[en] Individual-specific networks, defined as networks of nodes and connecting edges that are specific to an individual, are promising tools for precision medicine. When such networks are biological, interpretation of functional modules at an individual level becomes possible. An under-investigated problem is relevance or "significance" assessment of each individual-specific network. This paper proposes novel edge and module significance assessment procedures for weighted and unweighted individual-specific networks. Specifically, we propose a modular Cook's distance using a method that involves iterative modeling of one edge versus all the others within a module. Two procedures assessing changes between using all individuals and using all individuals but leaving one individual out (LOO) are proposed as well (LOO-ISN, MultiLOO-ISN), relying on empirically derived edges. We compare our proposals to competitors, including adaptions of OPTICS, kNN, and Spoutlier methods, by an extensive simulation study, templated on real-life scenarios for gene co-expression and microbial interaction networks. Results show the advantages of performing modular versus edge-wise significance assessments for individual-specific networks. Furthermore, modular Cook's distance is among the top performers across all considered simulation settings. Finally, the identification of outlying individuals regarding their individual-specific networks, is meaningful for precision medicine purposes, as confirmed by network analysis of microbiome abundance profiles.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Melograna, Federico; BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium. federico.melograna@kuleuven.be
Li, Zuqi; BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
Galazzo, Gianluca; School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Medical Microbiology Infectious Diseases and Infection Prevention, Maastricht University Medical Center+, Maastricht, The Netherlands
van Best, Niels; Institute of Medical Microbiology, RWTH University Hospital Aachen, RWTH University, Aachen, Germany ; Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
Mommers, Monique; Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
Penders, John; School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Medical Microbiology Infectious Diseases and Infection Prevention, Maastricht University Medical Center+, Maastricht, The Netherlands ; Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
Stella, Fabio; Department of Informatics, Systems and Communication, University of Milano-Bicocca, 20126, Milan, Italy
Van Steen, Kristel ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Bioinformatique ; BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
Language :
English
Title :
Edge and modular significance assessment in individual-specific networks.
This study was embedded within the Euregional Microbiome Center ( www.microbiomecenter.eu ), a cross-border initiative on host-microbiome interactions between the University of Liège, Maastricht University, Maastricht University Medical Center+ and Uniklinik RWTH Aachen. Funding was received from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreements N° 813533 (mlfpm.eu) and N° 860895 (h2020transys.eu). Many thanks to Diane Duroux from the BIO3 lab at the University of Liège (Belgium) for inspiring discussions on ISNs and to Alice Giampino of University of Milan-Bicocca for discussions and clarifications on Dirichlet sampling.This study was embedded within the Euregional Microbiome Center (www.microbiomecenter.eu), a cross-border initiative on host-microbiome interactions between the University of Liège, Maastricht University, Maastricht University Medical Center+ and Uniklinik RWTH Aachen. Funding was received from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreements N° 813533 (mlfpm.eu) and N° 860895 (h2020transys.eu). Many thanks to Diane Duroux from the BIO3 lab at the University of Liège (Belgium) for inspiring discussions on ISNs and to Alice Giampino of University of Milan-Bicocca for discussions and clarifications on Dirichlet sampling.
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