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Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways

A wide variety of 1) parametric regression models and 2) co-expression networks have been developed for finding gene-by-gene interactions underlying complex traits from expression data. While both methodological schemes have their own well-known benefits, little is known about their synergistic pote...

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Autores principales: Kontio, Juho A. J., Pyhäjärvi, Tanja, Sillanpää, Mikko J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118548/
https://www.ncbi.nlm.nih.gov/pubmed/33939702
http://dx.doi.org/10.1371/journal.pcbi.1008960
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author Kontio, Juho A. J.
Pyhäjärvi, Tanja
Sillanpää, Mikko J.
author_facet Kontio, Juho A. J.
Pyhäjärvi, Tanja
Sillanpää, Mikko J.
author_sort Kontio, Juho A. J.
collection PubMed
description A wide variety of 1) parametric regression models and 2) co-expression networks have been developed for finding gene-by-gene interactions underlying complex traits from expression data. While both methodological schemes have their own well-known benefits, little is known about their synergistic potential. Our study introduces their methodological fusion that cross-exploits the strengths of individual approaches via a built-in information-sharing mechanism. This fusion is theoretically based on certain trait-conditioned dependency patterns between two genes depending on their role in the underlying parametric model. Resulting trait-specific co-expression network estimation method 1) serves to enhance the interpretation of biological networks in a parametric sense, and 2) exploits the underlying parametric model itself in the estimation process. To also account for the substantial amount of intrinsic noise and collinearities, often entailed by expression data, a tailored co-expression measure is introduced along with this framework to alleviate related computational problems. A remarkable advance over the reference methods in simulated scenarios substantiate the method’s high-efficiency. As proof-of-concept, this synergistic approach is successfully applied in survival analysis, with acute myeloid leukemia data, further highlighting the framework’s versatility and broad practical relevance.
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spelling pubmed-81185482021-05-24 Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways Kontio, Juho A. J. Pyhäjärvi, Tanja Sillanpää, Mikko J. PLoS Comput Biol Research Article A wide variety of 1) parametric regression models and 2) co-expression networks have been developed for finding gene-by-gene interactions underlying complex traits from expression data. While both methodological schemes have their own well-known benefits, little is known about their synergistic potential. Our study introduces their methodological fusion that cross-exploits the strengths of individual approaches via a built-in information-sharing mechanism. This fusion is theoretically based on certain trait-conditioned dependency patterns between two genes depending on their role in the underlying parametric model. Resulting trait-specific co-expression network estimation method 1) serves to enhance the interpretation of biological networks in a parametric sense, and 2) exploits the underlying parametric model itself in the estimation process. To also account for the substantial amount of intrinsic noise and collinearities, often entailed by expression data, a tailored co-expression measure is introduced along with this framework to alleviate related computational problems. A remarkable advance over the reference methods in simulated scenarios substantiate the method’s high-efficiency. As proof-of-concept, this synergistic approach is successfully applied in survival analysis, with acute myeloid leukemia data, further highlighting the framework’s versatility and broad practical relevance. Public Library of Science 2021-05-03 /pmc/articles/PMC8118548/ /pubmed/33939702 http://dx.doi.org/10.1371/journal.pcbi.1008960 Text en © 2021 Kontio et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kontio, Juho A. J.
Pyhäjärvi, Tanja
Sillanpää, Mikko J.
Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
title Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
title_full Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
title_fullStr Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
title_full_unstemmed Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
title_short Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
title_sort model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118548/
https://www.ncbi.nlm.nih.gov/pubmed/33939702
http://dx.doi.org/10.1371/journal.pcbi.1008960
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