Logistic PCA explains differences between genome-scale metabolic models in terms of metabolic pathways
- Author(s)
- Leopold Zehetner, Diana Széliová, Barbara Kraus, Juan A. Hernandez Bort, Jürgen Zanghellini
- Abstract
Genome-scale metabolic models (GSMMs) offer a holistic view of biochemical reaction networks, enabling in-depth analyses of metabolism across species and tissues in multiple conditions. However, comparing GSMMs Against each other poses challenges as current dimensionality reduction algorithms or clustering methods lack mechanistic interpretability, and often rely on subjective assumptions. Here, we propose a new approach utilizing logisitic principal component analysis (LPCA) that efficiently clusters GSMMs while singling out mechanistic differences in terms of reactions and pathways that drive the categorization. We applied LPCA to multiple diverse datasets, including GSMMs of 222 Escherichia-strains, 343 budding yeasts (Saccharomycotina), 80 human tissues, and 2943 Firmicutes strains. Our findings demonstrate LPCA’s effectiveness in preserving microbial phylogenetic relationships and discerning human tissue-specific metabolic profiles, exhibiting comparable performance to traditional methods like t-distributed stochastic neighborhood embedding (t-SNE) and Jaccard coefficients. Moreover, the subsystems and associated reactions identified by LPCA align with existing knowledge, underscoring its reliability in dissecting GSMMs and uncovering the underlying drivers of separation.
- Organisation(s)
- Department of Analytical Chemistry
- External organisation(s)
- Baxalta Innovations GmbH, Vienna Doctoral School in Chemistry (DoSChem)
- Journal
- PLoS Computational Biology
- Volume
- 20
- ISSN
- 1553-734X
- DOI
- https://doi.org/10.1371/journal.pcbi.1012236
- Publication date
- 06-2024
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 104027 Computational chemistry, 106005 Bioinformatics
- ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics, Modelling and Simulation, Ecology, Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Computational Theory and Mathematics
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/logistic-pca-explains-differences-between-genomescale-metabolic-models-in-terms-of-metabolic-pathways(6d991282-7dd2-4618-82ee-66c4a2f08fd1).html