TROPPO: tissue-specific reconstruction and phenotype prediction using omics data

TL;DR

TROPPO is an open-source tool that helps build accurate, tissue-specific metabolic models using omics data.

Contribution

TROPPO introduces an open-source Python library for tissue-specific metabolic model reconstruction and validation.

Findings

TROPPO supports multiple context-specific reconstruction algorithms and includes validation methods.

The tool integrates gap-filling algorithms to ensure model consistency.

TROPPO is freely available and compatible with other constraint-based tools.

Abstract

The increasing availability of high-throughput technologies in systems biology has advanced predictive tools like genome-scale metabolic models. Despite this progress, integrating omics data to create accurate, context-specific metabolic models for different tissues or cells remains challenging. A significant issue is that many existing tools rely on proprietary software, which limits accessibility. We introduce TROPPO, an open-source Python library designed to overcome these challenges. TROPPO supports a wide range of context-specific reconstruction algorithms, provides validation methods for assessing generated models, and includes gap-filling algorithms to ensure model consistency, integrating well with other constraint-based tools.

TROPPO is implemented in Python and is freely available at https://github.com/BioSystemsUM/TROPPO and https://pypi.org/project/TROPPO/.

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