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1. The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

Author

Su Zhenqiang, Shippy Richard, Puri Raj K, Peterson Ron L, Mei Nan, Ma Yunqing, Luo Yuling, Li Quan-Zhen, Kawasaki Ernest S, Hong Huixiao, Herman Damir, Han Jing, Guo Xu, Fuscoe James C, Frueh Felix W, Fan Xiao-hui, Collins Patrick J, Chu Tzu-Ming, Bertholet Vincent, Cao Xiaoxi, Bao Wenjun, Barbacioru Catalin C, Amur Shashi, Qian Feng, Fang Hong, Boysen Cecilie, Croner Lisa J, Guo Lei, Goodsaid Federico M, Perkins Roger G, Harris Stephen C, Jensen Roderick V, Jones Wendell D, Shi Leming, Sun Yongming, Sun Hongmei, Thorn Brett, Turpaz Yaron, Wang Charles, Wang Sue, Warrington Janet A, Willey James C, Wu Jie, Xie Qian, Zhang Liang, Zhang Lu, Zhong Sheng, Wolfinger Russell D, and Tong Weida

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists. Results Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan – the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent P-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on P-value ranking is an expected mathematical consequence of the high variability of the t-values; the more stringent the P-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations. Conclusion We recommend the use of FC-ranking plus a non-stringent P cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the P-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and P-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the P criterion balances sensitivity and specificity.

Published
2008
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12. Effect of the AIN-93M purified diet and dietary restriction on survival in Sprague-Dawley rats: implications for chronic studies. (Nutrition and Aging)

Author

Duffy, Peter H., Lewis, Sherry M., Mayhugh, Martha A., McCracken, Andy, Thorn, Brett T., Reeves, Philip G., Blakely, Shirley A., Casciano, Daniel A., and Feuers, Ritchie J.

Subjects
Cell research -- Reports, Nutrition -- Research, Rats -- Usage, Animal feeding and feeds -- Research, Diet -- Research, Food/cooking/nutrition
Abstract

Survival, growth and dietary intake (DI) variables were monitored in a chronic 114-wk study in which male Sprague-Dawley rats [n = 120; National Center for Toxicological Research (NCTR) colony] consumed the AIN-93M purified diet ad libitum (AL), or an amount reduced by 31% of total AL intake inclusive of all macro- and micronutrients. The main objectives were to ascertain the survival characteristics of rats fed the AIN-93M diet and to determine whether dietary restriction (DR) increases longevity of rats fed this casein-based diet compared with the use of mixed-protein sources of the NIH-31 cereal-based diet in an earlier study. Body, liver, brain, the brain/body ratio, spleen, thymus and kidney weights, body length and body density were decreased (P < 0.05) by DR, whereas testis weight and skull length were not altered by DR. Significant age effects at 58 and 114 wk were found for body, brain, the brain/body ratio, liver and testis weights, and body density. Survival rates for the AL and 31% DR groups were 43.3 and 57.5%, respectively. Survival curves were not significantly different. The survival rate for AL rats fed the AIN-93M diet was not different from that of AL rats fed the NIH-31 diet (43.3 and 51.7%, respectively). However, the survival rate for 31% DR rats fed the AIN-93M diet was significantly lower than 25% DR rats fed the NIH-31 diet (57.5 and 87.5%, respectively) although both groups had similar body weights and energy intake at various ages. Nutritional components in the NIH-31 diet that are missing and/or reduced in the AIN-93M diet may interact with DR to increase 114-wk survival. Although the survivability, growth and anatomical results of this study suggest that the AIN-93M diet is suitable for chronic rodent studies, additional studies such as comprehensive histopathologic and physiologic investigations must be undertaken to complete the evaluation process. KEY WORDS: * AIN-93M * purified * dietary * restriction * survival * rats

Published
2002

16. The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Author

Shi, Leming, Jones, Wendell, Jensen, Roderick, Harris, Stephen, Perkins, Roger, Goodsaid, Federico, Guo, Lei, Croner, Lisa, Boysen, Cecilie, Fang, Hong, Amur, Shashi, Bao, Wenjun, Barbacioru, Catalin, Bertholet, Vincent, Cao, Xiaoxi Megan, Chu, Tzu-Ming, Collins, Patrick, Fan, Xiao-hui, Frueh, Felix, Fuscoe, James, Guo, Xu, Han, Jing, Herman, Damir, Hong, Huixiao, Kawasaki, Ernest, Li, Quan-Zhen, Luo, Yuling, Ma, Yunqing, Mei, Nan, Peterson, Ron, Puri, Raj, Qian, Feng, Shippy, Richard, Su, Zhenqiang, Sun, Yongming Andrew, Sun, Hongmei, Thorn, Brett, Turpaz, Yaron, Wang, Charles, Wang, Sue-Jane, Warrington, Janet, Willey, James, Wu, Jie, Xie, Qian, Zhang, Liang, Zhang, Lu, Zhong, Sheng, Chen, James, Wolfinger, Russell, and Tong, Weida

