Assessment of network module identification across complex diseases

<p dir="ltr">Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different type...

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المؤلف الرئيسي: Sarvenaz Choobdar (18602821) (author)
مؤلفون آخرون: The DREAM Module Identification Challenge Consortium (18602824) (author), Mehmet E. Ahsen (18602827) (author), Jake Crawford (14846212) (author), Mattia Tomasoni (4227274) (author), Tao Fang (434629) (author), David Lamparter (606695) (author), Junyuan Lin (13017369) (author), Benjamin Hescott (475948) (author), Xiaozhe Hu (18602830) (author), Johnathan Mercer (18602833) (author), Ted Natoli (1339764) (author), Rajiv Narayan (4635193) (author), Aravind Subramanian (712720) (author), Jitao D. Zhang (14913645) (author), Gustavo Stolovitzky (239041) (author), Zoltán Kutalik (174641) (author), Kasper Lage (42180) (author), Donna K. Slonim (14636480) (author), Julio Saez-Rodriguez (25229) (author), Lenore J. Cowen (18602836) (author), Sven Bergmann (20384) (author), Daniel Marbach (366952) (author)
منشور في: 2019
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author Sarvenaz Choobdar (18602821)
author2 The DREAM Module Identification Challenge Consortium (18602824)
Mehmet E. Ahsen (18602827)
Jake Crawford (14846212)
Mattia Tomasoni (4227274)
Tao Fang (434629)
David Lamparter (606695)
Junyuan Lin (13017369)
Benjamin Hescott (475948)
Xiaozhe Hu (18602830)
Johnathan Mercer (18602833)
Ted Natoli (1339764)
Rajiv Narayan (4635193)
Aravind Subramanian (712720)
Jitao D. Zhang (14913645)
Gustavo Stolovitzky (239041)
Zoltán Kutalik (174641)
Kasper Lage (42180)
Donna K. Slonim (14636480)
Julio Saez-Rodriguez (25229)
Lenore J. Cowen (18602836)
Sven Bergmann (20384)
Daniel Marbach (366952)
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author_facet Sarvenaz Choobdar (18602821)
The DREAM Module Identification Challenge Consortium (18602824)
Mehmet E. Ahsen (18602827)
Jake Crawford (14846212)
Mattia Tomasoni (4227274)
Tao Fang (434629)
David Lamparter (606695)
Junyuan Lin (13017369)
Benjamin Hescott (475948)
Xiaozhe Hu (18602830)
Johnathan Mercer (18602833)
Ted Natoli (1339764)
Rajiv Narayan (4635193)
Aravind Subramanian (712720)
Jitao D. Zhang (14913645)
Gustavo Stolovitzky (239041)
Zoltán Kutalik (174641)
Kasper Lage (42180)
Donna K. Slonim (14636480)
Julio Saez-Rodriguez (25229)
Lenore J. Cowen (18602836)
Sven Bergmann (20384)
Daniel Marbach (366952)
author_role author
dc.creator.none.fl_str_mv Sarvenaz Choobdar (18602821)
The DREAM Module Identification Challenge Consortium (18602824)
Mehmet E. Ahsen (18602827)
Jake Crawford (14846212)
Mattia Tomasoni (4227274)
Tao Fang (434629)
David Lamparter (606695)
Junyuan Lin (13017369)
Benjamin Hescott (475948)
Xiaozhe Hu (18602830)
Johnathan Mercer (18602833)
Ted Natoli (1339764)
Rajiv Narayan (4635193)
Aravind Subramanian (712720)
Jitao D. Zhang (14913645)
Gustavo Stolovitzky (239041)
Zoltán Kutalik (174641)
Kasper Lage (42180)
Donna K. Slonim (14636480)
Julio Saez-Rodriguez (25229)
Lenore J. Cowen (18602836)
Sven Bergmann (20384)
Daniel Marbach (366952)
dc.date.none.fl_str_mv 2019-08-30T03:00:00Z
dc.identifier.none.fl_str_mv 10.1038/s41592-019-0509-5
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Assessment_of_network_module_identification_across_complex_diseases/25886893
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biological sciences
Bioinformatics and computational biology
Bioinformatics
gene networks
protein networks
module identification
disease relevance
DREAM Challenge
dc.title.none.fl_str_mv Assessment of network module identification across complex diseases
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the ‘Disease Module Identification DREAM Challenge’, an open competition to comprehensively assess module identification methods across diverse protein–protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.</p><h2>Other Information</h2><p dir="ltr">Published in: Nature Methods<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41592-019-0509-5" target="_blank">https://dx.doi.org/10.1038/s41592-019-0509-5</a></p>
eu_rights_str_mv openAccess
id Manara2_f077f637abd2c4a92275ee773e327e26
identifier_str_mv 10.1038/s41592-019-0509-5
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/25886893
publishDate 2019
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spelling Assessment of network module identification across complex diseasesSarvenaz Choobdar (18602821)The DREAM Module Identification Challenge Consortium (18602824)Mehmet E. Ahsen (18602827)Jake Crawford (14846212)Mattia Tomasoni (4227274)Tao Fang (434629)David Lamparter (606695)Junyuan Lin (13017369)Benjamin Hescott (475948)Xiaozhe Hu (18602830)Johnathan Mercer (18602833)Ted Natoli (1339764)Rajiv Narayan (4635193)Aravind Subramanian (712720)Jitao D. Zhang (14913645)Gustavo Stolovitzky (239041)Zoltán Kutalik (174641)Kasper Lage (42180)Donna K. Slonim (14636480)Julio Saez-Rodriguez (25229)Lenore J. Cowen (18602836)Sven Bergmann (20384)Daniel Marbach (366952)Biological sciencesBioinformatics and computational biologyBioinformaticsgene networksprotein networksmodule identificationdisease relevanceDREAM Challenge<p dir="ltr">Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the ‘Disease Module Identification DREAM Challenge’, an open competition to comprehensively assess module identification methods across diverse protein–protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.</p><h2>Other Information</h2><p dir="ltr">Published in: Nature Methods<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41592-019-0509-5" target="_blank">https://dx.doi.org/10.1038/s41592-019-0509-5</a></p>2019-08-30T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1038/s41592-019-0509-5https://figshare.com/articles/journal_contribution/Assessment_of_network_module_identification_across_complex_diseases/25886893CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/258868932019-08-30T03:00:00Z
spellingShingle Assessment of network module identification across complex diseases
Sarvenaz Choobdar (18602821)
Biological sciences
Bioinformatics and computational biology
Bioinformatics
gene networks
protein networks
module identification
disease relevance
DREAM Challenge
status_str publishedVersion
title Assessment of network module identification across complex diseases
title_full Assessment of network module identification across complex diseases
title_fullStr Assessment of network module identification across complex diseases
title_full_unstemmed Assessment of network module identification across complex diseases
title_short Assessment of network module identification across complex diseases
title_sort Assessment of network module identification across complex diseases
topic Biological sciences
Bioinformatics and computational biology
Bioinformatics
gene networks
protein networks
module identification
disease relevance
DREAM Challenge