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 RoseShvetank 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^*

^*Korrespondierende/r Autor/-in für diese Arbeit

Klinik für Kinder- und Jugendmedizin

212 Zitate (Scopus)

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.

Originalsprache	Englisch
Aufsatznummer	12846
Zeitschrift	Nature Communications
Jahrgang	7
ISSN	1751-8628
DOIs	https://doi.org/10.1038/ncomms12846
Publikationsstatus	Veröffentlicht - 26.09.2016

Fördermittel

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

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 3 – Gesundheit und Wohlergehen

Strategische Forschungsbereiche und Zentren

Forschungsschwerpunkt: Gehirn, Hormone, Verhalten - Center for Brain, Behavior and Metabolism (CBBM)

Dokumente

10.1038/ncomms12846

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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, Artikel 12846. https://doi.org/10.1038/ncomms12846

@article{52fc0500e39b4e048a2b14e55bc6525e,

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 = "Funding Information: This work is supported by NIH grants: R01GM098316, U54HL127624 and U54CA189201 to A.M Publisher Copyright: {\textcopyright} The Author(s) 2016. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.",

year = "2016",

month = sep,

day = "26",

doi = "10.1038/ncomms12846",

language = "English",

volume = "7",

journal = "Nature Communications",

issn = "1751-8628",

publisher = "John Wiley \& Sons Inc.",

}

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, Jg. 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

N1 - Funding Information: This work is supported by NIH grants: R01GM098316, U54HL127624 and U54CA189201 to A.M Publisher Copyright: © The Author(s) 2016. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.

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.

UR - https://www.scopus.com/pages/publications/84989257090

U2 - 10.1038/ncomms12846

DO - 10.1038/ncomms12846

M3 - Journal articles

AN - SCOPUS:84989257090

SN - 1751-8628

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

Fördermittel

UN SDGs

Strategische Forschungsbereiche und Zentren

Dokumente

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