Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

Zichen Wang; Caroline D. Monteiro; Kathleen M. Jagodnik; Nicolas F. Fernandez; Gregory W. Gundersen; Andrew D. Rouillard; Sherry L. Jenkins; Axel S. Feldmann; Kevin S. Hu; Michael G. McDermott; Qiaonan Duan; Neil R. Clark; Matthew R. Jones; Yan Kou; Troy Goff; Holly Woodland; Fabio M.R. Amaral; Gregory L. Szeto; Oliver Fuchs; Sophia M. Schüssler-Fiorenza Rose; Shvetank Sharma; Uwe Schwartz; Xabier Bengoetxea Bausela; Maciej Szymkiewicz; Vasileios Maroulis; Anton Salykin; Carolina M. Barra; Candice D. Kruth; Nicholas J. Bongio; Vaibhav Mathur; Radmila D. Todoric; Udi E. Rubin; Apostolos Malatras; Carl T. Fulp; John A. Galindo; Ruta Motiejunaite; Christoph Jüschke; Philip C. Dishuck; Katharina Lahl; Mohieddin Jafari; Sara Aibar; Apostolos Zaravinos; Linda H. Steenhuizen; Lindsey R. Allison; Pablo Gamallo; Fernando De Andres Segura; Tyler Dae Devlin; Vicente Pérez-García; Avi Ma'ayan

doi:10.1038/ncomms12846

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

Zichen Wang
, Caroline D. Monteiro
, Kathleen M. Jagodnik
, Nicolas F. Fernandez
, Gregory W. Gundersen
, Andrew D. Rouillard
, Sherry L. Jenkins
, Axel S. Feldmann
, Kevin S. Hu
, Michael G. McDermott
, Qiaonan Duan
, Neil R. Clark
, Matthew R. Jones
, Yan Kou
, Troy Goff
, Holly Woodland
, Fabio M.R. Amaral
, Gregory L. Szeto
, Oliver Fuchs
, Sophia M. Schüssler-Fiorenza Rose

Shvetank Sharma, Uwe Schwartz, Xabier Bengoetxea Bausela, Maciej Szymkiewicz, Vasileios Maroulis, Anton Salykin, Carolina M. Barra, Candice D. Kruth, Nicholas J. Bongio, Vaibhav Mathur, Radmila D. Todoric, Udi E. Rubin, Apostolos Malatras, Carl T. Fulp, John A. Galindo, Ruta Motiejunaite, Christoph Jüschke, Philip C. Dishuck, Katharina Lahl, Mohieddin Jafari, Sara Aibar, Apostolos Zaravinos, Linda H. Steenhuizen, Lindsey R. Allison, Pablo Gamallo, Fernando De Andres Segura, Tyler Dae Devlin, Vicente Pérez-García, Avi Ma'ayan

Icahn School of Medicine at Mount Sinai
NASA Glenn Research Center
Baylor College of Medicine
the Fairway
University of Nottingham
Massachusetts Institute of Technology
Ludwig Maximilian University of Munich
Department of Veterans Affairs
Stanford University
Institute of Liver and Biliary Sciences
University of Regensburg
University of Navarra
Polish Academy of Sciences
Masaryk University
Hospital del Mar
Shenandoah University
IBM
Columbia University
Centre de Recherche en Myologie
Universidad Nacional de Colombia
Brigham and Women’s Hospital
University of Oldenburg
Technical University of Denmark
Pasteur Institute of Iran
Institute for Researches in Fundamental Sciences
Universidad de Salamanca
Karolinska Institutet
European University Cyprus
University of Extremadura
CSIC - National Center for Biotechnology

Research output: Contribution to journal › Article › peer-review

211 Scopus citations

Abstract

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

Original language	English
Article number	12846
Journal	Nature Communications
Volume	7
DOIs	https://doi.org/10.1038/ncomms12846
State	Published - 26 Sep 2016
Externally published	Yes

Bibliographical note

Publisher Copyright:
© The Author(s) 2016.

Funding

This work is supported by NIH grants: R01GM098316, U54HL127624 and U54CA189201 to A.M

Funders	Funder number
National Institutes of Health	U54CA189201, U54HL127624, R01GM098316

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1038/ncomms12846

Cite this

Wang, Z., Monteiro, C. D., Jagodnik, K. M., Fernandez, N. F., Gundersen, G. W., Rouillard, A. D., Jenkins, S. L., Feldmann, A. S., Hu, K. S., McDermott, M. G., Duan, Q., Clark, N. R., Jones, M. R., Kou, Y., Goff, T., Woodland, H., Amaral, F. M. R., Szeto, G. L., Fuchs, O., ... Ma'ayan, A. (2016). Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd. Nature Communications, 7, Article 12846. https://doi.org/10.1038/ncomms12846

