directLFQ
directLFQ performs label-free protein quantification from peptide or fragment-ion intensities to enable scalable normalization and intensity estimation in mass spectrometry-based proteomics.
Key Features:
- Scalability: Employs a ratio-based algorithm that scales linearly with the number of samples, enabling quantification of ~10,000 proteomes in ≈10 minutes and ~100,000 proteomes in under two hours, with up to 1,000-fold speed improvement versus MaxLFQ.
- Ratio-based normalization: Uses ratio-based sample normalization and protein intensity calculation for consistent quantitative estimates.
- Logarithmic-space alignment: Aligns samples and ion traces by shifting in logarithmic space to achieve precise normalization across samples.
- Normalization and performance: Shows normalization properties and benchmark performance comparable to MaxLFQ for both DDA and DIA datasets.
- Peptide-level intensity estimates: Provides normalized peptide intensity estimates for detailed peptide-level comparisons in addition to protein-level quantification.
- Integration with workflows: Compatible with the AlphaPept ecosystem and designed to operate downstream of common proteomics workflows.
Scientific Applications:
- Large-scale proteomics: Enables rapid protein quantification in large-scale, high-throughput proteomic studies.
- DDA and DIA analysis: Supports normalization and comparative quantification in both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets.
- Peptide-level analyses: Facilitates peptide-level differential analysis using normalized peptide intensity estimates.
Methodology:
Implements a ratio-based sample normalization and protein intensity calculation, aligns samples and ion traces by logarithmic-space shifting, and outputs normalized peptide and protein intensity estimates with algorithms that scale linearly with sample number.
Topics
Details
- License:
- Apache-2.0
- Cost:
- Free of charge
- Tool Type:
- desktop application, library
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python
- Added:
- 8/8/2023
- Last Updated:
- 8/8/2023
Operations
Publications
Ammar C, Schessner JP, Willems S, Michaelis AC, Mann M. Accurate Label-Free Quantification by directLFQ to Compare Unlimited Numbers of Proteomes. Molecular & Cellular Proteomics. 2023;22(7):100581. doi:10.1016/j.mcpro.2023.100581. PMID:37225017. PMCID:PMC10315922.