Data processing pipelines for comprehensive profiling of proteomics samples by label-free LC-MS for biomarker discovery

Abstract

Label-free quantitative LC-MS profiling of complex body fluids has become an important analytical tool for biomarker and biological knowledge discovery in the past decade. Accurate processing, statistical analysis and validation of acquired data diversified by the different types of mass spectrometers, mass spectrometer parameter settings and applied sample preparation steps are essential to answer complex life science research questions and understand the molecular mechanism of disease onset and developments. This review provides insight into the main modules of label-free data processing pipelines with statistical analysis and validation and discusses recent developments. Special emphasis is devoted to quality control methods, performance assessment of complete workflows and algorithms of individual modules. Finally, the review discusses the current state and trends in high throughput data processing and analysis solutions for users with little bioinformatics knowledge.