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.

Links