The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

Leming Shi; Gregory Campbell; Wendell D. Jones; Fabien Campagne; Zhining Wen; Stephen J. Walker; Zhenqiang Su; Tzu Ming Chu; Federico M. Goodsaid; Lajos Pusztai; John D. Shaughnessy; André Oberthuer; Russell S. Thomas; Richard S. Paules; Mark Fielden; Bart Barlogie; Weijie Chen; Pan Du; Matthias Fischer; Cesare Furlanello; Brandon D. Gallas; Xijin Ge; Dalila B. Megherbi; W. Fraser Symmans; May D. Wang; John Zhang; Hans Bitter; Benedikt Brors; Pierre R. Bushel; Max Bylesjo; Minjun Chen; Jie Cheng; Jing Cheng; Jeff Chou; Timothy S. Davison; Mauro Delorenzi; Youping Deng; Viswanath Devanarayan; David J. Dix; Joaquin Dopazo; Kevin C. Dorff; Fathi Elloumi; Jianqing Fan; Shicai Fan; Xiaohui Fan; Hong Fang; Nina Gonzaludo; Kenneth R. Hess; Huixiao Hong; Jun Huan; Rafael A. Irizarry; Richard Judson; Dilafruz Juraeva; Samir Lababidi; Christophe G. Lambert; Li Li; Yanen Li; Zhen Li; Simon M. Lin; Guozhen Liu; Edward K. Lobenhofer; Jun Luo; Wen Luo; Matthew N. McCall; Yuri Nikolsky; Gene A. Pennello; Roger G. Perkins; Reena Philip; Vlad Popovici; Nathan D. Price; Feng Qian; Andreas Scherer; Tieliu Shi; Weiwei Shi; Jaeyun Sung; Danielle Thierry-Mieg; Jean Thierry-Mieg; Venkata Thodima; Johan Trygg; Lakshmi Vishnuvajjala; Sue Jane Wang; Jianping Wu; Yichao Wu; Qian Xie; Waleed A. Yousef; Liang Zhang; Xuegong Zhang; Sheng Zhong; Yiming Zhou; Sheng Zhu; Dhivya Arasappan; Wenjun Bao; Anne Bergstrom Lucas; Frank Berthold; Richard J. Brennan; Andreas Buness; Jennifer G. Catalano; Chang Chang; Rong Chen; Yiyu Cheng; Jian Cui; Wendy Czika; Francesca Demichelis; Xutao Deng; Damir Dosymbekov; Roland Eils; Yang Feng; Jennifer Fostel; Stephanie Fulmer-Smentek; James C. Fuscoe; Laurent Gatto; Weigong Ge; Darlene R. Goldstein; Li Guo; Donald N. Halbert; Jing Han; Stephen C. Harris; Christos Hatzis; Damir Herman; Jianping Huang; Roderick V. Jensen; Rui Jiang; Charles D. Johnson; Giuseppe Jurman; Yvonne Kahlert; Sadik A. Khuder; Matthias Kohl; Jianying Li; Li Lee; Menglong Li; Quan Zhen Li; Shao Li; Zhiguang Li; Jie Liu; Ying Liu; Zhichao Liu; Lu Meng; Manuel Madera; Francisco Martinez-Murillo; Ignacio Medina; Joseph Meehan; Kelci Miclaus; Richard A. Moffitt; David Montaner; Piali Mukherjee; George J. Mulligan; Padraic Neville; Tatiana Nikolskaya; Baitang Ning; Grier P. Page; Joel Parker; R. Mitchell Parry; Xuejun Peng; Ron L. Peterson; John H. Phan; Brian Quanz; Yi Ren; Samantha Riccadonna; Alan H. Roter; Frank W. Samuelson; Martin M. Schumacher; Joseph D. Shambaugh; Qiang Shi; Richard Shippy; Shengzhu Si; Aaron Smalter; Christos Sotiriou; Mat Soukup; Frank Staedtler; Guido Steiner; Todd H. Stokes; Qinglan Sun; Pei Yi Tan; Rong Tang; Zivana Tezak; Brett Thorn; Marina Tsyganova; Yaron Turpaz; Silvia C. Vega; Roberto Visintainer; Juergen Von Frese; Charles Wang; Eric Wang; Junwei Wang; Wei Wang; Frank Westermann; James C. Willey; Matthew Woods; Shujian Wu; Nianqing Xiao; Joshua Xu; Lei Xu; Lun Yang; Xiao Zeng; Jialu Zhang; Li Zheng; Min Zhang; Chen Zhao; Raj K. Puri; Uwe Scherf; Weida Tong; Russell D. Wolfinger

