Article (Scientific journals)
netANOVA: novel graph clustering technique with significance assessment via hierarchical ANOVA.
Duroux, Diane; Van Steen, Kristel
2023In Briefings in Bioinformatics, 24 (2)
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Keywords :
Graph comparison; Network clustering; Stratified medicine; System medicine; Cluster Analysis; Computer Simulation; Workflow; Analysis of Variance; Algorithms; Information Systems; Molecular Biology
Abstract :
[en] Many problems in life sciences can be brought back to a comparison of graphs. Even though a multitude of such techniques exist, often, these assume prior knowledge about the partitioning or the number of clusters and fail to provide statistical significance of observed between-network heterogeneity. Addressing these issues, we developed an unsupervised workflow to identify groups of graphs from reliable network-based statistics. In particular, we first compute the similarity between networks via appropriate distance measures between graphs and use them in an unsupervised hierarchical algorithm to identify classes of similar networks. Then, to determine the optimal number of clusters, we recursively test for distances between two groups of networks. The test itself finds its inspiration in distance-wise ANOVA algorithms. Finally, we assess significance via the permutation of between-object distance matrices. Notably, the approach, which we will call netANOVA, is flexible since users can choose multiple options to adapt to specific contexts and network types. We demonstrate the benefits and pitfalls of our approach via extensive simulations and an application to two real-life datasets. NetANOVA achieved high performance in many simulation scenarios while controlling type I error. On non-synthetic data, comparison against state-of-the-art methods showed that netANOVA is often among the top performers. There are many application fields, including precision medicine, for which identifying disease subtypes via individual-level biological networks improves prevention programs, diagnosis and disease monitoring.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Duroux, Diane ;  Université de Liège - ULiège > GIGA > GIGA Medical Genomics - Biostatistics, biomedicine and bioinformatics
Van Steen, Kristel  ;  Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Bioinformatique ; BIO3 - Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
Language :
Title :
netANOVA: novel graph clustering technique with significance assessment via hierarchical ANOVA.
Publication date :
19 March 2023
Journal title :
Briefings in Bioinformatics
Publisher :
Oxford University Press, England
Volume :
Issue :
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
EU - European Union [BE]
Funding number :
Marie Sklodowska-Curie grant agreement No 813533
Funding text :
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 813533.
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since 04 July 2023


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