دورية أكاديمية

PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration.

التفاصيل البيبلوغرافية
العنوان: PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration.
المؤلفون: Wieder, Cecilia, Cooke, Juliette, Frainay, Clement, Poupin, Nathalie, Bowler, Russell, Jourdan, Fabien, Kechris, Katerina J, Lai, Rachel Pj, Ebbels, Timothy
المصدر: PLoS Comput Biol ; ISSN:1553-7358 ; Volume:20 ; Issue:3
بيانات النشر: Public Library of Science
سنة النشر: 2024
المجموعة: PubMed Central (PMC)
الوصف: As terabytes of multi-omics data are being generated, there is an ever-increasing need for methods facilitating the integration and interpretation of such data. Current multi-omics integration methods typically output lists, clusters, or subnetworks of molecules related to an outcome. Even with expert domain knowledge, discerning the biological processes involved is a time-consuming activity. Here we propose PathIntegrate, a method for integrating multi-omics datasets based on pathways, designed to exploit knowledge of biological systems and thus provide interpretable models for such studies. PathIntegrate employs single-sample pathway analysis to transform multi-omics datasets from the molecular to the pathway-level, and applies a predictive single-view or multi-view model to integrate the data. Model outputs include multi-omics pathways ranked by their contribution to the outcome prediction, the contribution of each omics layer, and the importance of each molecule in a pathway. Using semi-synthetic data we demonstrate the benefit of grouping molecules into pathways to detect signals in low signal-to-noise scenarios, as well as the ability of PathIntegrate to precisely identify important pathways at low effect sizes. Finally, using COPD and COVID-19 data we showcase how PathIntegrate enables convenient integration and interpretation of complex high-dimensional multi-omics datasets. PathIntegrate is available as an open-source Python package.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: https://doi.org/10.1371/journal.pcbi.1011814Test; https://pubmed.ncbi.nlm.nih.gov/38527092Test; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10994553Test/
DOI: 10.1371/journal.pcbi.1011814
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011814Test
https://pubmed.ncbi.nlm.nih.gov/38527092Test
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10994553Test/
حقوق: Copyright: © 2024 Wieder et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
رقم الانضمام: edsbas.7467048F
قاعدة البيانات: BASE