doi:10.1038/nbt.1665

The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

Leming Shi, Gregory Campbell, Wendell D. Jones, Fabien Campagne, Zhining Wen, Stephen J. Walker, Zhenqiang Su, Tzu Ming Chu, Federico M. Goodsaid, Lajos Pusztai, John D. Shaughnessy, André Oberthuer, Russell S. Thomas, Richard S. Paules, Mark Fielden, Bart Barlogie, Weijie Chen, Pan Du, Matthias Fischer, Cesare FurlanelloBrandon D. Gallas, Xijin Ge, Dalila B. Megherbi, W. Fraser Symmans, May D. Wang, John Zhang, Hans Bitter, Benedikt Brors, Pierre R. Bushel, Max Bylesjo, Minjun Chen, Jie Cheng, Jing Cheng, Jeff Chou, Timothy S. Davison, Mauro Delorenzi, Youping Deng, Viswanath Devanarayan, David J. Dix, Joaquin Dopazo, Kevin C. Dorff, Fathi Elloumi, Jianqing Fan, Shicai Fan, Xiaohui Fan, Hong Fang, Nina Gonzaludo, Kenneth R. Hess, Huixiao Hong, Jun Huan, Rafael A. Irizarry, Richard Judson, Dilafruz Juraeva, Samir Lababidi, Christophe G. Lambert, Li Li, Yanen Li, Zhen Li, Simon M. Lin, Guozhen Liu, Edward K. Lobenhofer, Jun Luo, Wen Luo, Matthew N. McCall, Yuri Nikolsky, Gene A. Pennello, Roger G. Perkins, Reena Philip, Vlad Popovici, Nathan D. Price, Feng Qian, Andreas Scherer, Tieliu Shi, Weiwei Shi, Jaeyun Sung, Danielle Thierry-Mieg, Jean Thierry-Mieg, Venkata Thodima, Johan Trygg, Lakshmi Vishnuvajjala, Sue Jane Wang, Jianping Wu, Yichao Wu, Qian Xie, Waleed A. Yousef, Liang Zhang, Xuegong Zhang, Sheng Zhong, Yiming Zhou, Sheng Zhu, Dhivya Arasappan, Wenjun Bao, Anne Bergstrom Lucas, Frank Berthold, Richard J. Brennan, Andreas Buness, Jennifer G. Catalano, Chang Chang, Rong Chen, Yiyu Cheng, Jian Cui, Wendy Czika, Francesca Demichelis, Xutao Deng, Damir Dosymbekov, Roland Eils, Yang Feng, Jennifer Fostel, Stephanie Fulmer-Smentek, James C. Fuscoe, Laurent Gatto, Weigong Ge, Darlene R. Goldstein, Li Guo, Donald N. Halbert, Jing Han, Stephen C. Harris, Christos Hatzis, Damir Herman, Jianping Huang, Roderick V. Jensen, Rui Jiang, Charles D. Johnson, Giuseppe Jurman, Yvonne Kahlert, Sadik A. Khuder, Matthias Kohl, Jianying Li, Li Lee, Menglong Li, Quan Zhen Li, Shao Li, Zhiguang Li, Jie Liu, Ying Liu, Zhichao Liu, Lu Meng, Manuel Madera, Francisco Martinez-Murillo, Ignacio Medina, Joseph Meehan, Kelci Miclaus, Richard A. Moffitt, David Montaner, Piali Mukherjee, George J. Mulligan, Padraic Neville, Tatiana Nikolskaya, Baitang Ning, Grier P. Page, Joel Parker, R. Mitchell Parry, Xuejun Peng, Ron L. Peterson, John H. Phan, Brian Quanz, Yi Ren, Samantha Riccadonna, Alan H. Roter, Frank W. Samuelson, Martin M. Schumacher, Joseph D. Shambaugh, Qiang Shi, Richard Shippy, Shengzhu Si, Aaron Smalter, Christos Sotiriou, Mat Soukup, Frank Staedtler, Guido Steiner, Todd H. Stokes, Qinglan Sun, Pei Yi Tan, Rong Tang, Zivana Tezak, Brett Thorn, Marina Tsyganova, Yaron Turpaz, Silvia C. Vega, Roberto Visintainer, Juergen Von Frese, Charles Wang, Eric Wang, Junwei Wang, Wei Wang, Frank Westermann, James C. Willey, Matthew Woods, Shujian Wu, Nianqing Xiao, Joshua Xu, Lei Xu, Lun Yang, Xiao Zeng, Jialu Zhang, Li Zheng, Min Zhang, Chen Zhao, Raj K. Puri, Uwe Scherf, Weida Tong, Russell D. Wolfinger

