Protocol for single-cell optimization objective and trade-off inference

Single-cell optimization objective and trade-off inference (SCOOTI) is a computational framework that integrates bulk and single-cell omics data with genome-scale metabolic modeling to infer metabolic objectives and trade-offs in biological systems. Here, we present a protocol for installing and running SCOOTI, using transcriptomics, proteomics, and metabolomics data to constrain metabolic models. We describe steps to interpret metabolic priorities across different cell states or conditions through clustering, dimensionality reduction, and trade-off analysis. • Steps to infer metabolic objectives from bulk and single-cell omics data • Construction of unconstrained and omics-constrained genome-scale metabolic models • Meta-regression-based inference of metabolic objective coefficients across conditions • Downstream analysis of metabolic trade-offs and objective priorities across cell states Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Single-cell optimization objective and trade-off inference (SCOOTI) is a computational framework that integrates bulk and single-cell omics data with genome-scale metabolic modeling to infer metabolic objectives and trade-offs in biological systems. Here, we present a protocol for installing and running SCOOTI, using transcriptomics, proteomics, and metabolomics data to constrain metabolic models. We describe steps to interpret metabolic priorities across different cell states or conditions through clustering, dimensionality reduction, and trade-off analysis.