@article{2bc07f84c87d4b1e87152d71c68864ce,

title = "Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd",

abstract = "Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.",

author = "Zichen Wang and Monteiro, \{Caroline D.\} and Jagodnik, \{Kathleen M.\} and Fernandez, \{Nicolas F.\} and Gundersen, \{Gregory W.\} and Rouillard, \{Andrew D.\} and Jenkins, \{Sherry L.\} and Feldmann, \{Axel S.\} and Hu, \{Kevin S.\} and McDermott, \{Michael G.\} and Qiaonan Duan and Clark, \{Neil R.\} and Jones, \{Matthew R.\} and Yan Kou and Troy Goff and Holly Woodland and Amaral, \{Fabio M.R.\} and Szeto, \{Gregory L.\} and Oliver Fuchs and \{Sch{\"u}ssler-Fiorenza Rose\}, \{Sophia M.\} and Shvetank Sharma and Uwe Schwartz and Bausela, \{Xabier Bengoetxea\} and Maciej Szymkiewicz and Vasileios Maroulis and Anton Salykin and Barra, \{Carolina M.\} and Kruth, \{Candice D.\} and Bongio, \{Nicholas J.\} and Vaibhav Mathur and Todoric, \{Radmila D.\} and Rubin, \{Udi E.\} and Apostolos Malatras and Fulp, \{Carl T.\} and Galindo, \{John A.\} and Ruta Motiejunaite and Christoph J{\"u}schke and Dishuck, \{Philip C.\} and Katharina Lahl and Mohieddin Jafari and Sara Aibar and Apostolos Zaravinos and Steenhuizen, \{Linda H.\} and Allison, \{Lindsey R.\} and Pablo Gamallo and \{De Andres Segura\}, Fernando and \{Dae Devlin\}, Tyler and Vicente P{\'e}rez-Garc{\'i}a and Avi Ma'ayan",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2016.",

year = "2016",

month = sep,

day = "26",

doi = "10.1038/ncomms12846",

language = "אנגלית",

volume = "7",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Research",

}

Wang, Z, Monteiro, CD, Jagodnik, KM, Fernandez, NF, Gundersen, GW, Rouillard, AD, Jenkins, SL, Feldmann, AS, Hu, KS, McDermott, MG, Duan, Q, Clark, NR, Jones, MR, Kou, Y, Goff, T, Woodland, H, Amaral, FMR, Szeto, GL, Fuchs, O, Schüssler-Fiorenza Rose, SM, Sharma, S, Schwartz, U, Bausela, XB, Szymkiewicz, M, Maroulis, V, Salykin, A, Barra, CM, Kruth, CD, Bongio, NJ, Mathur, V, Todoric, RD, Rubin, UE, Malatras, A, Fulp, CT, Galindo, JA, Motiejunaite, R, Jüschke, C, Dishuck, PC, Lahl, K, Jafari, M, Aibar, S, Zaravinos, A, Steenhuizen, LH, Allison, LR, Gamallo, P, De Andres Segura, F, Dae Devlin, T, Pérez-García, V & Ma'ayan, A 2016, 'Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd', Nature Communications, vol. 7, 12846. https://doi.org/10.1038/ncomms12846

TY - JOUR

T1 - Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

AU - Wang, Zichen

AU - Monteiro, Caroline D.

AU - Jagodnik, Kathleen M.

AU - Fernandez, Nicolas F.

AU - Gundersen, Gregory W.

AU - Rouillard, Andrew D.

AU - Jenkins, Sherry L.

AU - Feldmann, Axel S.

AU - Hu, Kevin S.

AU - McDermott, Michael G.

AU - Duan, Qiaonan

AU - Clark, Neil R.

AU - Jones, Matthew R.

AU - Kou, Yan

AU - Goff, Troy

AU - Woodland, Holly

AU - Amaral, Fabio M.R.

AU - Szeto, Gregory L.

AU - Fuchs, Oliver

AU - Schüssler-Fiorenza Rose, Sophia M.

AU - Sharma, Shvetank

AU - Schwartz, Uwe

AU - Bausela, Xabier Bengoetxea

AU - Szymkiewicz, Maciej

AU - Maroulis, Vasileios

AU - Salykin, Anton

AU - Barra, Carolina M.

AU - Kruth, Candice D.

AU - Bongio, Nicholas J.

AU - Mathur, Vaibhav

AU - Todoric, Radmila D.

AU - Rubin, Udi E.

AU - Malatras, Apostolos

AU - Fulp, Carl T.

AU - Galindo, John A.

AU - Motiejunaite, Ruta

AU - Jüschke, Christoph

AU - Dishuck, Philip C.

AU - Lahl, Katharina

AU - Jafari, Mohieddin

AU - Aibar, Sara

AU - Zaravinos, Apostolos

AU - Steenhuizen, Linda H.

AU - Allison, Lindsey R.

AU - Gamallo, Pablo

AU - De Andres Segura, Fernando

AU - Dae Devlin, Tyler

AU - Pérez-García, Vicente

AU - Ma'ayan, Avi

PY - 2016/9/26

Y1 - 2016/9/26

N2 - Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

AB - Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

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U2 - 10.1038/ncomms12846

DO - 10.1038/ncomms12846

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AN - SCOPUS:84989257090

SN - 2041-1723

VL - 7

JO - Nature Communications

JF - Nature Communications

M1 - 12846

ER -

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

Abstract

Bibliographical note

Funding

UN SDGs

Access to Document

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