Global Public Health

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

Abstract

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Original language	English (US)
Pages (from-to)	827-838
Number of pages	12
Journal	Nature Biotechnology
Volume	28
Issue number	8
DOIs	https://doi.org/10.1038/nbt.1665
State	Published - Aug 2010

ASJC Scopus subject areas

Biotechnology
Bioengineering
Applied Microbiology and Biotechnology
Molecular Medicine
Biomedical Engineering

Access to Document

10.1038/nbt.1665

Cite this

Shi, L., Campbell, G., Jones, W. D., Campagne, F., Wen, Z., Walker, S. J., Su, Z., Chu, T. M., Goodsaid, F. M., Pusztai, L., Shaughnessy, J. D., Oberthuer, A., Thomas, R. S., Paules, R. S., Fielden, M., Barlogie, B., Chen, W., Du, P., Fischer, M., ... Wolfinger, R. D. (2010). The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature Biotechnology, 28(8), 827-838. https://doi.org/10.1038/nbt.1665

Shi, L, Campbell, G, Jones, WD, Campagne, F, Wen, Z, Walker, SJ, Su, Z, Chu, TM, Goodsaid, FM, Pusztai, L, Shaughnessy, JD, Oberthuer, A, Thomas, RS, Paules, RS, Fielden, M, Barlogie, B, Chen, W, Du, P, Fischer, M, Furlanello, C, Gallas, BD, Ge, X, Megherbi, DB, Symmans, WF, Wang, MD, Zhang, J, Bitter, H, Brors, B, Bushel, PR, Bylesjo, M, Chen, M, Cheng, J, Cheng, J, Chou, J, Davison, TS, Delorenzi, M, Deng, Y, Devanarayan, V, Dix, DJ, Dopazo, J, Dorff, KC, Elloumi, F, Fan, J, Fan, S, Fan, X, Fang, H, Gonzaludo, N, Hess, KR, Hong, H, Huan, J, Irizarry, RA, Judson, R, Juraeva, D, Lababidi, S, Lambert, CG, Li, L, Li, Y, Li, Z, Lin, SM, Liu, G, Lobenhofer, EK, Luo, J, Luo, W, McCall, MN, Nikolsky, Y, Pennello, GA, Perkins, RG, Philip, R, Popovici, V, Price, ND, Qian, F, Scherer, A, Shi, T, Shi, W, Sung, J, Thierry-Mieg, D, Thierry-Mieg, J, Thodima, V, Trygg, J, Vishnuvajjala, L, Wang, SJ, Wu, J, Wu, Y, Xie, Q, Yousef, WA, Zhang, L, Zhang, X, Zhong, S, Zhou, Y, Zhu, S, Arasappan, D, Bao, W, Lucas, AB, Berthold, F, Brennan, RJ, Buness, A, Catalano, JG, Chang, C, Chen, R, Cheng, Y, Cui, J, Czika, W, Demichelis, F, Deng, X, Dosymbekov, D, Eils, R, Feng, Y, Fostel, J, Fulmer-Smentek, S, Fuscoe, JC, Gatto, L, Ge, W, Goldstein, DR, Guo, L, Halbert, DN, Han, J, Harris, SC, Hatzis, C, Herman, D, Huang, J, Jensen, RV, Jiang, R, Johnson, CD, Jurman, G, Kahlert, Y, Khuder, SA, Kohl, M, Li, J, Lee, L, Li, M, Li, QZ, Li, S, Li, Z, Liu, J, Liu, Y, Liu, Z, Meng, L, Madera, M, Martinez-Murillo, F, Medina, I, Meehan, J, Miclaus, K, Moffitt, RA, Montaner, D, Mukherjee, P, Mulligan, GJ, Neville, P, Nikolskaya, T, Ning, B, Page, GP, Parker, J, Parry, RM, Peng, X, Peterson, RL, Phan, JH, Quanz, B, Ren, Y, Riccadonna, S, Roter, AH, Samuelson, FW, Schumacher, MM, Shambaugh, JD, Shi, Q, Shippy, R, Si, S, Smalter, A, Sotiriou, C, Soukup, M, Staedtler, F, Steiner, G, Stokes, TH, Sun, Q, Tan, PY, Tang, R, Tezak, Z, Thorn, B, Tsyganova, M, Turpaz, Y, Vega, SC, Visintainer, R, Von Frese, J, Wang, C, Wang, E, Wang, J, Wang, W, Westermann, F, Willey, JC, Woods, M, Wu, S, Xiao, N, Xu, J, Xu, L, Yang, L, Zeng, X, Zhang, J, Zheng, L, Zhang, M, Zhao, C, Puri, RK, Scherf, U, Tong, W & Wolfinger, RD 2010, 'The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models', Nature Biotechnology, vol. 28, no. 8, pp. 827-838. https://doi.org/10.1038/nbt.1665

