LFQuant

LFQuant performs label-free quantification of high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics data by reconstructing peptide extracted ion chromatograms from identification information to enable accurate, large-scale protein quantification.

Key Features:

• File and search-engine compatibility: Supports raw data formats mzXML and Thermo RAW and integrates with SEQUEST, MASCOT, and X!Tandem, with support for a target-decoy search strategy.
• Peptide XIC reconstruction: Reconstructs peptide extracted ion chromatograms from database search results to refine quantification and reduce search space.
• Search-space optimization and speed: Optimizes the search space derived from identification information to enhance processing speed.
• Cross-assignment across runs: Performs cross-assignment among different runs to mitigate random effects of MS/MS sampling and improve quantitative consistency.
• Large-scale and fractionated dataset handling: Processes extensive label-free datasets including those fractionated by SDS-PAGE or 2D LC.
• Comparative performance: Demonstrated improved precision, accuracy, and reduced processing time relative to MaxQuant and IDEAL-Q on replication datasets such as UPS1.

Scientific Applications:

• Label-free quantitative proteomics: Quantification of protein abundance from LC-MS/MS datasets without isotopic labeling.
• Large-scale proteome studies: Analysis of complex protein mixtures and fractionated samples for comprehensive protein expression profiling.
• Comparative and differential expression studies: Quantitative comparison of protein levels across conditions or sample cohorts using reconstructed peptide XICs and cross-run assignment.

Methodology:

Reconstructs peptide extracted ion chromatograms from database search results, optimizes search space to enhance processing speed, employs cross-assignment among runs, and supports a target-decoy search strategy with SEQUEST, MASCOT, and X!Tandem on mzXML and Thermo RAW inputs.