Assessment of network module identification across complex diseases

On 30 August, 2019

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.

Original Paper: 

  • [DOI] S. Choobdar, M. E. Ahsen, J. Crawford, M. Tomasoni, T. Fang, D. Lamparter, J. Lin, B. Hescott, X. Hu, J. Mercer, T. Natoli, R. Narayan, F. Aicheler, N. Amoroso, A. Arenas, K. Azhagesan, A. Baker, M. Banf, S. Batzoglou, A. Baudot, R. Bellotti, S. Bergmann, K. A. Boroevich, C. Brun, S. Cai, M. Caldera, A. Calderone, G. Cesareni, W. Chen, C. Chichester, S. Choobdar, L. Cowen, J. Crawford, H. Cui, P. Dao, M. De Domenico, A. Dhroso, G. Didier, M. Divine, A. del Sol, T. Fang, X. Feng, J. C. Flores-Canales, S. Fortunato, A. Gitter, A. Gorska, Y. Guan, A. Guénoche, S. Gómez, H. Hamza, A. Hartmann, S. He, A. Heijs, J. Heinrich, B. Hescott, X. Hu, Y. Hu, X. Huang, K. V. Hughitt, M. Jeon, L. Jeub, N. T. Johnson, K. Joo, I. Joung, S. Jung, S. G. Kalko, P. J. Kamola, J. Kang, B. Kaveelerdpotjana, M. Kim, Y. Kim, O. Kohlbacher, D. Korkin, K. Krzysztof, K. Kunji, Z. Kutalik, K. Lage, D. Lamparter, S. Lang-Brown, T. D. Le, J. Lee, S. Lee, J. Lee, D. Li, J. Li, J. Lin, L. Liu, A. Loizou, Z. Luo, A. Lysenko, T. Ma, R. Mall, D. Marbach, T. Mattia, M. Medvedovic, J. Menche, J. Mercer, E. Micarelli, A. Monaco, F. Müller, R. Narayan, O. Narykov, T. Natoli, T. Norman, S. Park, L. Perfetto, D. Perrin, S. Pirrò, T. M. Przytycka, X. Qian, K. Raman, D. Ramazzotti, E. Ramsahai, B. Ravindran, P. Rennert, J. Saez-Rodriguez, C. Schärfe, R. Sharan, N. Shi, W. Shin, H. Shu, H. Sinha, D. K. Slonim, L. Spinelli, S. Srinivasan, A. Subramanian, C. Suver, D. Szklarczyk, S. Tangaro, S. Thiagarajan, L. Tichit, T. Tiede, B. Tripathi, A. Tsherniak, T. Tsunoda, D. Türei, E. Ullah, G. Vahedi, A. Valdeolivas, J. Vivek, C. von Mering, A. Waagmeester, B. Wang, Y. Wang, B. A. Weir, S. White, S. Winkler, K. Xu, T. Xu, C. Yan, L. Yang, K. Yu, X. Yu, G. Zaffaroni, M. Zaslavskiy, T. Zeng, J. D. Zhang, L. Zhang, W. Zhang, L. Zhang, X. Zhang, J. Zhang, X. Zhou, J. Zhou, H. Zhu, J. Zhu, G. Zuccon, A. Subramanian, J. D. Zhang, G. Stolovitzky, Z. Kutalik, K. Lage, D. K. Slonim, J. Saez-Rodriguez, L. J. Cowen, S. Bergmann, D. Marbach, and T. D. M. I. C. Consortium, “Assessment of network module identification across complex diseases,” Nature Methods, vol. 16, iss. 9, pp. 843-852, 2019.
    [bibtex] 
    @article{Choobdar2019Assessment,
  abstract = {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.},
  added-at = {2019-08-31T09:26:34.000+0200},
  author = {Choobdar, Sarvenaz and Ahsen, Mehmet E. and Crawford, Jake and Tomasoni, Mattia and Fang, Tao and Lamparter, David and Lin, Junyuan and Hescott, Benjamin and Hu, Xiaozhe and Mercer, Johnathan and Natoli, Ted and Narayan, Rajiv and Aicheler, Fabian and Amoroso, Nicola and Arenas, Alex and Azhagesan, Karthik and Baker, Aaron and Banf, Michael and Batzoglou, Serafim and Baudot, Anaïs and Bellotti, Roberto and Bergmann, Sven and Boroevich, Keith A. and Brun, Christine and Cai, Stanley and Caldera, Michael and Calderone, Alberto and Cesareni, Gianni and Chen, Weiqi and Chichester, Christine and Choobdar, Sarvenaz and Cowen, Lenore and Crawford, Jake and Cui, Hongzhu and Dao, Phuong and De Domenico, Manlio and Dhroso, Andi and Didier, Gilles and Divine, Mathew and del Sol, Antonio and Fang, Tao and Feng, Xuyang and Flores-Canales, Jose C. and Fortunato, Santo