@article{e0513ee1f38643e599ddae3ef6b3fe2c,

title = "The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models",

abstract = "Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.",

author = "Leming Shi and Gregory Campbell and Jones, {Wendell D.} and Fabien Campagne and Zhining Wen and Walker, {Stephen J.} and Zhenqiang Su and Chu, {Tzu Ming} and Goodsaid, {Federico M.} and Lajos Pusztai and Shaughnessy, {John D.} and Andr{\'e} Oberthuer and Thomas, {Russell S.} and Paules, {Richard S.} and Mark Fielden and Bart Barlogie and Weijie Chen and Pan Du and Matthias Fischer and Cesare Furlanello and Gallas, {Brandon D.} and Xijin Ge and Megherbi, {Dalila B.} and Symmans, {W. Fraser} and Wang, {May D.} and John Zhang and Hans Bitter and Benedikt Brors and Bushel, {Pierre R.} and Max Bylesjo and Minjun Chen and Jie Cheng and Jing Cheng and Jeff Chou and Davison, {Timothy S.} and Mauro Delorenzi and Youping Deng and Viswanath Devanarayan and Dix, {David J.} and Joaquin Dopazo and Dorff, {Kevin C.} and Fathi Elloumi and Jianqing Fan and Shicai Fan and Xiaohui Fan and Hong Fang and Nina Gonzaludo and Hess, {Kenneth R.} and Huixiao Hong and Jun Huan and Irizarry, {Rafael A.} and Richard Judson and Dilafruz Juraeva and Samir Lababidi and Lambert, {Christophe G.} and Li Li and Yanen Li and Zhen Li and Lin, {Simon M.} and Guozhen Liu and Lobenhofer, {Edward K.} and Jun Luo and Wen Luo and McCall, {Matthew N.} and Yuri Nikolsky and Pennello, {Gene A.} and Perkins, {Roger G.} and Reena Philip and Vlad Popovici and Price, {Nathan D.} and Feng Qian and Andreas Scherer and Tieliu Shi and Weiwei Shi and Jaeyun Sung and Danielle Thierry-Mieg and Jean Thierry-Mieg and Venkata Thodima and Johan Trygg and Lakshmi Vishnuvajjala and Wang, {Sue Jane} and Jianping Wu and Yichao Wu and Qian Xie and Yousef, {Waleed A.} and Liang Zhang and Xuegong Zhang and Sheng Zhong and Yiming Zhou and Sheng Zhu and Dhivya Arasappan and Wenjun Bao and Lucas, {Anne Bergstrom} and Frank Berthold and Brennan, {Richard J.} and Andreas Buness and Catalano, {Jennifer G.} and Chang Chang and Rong Chen and Yiyu Cheng and Jian Cui and Wendy Czika and Francesca Demichelis and Xutao Deng and Damir Dosymbekov and Roland Eils and Yang Feng and Jennifer Fostel and Stephanie Fulmer-Smentek and Fuscoe, {James C.} and Laurent Gatto and Weigong Ge and Goldstein, {Darlene R.} and Li Guo and Halbert, {Donald N.} and Jing Han and Harris, {Stephen C.} and Christos Hatzis and Damir Herman and Jianping Huang and Jensen, {Roderick V.} and Rui Jiang and Johnson, {Charles D.} and Giuseppe Jurman and Yvonne Kahlert and Khuder, {Sadik A.} and Matthias Kohl and Jianying Li and Li Lee and Menglong Li and Li, {Quan Zhen} and Shao Li and Zhiguang Li and Jie Liu and Ying Liu and Zhichao Liu and Lu Meng and Manuel Madera and Francisco Martinez-Murillo and Ignacio Medina and Joseph Meehan and Kelci Miclaus and Moffitt, {Richard A.} and David Montaner and Piali Mukherjee and Mulligan, {George J.} and Padraic Neville and Tatiana Nikolskaya and Baitang Ning and Page, {Grier P.} and Joel Parker and Parry, {R. Mitchell} and Xuejun Peng and Peterson, {Ron L.} and Phan, {John H.} and Brian Quanz and Yi Ren and Samantha Riccadonna and Roter, {Alan H.} and Samuelson, {Frank W.} and Schumacher, {Martin M.} and Shambaugh, {Joseph D.} and Qiang Shi and Richard Shippy and Shengzhu Si and Aaron Smalter and Christos Sotiriou and Mat Soukup and Frank Staedtler and Guido Steiner and Stokes, {Todd H.} and Qinglan Sun and Tan, {Pei Yi} and Rong Tang and Zivana Tezak and Brett Thorn and Marina Tsyganova and Yaron Turpaz and Vega, {Silvia C.} and Roberto Visintainer and {Von Frese}, Juergen and Charles Wang and Eric Wang and Junwei Wang and Wei Wang and Frank Westermann and Willey, {James C.} and Matthew Woods and Shujian Wu and Nianqing Xiao and Joshua Xu and Lei Xu and Lun Yang and Xiao Zeng and Jialu Zhang and Li Zheng and Min Zhang and Chen Zhao and Puri, {Raj K.} and Uwe Scherf and Weida Tong and Wolfinger, {Russell D.}",

