SCALiR: a web application for automating absolute quantification of mass spectrometry-based metabolomics data

Area of Science:

• Metabolomics
• Analytical Chemistry
• Bioinformatics

Background:

• Quantitative liquid chromatography-mass spectrometry (LC-MS) is crucial for biological systems analysis but faces challenges in manual metabolite concentration determination.
• Existing methods for calculating metabolite concentrations from standard curves are labor-intensive and lack automated open-source solutions.
• Accurate quantification is essential for robust metabolomics research, driving the need for efficient computational tools.

Approach:

• Introduction of SCALiR (Standard Curve Application for determining Linear Ranges), a novel web-based software tool for automated metabolite quantification.
• SCALiR employs an algorithm to automatically determine the best-fit line for standard curves and calculate absolute compound concentrations from LC-MS signal data.
• The tool is designed to be open-source and vendor-agnostic, facilitating integration into diverse quantitative workflows.

Key Points:

• SCALiR demonstrates excellent performance, achieving an R² of 0.99 when comparing calculated versus expected concentrations for 77 metabolites.
• The software ensures reproducibility, with an average coefficient of variation of 0.091 for mid-range standards across ten analytical batches.
• Key advantages include rapid analysis (10 seconds for >75 compounds), automation capabilities, and deterministic quantification limit evaluation.

Conclusions:

• SCALiR provides a simple, rapid, and open-source solution for automated quantitative metabolomics.
• The tool enhances the rigor and reproducibility of metabolomics studies by simplifying complex data analysis.
• SCALiR empowers the metabolomics community with efficient tools for absolute metabolite quantification.