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BioinformaticsbioRxiv
Preprint

RMetD2: a tool for integration of relative transcriptomics data into Genome-scale metabolic models

Cheng ZhangiD, Sunjae LeeiD, Gholamreza BidkhoriiD, Rui BenfeitasiD, Alen LovrićiD, Shuqi CheniD, Mathias UhléniD, Jens NielseniD, Adil MardinoğluiD

Abstract

Relative Metabolic Differences version 2 (RMetD2) is a tool for integration of differentially expressed (DE) genes into genome-scale metabolic models (GEMs) for revealing the altered metabolism between two biological conditions. This method provides a robust evaluation of the metabolism by using flux ranges instead of a single set of flux distributions. RMetD2 classifies reactions into three different groups, namely up-regulated, down-regulated and unchanged, which enables systematic interpretation of the metabolic differences between two different conditions. We employed this method in three different case studies using mice and human datasets, and compared it with state-of-the-art methods used for studying condition-specific metabolic differences using GEMs. We observed that RMetD2 is capable of capturing experimentally-observed features that are missed by other methods, highlighting its potential use in biotechnology and systems medicine applications. RMetD2 is implemented in Matlab and it is available without any limitation at https://sourceforge.net/projects/rmetd.

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02 /Specification & Classification

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