note = "Funding Information: The MAQC-II project was funded in part by the FDA{\textquoteright}s Office of Critical Path Programs (to L.S.). Participants from the National Institutes of Health (NIH) were supported by the Intramural Research Program of NIH, Bethesda, Maryland or the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, North Carolina. J.F. was supported by the Division of Intramural Research of the NIEHS under contract HHSN273200700046U. Participants from the Johns Hopkins University were supported by grants from the NIH (1R01GM083084-01 and 1R01RR021967-01A2 to R.A.I. and T32GM074906 to M.M.). Participants from the Weill Medical College of Cornell University were partially supported by the Biomedical Informatics Core of the Institutional Clinical and Translational Science Award RFA-RM-07-002. F.C. acknowledges resources from The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine and from the David A. Cofrin Center for Biomedical Information at Weill Cornell. The data set from The Hamner Institutes for Health Sciences was supported by a grant from the American Chemistry Council{\textquoteright}s Long Range Research Initiative. The breast cancer data set was generated with support of grants from NIH (R-01 to L.P.), The Breast Cancer Research Foundation (to L.P. and W.F.S.) and the Faculty Incentive Funds of the University of Texas MD Anderson Cancer Center (to W.F.S.). The data set from the University of Arkansas for Medical Sciences was supported by National Cancer Institute (NCI) PO1 grant CA55819-01A1, NCI R33 Grant CA97513-01, Donna D. and Donald M. Lambert Lebow Fund to Cure Myeloma and Nancy and Steven Grand Foundation. We are grateful to the individuals whose gene expression data were used in this study. All MAQC-II participants freely donated their time and reagents for the completion and analyses of the MAQC-II project. The MAQC-II consortium also thanks R. O{\textquoteright}Neill for his encouragement and coordination among FDA Centers on the formation of the RBWG. The MAQC-II consortium gratefully dedicates this work in memory of R.F. Wagner who enthusiastically worked on the MAQC-II project and inspired many of us until he unexpectedly passed away in June 2008.",

year = "2010",

month = aug,

doi = "10.1038/nbt.1665",

language = "English (US)",

volume = "28",

pages = "827--838",

journal = "Nature Biotechnology",

issn = "1087-0156",

publisher = "Nature Research",

number = "8",

}

TY - JOUR

T1 - The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

AU - Shi, Leming

AU - Campbell, Gregory

AU - Jones, Wendell D.

AU - Campagne, Fabien

AU - Wen, Zhining

AU - Walker, Stephen J.

AU - Su, Zhenqiang

AU - Chu, Tzu Ming

AU - Goodsaid, Federico M.

AU - Pusztai, Lajos

AU - Shaughnessy, John D.

