Andrew Walakira (Avtor), Damjana Rozman (Avtor), Tadeja Režen (Avtor), Miha Mraz (Avtor), Miha Moškon (Avtor)

Povzetek

Omics data can be integrated into a reference model using various model extraction methods (MEMs) to yield context-specific genome-scale metabolic models (GEMs). How to chose the appropriate MEM, thresholding rule and threshold remains a challenge. We integrated mouse transcriptomic data from a Cyp51 knockout mice diet experiment (GSE58271) using five MEMs (GIMME, iMAT, FASTCORE, INIT an tINIT) in a combination with a recently published mouse GEM iMM1865. Except for INIT and tINIT, the size of extracted models varied with the MEM used (t-test: p-value <0.001). The Jaccard index of iMAT models ranged from 0.27 to 1.0. Out of the three factors under study in the experiment (diet, gender and genotype), gender explained most of the variability (>90%) in PC1 for FASTCORE. In iMAT, each of the three factors explained less than 40% of the variability within PC1, PC2 and PC3. Among all the MEMs, FASTCORE captured the most of the true variability in the data by clustering samples by gender. Our results show that for the efficient use of MEMs in the context of omics data integration and analysis, one should apply various MEMs, thresholding rules, and thresholding values to select the MEM and its configuration that best captures the true variability in the data. This selection can be guided by the methodology as proposed and used in this paper. Moreover, we describe certain approaches that can be used to analyse the results obtained with the selected MEM and to put these results in a biological context.

Ključne besede

metabolni modeli na nivoju genoma;ekstrakcija modelov;kontekstno specifični metabolni modeli;integracija omskih podatkov;analiza obogatitve metabolnih podsistemov;genome-scale metabolic model;model extraction methods;context-specific metabolic model;omics data integration;subsystem enrichment analysis;model interpretability;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FRI - Fakulteta za računalništvo in informatiko
UDK: 004:575.112
COBISS: 66227971 Povezava se bo odprla v novem oknu
ISSN: 2001-0370
Št. ogledov: 389
Št. prenosov: 97
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: metabolni modeli na nivoju genoma;ekstrakcija modelov;kontekstno specifični metabolni modeli;integracija omskih podatkov;analiza obogatitve metabolnih podsistemov;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 3521-3530
Zvezek: ǂVol. ǂ19
Čas izdaje: 2021
DOI: 10.1016/j.csbj.2021.06.009
ID: 13055815