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Herwig, Ralf
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Herwig, Ralf
author Barel, Gal
Herwig, Ralf
spellingShingle Barel, Gal
Herwig, Ralf
Nucleic Acids Research
NetCore: a network propagation approach using node coreness
Genetics
author_sort barel, gal
spelling Barel, Gal Herwig, Ralf 0305-1048 1362-4962 Oxford University Press (OUP) Genetics http://dx.doi.org/10.1093/nar/gkaa639 <jats:title>Abstract</jats:title> <jats:p>We present NetCore, a novel network propagation approach based on node coreness, for phenotype–genotype associations and module identification. NetCore addresses the node degree bias in PPI networks by using node coreness in the random walk with restart procedure, and achieves improved re-ranking of genes after propagation. Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the phenotype. We evaluated NetCore on gene sets from 11 different GWAS traits and showed improved performance compared to the standard degree-based network propagation using cross-validation. Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. We compared the novel approach to existing network propagation approaches and showed the benefits of using NetCore in comparison to those. We provide an easy-to-use implementation, together with a high confidence PPI network extracted from ConsensusPathDB, which can be applied to various types of genomics data in order to obtain a re-ranking of genes and functionally relevant network modules.</jats:p> NetCore: a network propagation approach using node coreness Nucleic Acids Research
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title NetCore: a network propagation approach using node coreness
title_unstemmed NetCore: a network propagation approach using node coreness
title_full NetCore: a network propagation approach using node coreness
title_fullStr NetCore: a network propagation approach using node coreness
title_full_unstemmed NetCore: a network propagation approach using node coreness
title_short NetCore: a network propagation approach using node coreness
title_sort netcore: a network propagation approach using node coreness
topic Genetics
url http://dx.doi.org/10.1093/nar/gkaa639
publishDate 2020
physical e98-e98
description <jats:title>Abstract</jats:title> <jats:p>We present NetCore, a novel network propagation approach based on node coreness, for phenotype–genotype associations and module identification. NetCore addresses the node degree bias in PPI networks by using node coreness in the random walk with restart procedure, and achieves improved re-ranking of genes after propagation. Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the phenotype. We evaluated NetCore on gene sets from 11 different GWAS traits and showed improved performance compared to the standard degree-based network propagation using cross-validation. Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. We compared the novel approach to existing network propagation approaches and showed the benefits of using NetCore in comparison to those. We provide an easy-to-use implementation, together with a high confidence PPI network extracted from ConsensusPathDB, which can be applied to various types of genomics data in order to obtain a re-ranking of genes and functionally relevant network modules.</jats:p>
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author Barel, Gal, Herwig, Ralf
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author_sort barel, gal
container_issue 17
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container_title Nucleic Acids Research
container_volume 48
description <jats:title>Abstract</jats:title> <jats:p>We present NetCore, a novel network propagation approach based on node coreness, for phenotype–genotype associations and module identification. NetCore addresses the node degree bias in PPI networks by using node coreness in the random walk with restart procedure, and achieves improved re-ranking of genes after propagation. Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the phenotype. We evaluated NetCore on gene sets from 11 different GWAS traits and showed improved performance compared to the standard degree-based network propagation using cross-validation. Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. We compared the novel approach to existing network propagation approaches and showed the benefits of using NetCore in comparison to those. We provide an easy-to-use implementation, together with a high confidence PPI network extracted from ConsensusPathDB, which can be applied to various types of genomics data in order to obtain a re-ranking of genes and functionally relevant network modules.</jats:p>
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spelling Barel, Gal Herwig, Ralf 0305-1048 1362-4962 Oxford University Press (OUP) Genetics http://dx.doi.org/10.1093/nar/gkaa639 <jats:title>Abstract</jats:title> <jats:p>We present NetCore, a novel network propagation approach based on node coreness, for phenotype–genotype associations and module identification. NetCore addresses the node degree bias in PPI networks by using node coreness in the random walk with restart procedure, and achieves improved re-ranking of genes after propagation. Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the phenotype. We evaluated NetCore on gene sets from 11 different GWAS traits and showed improved performance compared to the standard degree-based network propagation using cross-validation. Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. We compared the novel approach to existing network propagation approaches and showed the benefits of using NetCore in comparison to those. We provide an easy-to-use implementation, together with a high confidence PPI network extracted from ConsensusPathDB, which can be applied to various types of genomics data in order to obtain a re-ranking of genes and functionally relevant network modules.</jats:p> NetCore: a network propagation approach using node coreness Nucleic Acids Research
spellingShingle Barel, Gal, Herwig, Ralf, Nucleic Acids Research, NetCore: a network propagation approach using node coreness, Genetics
title NetCore: a network propagation approach using node coreness
title_full NetCore: a network propagation approach using node coreness
title_fullStr NetCore: a network propagation approach using node coreness
title_full_unstemmed NetCore: a network propagation approach using node coreness
title_short NetCore: a network propagation approach using node coreness
title_sort netcore: a network propagation approach using node coreness
title_unstemmed NetCore: a network propagation approach using node coreness
topic Genetics
url http://dx.doi.org/10.1093/nar/gkaa639