AU - Oberthuer, André

AU - Thomas, Russell S.

AU - Paules, Richard S.

AU - Fielden, Mark

AU - Barlogie, Bart

AU - Chen, Weijie

AU - Du, Pan

AU - Fischer, Matthias

AU - Furlanello, Cesare

AU - Gallas, Brandon D.

AU - Ge, Xijin

AU - Megherbi, Dalila B.

AU - Symmans, W. Fraser

AU - Wang, May D.

AU - Zhang, John

AU - Bitter, Hans

AU - Brors, Benedikt

AU - Bushel, Pierre R.

AU - Bylesjo, Max

AU - Chen, Minjun

AU - Cheng, Jie

AU - Cheng, Jing

AU - Chou, Jeff

AU - Davison, Timothy S.

AU - Delorenzi, Mauro

AU - Deng, Youping

AU - Devanarayan, Viswanath

AU - Dix, David J.

AU - Dopazo, Joaquin

AU - Dorff, Kevin C.

AU - Elloumi, Fathi

AU - Fan, Jianqing

AU - Fan, Shicai

AU - Fan, Xiaohui

AU - Fang, Hong

AU - Gonzaludo, Nina

AU - Hess, Kenneth R.

AU - Hong, Huixiao

AU - Huan, Jun

AU - Irizarry, Rafael A.

AU - Judson, Richard

AU - Juraeva, Dilafruz

AU - Lababidi, Samir

AU - Lambert, Christophe G.

AU - Li, Li

AU - Li, Yanen

AU - Li, Zhen

AU - Lin, Simon M.

AU - Liu, Guozhen

AU - Lobenhofer, Edward K.

AU - Luo, Jun

AU - Luo, Wen

AU - McCall, Matthew N.

AU - Nikolsky, Yuri

AU - Pennello, Gene A.

AU - Perkins, Roger G.

AU - Philip, Reena

AU - Popovici, Vlad

AU - Price, Nathan D.

AU - Qian, Feng

AU - Scherer, Andreas

AU - Shi, Tieliu

AU - Shi, Weiwei

AU - Sung, Jaeyun

AU - Thierry-Mieg, Danielle

AU - Thierry-Mieg, Jean

AU - Thodima, Venkata

AU - Trygg, Johan

AU - Vishnuvajjala, Lakshmi

AU - Wang, Sue Jane

AU - Wu, Jianping

AU - Wu, Yichao

AU - Xie, Qian

AU - Yousef, Waleed A.

AU - Zhang, Liang

AU - Zhang, Xuegong

AU - Zhong, Sheng

AU - Zhou, Yiming

AU - Zhu, Sheng

AU - Arasappan, Dhivya

AU - Bao, Wenjun

AU - Lucas, Anne Bergstrom

AU - Berthold, Frank

AU - Brennan, Richard J.

AU - Buness, Andreas

AU - Catalano, Jennifer G.

AU - Chang, Chang

AU - Chen, Rong

AU - Cheng, Yiyu

AU - Cui, Jian

AU - Czika, Wendy

AU - Demichelis, Francesca

AU - Deng, Xutao

AU - Dosymbekov, Damir

AU - Eils, Roland

AU - Feng, Yang

AU - Fostel, Jennifer

AU - Fulmer-Smentek, Stephanie

AU - Fuscoe, James C.

AU - Gatto, Laurent

AU - Ge, Weigong

AU - Goldstein, Darlene R.

AU - Guo, Li

AU - Halbert, Donald N.

AU - Han, Jing

AU - Harris, Stephen C.

AU - Hatzis, Christos

AU - Herman, Damir

AU - Huang, Jianping

AU - Jensen, Roderick V.

AU - Jiang, Rui

AU - Johnson, Charles D.

AU - Jurman, Giuseppe

AU - Kahlert, Yvonne

AU - Khuder, Sadik A.

AU - Kohl, Matthias

AU - Li, Jianying

AU - Lee, Li

AU - Li, Menglong

AU - Li, Quan Zhen

AU - Li, Shao

AU - Li, Zhiguang

AU - Liu, Jie

AU - Liu, Ying

AU - Liu, Zhichao

AU - Meng, Lu

AU - Madera, Manuel

AU - Martinez-Murillo, Francisco

AU - Medina, Ignacio

AU - Meehan, Joseph

AU - Miclaus, Kelci

AU - Moffitt, Richard A.