and Gitter, Anthony and Gorska, Anna and Guan, Yuanfang and Guénoche, Alain and Gómez, Sergio and Hamza, Hatem and Hartmann, András and He, Shan and Heijs, Anton and Heinrich, Julian and Hescott, Benjamin and Hu, Xiaozhe and Hu, Ying and Huang, Xiaoqing and Hughitt, V. Keith and Jeon, Minji and Jeub, Lucas and Johnson, Nathan T. and Joo, Keehyoung and Joung, InSuk and Jung, Sascha and Kalko, Susana G. and Kamola, Piotr J. and Kang, Jaewoo and Kaveelerdpotjana, Benjapun and Kim, Minjun and Kim, Yoo-Ah and Kohlbacher, Oliver and Korkin, Dmitry and Krzysztof, Kiryluk and Kunji, Khalid and Kutalik, Zoltàn and Lage, Kasper and Lamparter, David and Lang-Brown, Sean and Le, Thuc Duy and Lee, Jooyoung and Lee, Sunwon and Lee, Juyong and Li, Dong and Li, Jiuyong and Lin, Junyuan and Liu, Lin and Loizou, Antonis and Luo, Zhenhua and Lysenko, Artem and Ma, Tianle and Mall, Raghvendra and Marbach, Daniel and Mattia, Tomasoni and Medvedovic, Mario and Menche, Jörg and Mercer, Johnathan and Micarelli, Elisa and Monaco, Alfonso and Müller, Felix and Narayan, Rajiv and Narykov, Oleksandr and Natoli, Ted and Norman, Thea and Park, Sungjoon and Perfetto, Livia and Perrin, Dimitri and Pirrò, Stefano and Przytycka, Teresa M. and Qian, Xiaoning and Raman, Karthik and Ramazzotti, Daniele and Ramsahai, Emilie and Ravindran, Balaraman and Rennert, Philip and Saez-Rodriguez, Julio and Schärfe, Charlotta and Sharan, Roded and Shi, Ning and Shin, Wonho and Shu, Hai and Sinha, Himanshu and Slonim, Donna K. and Spinelli, Lionel and Srinivasan, Suhas and Subramanian, Aravind and Suver, Christine and Szklarczyk, Damian and Tangaro, Sabina and Thiagarajan, Suresh and Tichit, Laurent and Tiede, Thorsten and Tripathi, Beethika and Tsherniak, Aviad and Tsunoda, Tatsuhiko and Türei, Dénes and Ullah, Ehsan and Vahedi, Golnaz and Valdeolivas, Alberto and Vivek, Jayaswal and von Mering, Christian and Waagmeester, Andra and Wang, Bo and Wang, Yijie and Weir, Barbara A. and White, Shana and Winkler, Sebastian and Xu, Ke and Xu, Taosheng and Yan, Chunhua and Yang, Liuqing and Yu, Kaixian and Yu, Xiangtian and Zaffaroni, Gaia and Zaslavskiy, Mikhail and Zeng, Tao and Zhang, Jitao D. and Zhang, Lu and Zhang, Weijia and Zhang, Lixia and Zhang, Xinyu and Zhang, Junpeng and Zhou, Xin and Zhou, Jiarui and Zhu, Hongtu and Zhu, Junjie and Zuccon, Guido and Subramanian, Aravind and Zhang, Jitao D. and Stolovitzky, Gustavo and Kutalik, Zoltán and Lage, Kasper and Slonim, Donna K. and Saez-Rodriguez, Julio and Cowen, Lenore J. and Bergmann, Sven and Marbach, Daniel and Consortium, The DREAM Module Identification Challenge},
  biburl = {https://www.bibsonomy.org/bibtex/2b16329a3c248adb971d62f5565b27a0e/karthikraman},
  description = {Assessment of network module identification across complex diseases | Nature Methods},
  doi = {10.1038/s41592-019-0509-5},
  interhash = {9fe2b286802d6572f14a8a2040d5dcc2},
  intrahash = {b16329a3c248adb971d62f5565b27a0e},
  issn = {15487105},
  journal = {Nature Methods},
  keywords = {community-detection myown networks},
  number = 9,
  pages = {843--852},
  refid = {Choobdar2019},
  timestamp = {2019-08-31T09:26:34.000+0200},
  title = {Assessment of network module identification across complex diseases},
  url = {https://doi.org/10.1038/s41592-019-0509-5},
  volume = 16,
  year = 2019
}

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