differential expression analysis capabilities.
• Implementation of features for visualizing label-free quantitative proteomics data.

Main Results:

• LFQ-Analyst offers a user-friendly interface for analyzing MaxQuant-preprocessed proteomics data.
• The application provides numerous publication-quality graphics for statistical and exploratory analysis.
• It simplifies complex data interpretation for researchers with varying levels of expertise.

Conclusions:

• LFQ-Analyst addresses the need for accessible tools in proteomics data analysis.
• The web application empowers biologists and researchers to perform sophisticated analyses independently.
• LFQ-Analyst enhances the utility of label-free quantification in proteomics research.