AU - Montaner, David

AU - Mukherjee, Piali

AU - Mulligan, George J.

AU - Neville, Padraic

AU - Nikolskaya, Tatiana

AU - Ning, Baitang

AU - Page, Grier P.

AU - Parker, Joel

AU - Parry, R. Mitchell

AU - Peng, Xuejun

AU - Peterson, Ron L.

AU - Phan, John H.

AU - Quanz, Brian

AU - Ren, Yi

AU - Riccadonna, Samantha

AU - Roter, Alan H.

AU - Samuelson, Frank W.

AU - Schumacher, Martin M.

AU - Shambaugh, Joseph D.

AU - Shi, Qiang

AU - Shippy, Richard

AU - Si, Shengzhu

AU - Smalter, Aaron

AU - Sotiriou, Christos

AU - Soukup, Mat

AU - Staedtler, Frank

AU - Steiner, Guido

AU - Stokes, Todd H.

AU - Sun, Qinglan

AU - Tan, Pei Yi

AU - Tang, Rong

AU - Tezak, Zivana

AU - Thorn, Brett

AU - Tsyganova, Marina

AU - Turpaz, Yaron

AU - Vega, Silvia C.

AU - Visintainer, Roberto

AU - Von Frese, Juergen

AU - Wang, Charles

AU - Wang, Eric

AU - Wang, Junwei

AU - Wang, Wei

AU - Westermann, Frank

AU - Willey, James C.

AU - Woods, Matthew

AU - Wu, Shujian

AU - Xiao, Nianqing

AU - Xu, Joshua

AU - Xu, Lei

AU - Yang, Lun

AU - Zeng, Xiao

AU - Zhang, Jialu

AU - Zheng, Li

AU - Zhang, Min

AU - Zhao, Chen

AU - Puri, Raj K.

AU - Scherf, Uwe

AU - Tong, Weida

AU - Wolfinger, Russell D.

N1 - Funding Information: The MAQC-II project was funded in part by the FDA’s Office of Critical Path Programs (to L.S.). Participants from the National Institutes of Health (NIH) were supported by the Intramural Research Program of NIH, Bethesda, Maryland or the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, North Carolina. J.F. was supported by the Division of Intramural Research of the NIEHS under contract HHSN273200700046U. Participants from the Johns Hopkins University were supported by grants from the NIH (1R01GM083084-01 and 1R01RR021967-01A2 to R.A.I. and T32GM074906 to M.M.). Participants from the Weill Medical College of Cornell University were partially supported by the Biomedical Informatics Core of the Institutional Clinical and Translational Science Award RFA-RM-07-002. F.C. acknowledges resources from The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine and from the David A. Cofrin Center for Biomedical Information at Weill Cornell. The data set from The Hamner Institutes for Health Sciences was supported by a grant from the American Chemistry Council’s Long Range Research Initiative. The breast cancer data set was generated with support of grants from NIH (R-01 to L.P.), The Breast Cancer Research Foundation (to L.P. and W.F.S.) and the Faculty Incentive Funds of the University of Texas MD Anderson Cancer Center (to W.F.S.). The data set from the University of Arkansas for Medical Sciences was supported by National Cancer Institute (NCI) PO1 grant CA55819-01A1, NCI R33 Grant CA97513-01, Donna D. and Donald M. Lambert Lebow Fund to Cure Myeloma and Nancy and Steven Grand Foundation. We are grateful to the individuals whose gene expression data were used in this study. All MAQC-II participants freely donated their time and reagents for the completion and analyses of the MAQC-II project. The MAQC-II consortium also thanks R. O’Neill for his encouragement and coordination among FDA Centers on the formation of the RBWG. The MAQC-II consortium gratefully dedicates this work in memory of R.F. Wagner who enthusiastically worked on the MAQC-II project and inspired many of us until he unexpectedly passed away in June 2008.

PY - 2010/8

Y1 - 2010/8

N2 - Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

AB - Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

UR - http://www.scopus.com/inward/record.url?scp=78650735473&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78650735473&partnerID=8YFLogxK

U2 - 10.1038/nbt.1665

DO - 10.1038/nbt.1665

M3 - Article

C2 - 20676074

AN - SCOPUS:78650735473

SN - 1087-0156

VL - 28

SP - 827

EP - 838

JO - Nature Biotechnology

JF - Nature Biotechnology

IS - 8

ER -

The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this