Published
2007
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18. Toxicity Evaluation of Bisphenol A Administered by Gavage to Sprague Dawley Rats From Gestation Day 6 Through Postnatal Day 90

Author

Delclos, K. Barry, primary, Camacho, Luísa, additional, Lewis, Sherry M., additional, Vanlandingham, Michelle M., additional, Latendresse, John R., additional, Olson, Greg R., additional, Davis, Kelly J., additional, Patton, Ralph E., additional, Gamboa da Costa, Gonçalo, additional, Woodling, Kellie A., additional, Bryant, Matthew S., additional, Chidambaram, Mani, additional, Trbojevich, Raul, additional, Juliar, Beth E., additional, Felton, Robert P., additional, and Thorn, Brett T., additional

Published
2016
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19. The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

Author

Shi, Leming, Jones, Wendell D., Jensen, Roderick V., Harris, Stephen C., Perkins, Roger G., Goodsaid, Federico M., Guo, Lei, Croner, Lisa J., Boysen, Cecilie, Fang, Hong, Qian, Feng, Amur, Shashi, Bao, Wenjun, Barbacioru, Catalin C., Bertholet, Vincent, Cao, Xiaoxi M., Chu, Tzu-Ming, Collins, Patrick J., Fan, Xiao-hui, Frueh, Felix W., Fuscoe, James C., Guo, Xu, Han, Jing, Herman, Damir, Hong, Huixiao, Kawasaki, Ernest S., Li, Quan-Zhen, Luo, Yuling, Ma, Yunqing, Mei, Nan, Peterson, Ron L., Puri, Raj K., Shippy, Richard, Su, Zhenqiang, Sun, Yongming A., Sun, Hongmei, Thorn, Brett, Turpaz, Yaron, Wang, Charles, Wang, Sue J., Warrington, Janet A., Willey, James C., Wu, Jie, Xie, Qian, Zhang, Liang, Zhang, Lu, Zhong, Sheng, Wolfinger, Russell D., Tong, Weida, and Biological Sciences

Subjects
genetic structures
Abstract

Background Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists. Results Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan - the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent P-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on P-value ranking is an expected mathematical consequence of the high variability of the t-values; the more stringent the P-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations. Conclusion We recommend the use of FC-ranking plus a non-stringent P cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the P-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and P-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the P criterion balances sensitivity and specificity. Published version

Published
2008

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

Author

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

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.

Published
2010
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21. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Author

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

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.

Published
2010

22. The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

Author

Biological Sciences, Shi, Leming, Jones, Wendell D., Jensen, Roderick V., Harris, Stephen C., Perkins, Roger G., Goodsaid, Federico M., Guo, Lei, Croner, Lisa J., Boysen, Cecilie, Fang, Hong, Qian, Feng, Amur, Shashi, Bao, Wenjun, Barbacioru, Catalin C., Bertholet, Vincent, Cao, Xiaoxi M., Chu, Tzu-Ming, Collins, Patrick J., Fan, Xiao-hui, Frueh, Felix W., Fuscoe, James C., Guo, Xu, Han, Jing, Herman, Damir, Hong, Huixiao, Kawasaki, Ernest S., Li, Quan-Zhen, Luo, Yuling, Ma, Yunqing, Mei, Nan, Peterson, Ron L., Puri, Raj K., Shippy, Richard, Su, Zhenqiang, Sun, Yongming A., Sun, Hongmei, Thorn, Brett, Turpaz, Yaron, Wang, Charles, Wang, Sue J., Warrington, Janet A., Willey, James C., Wu, Jie, Xie, Qian, Zhang, Liang, Zhang, Lu, Zhong, Sheng, Wolfinger, Russell D., Tong, Weida, Biological Sciences, Shi, Leming, Jones, Wendell D., Jensen, Roderick V., Harris, Stephen C., Perkins, Roger G., Goodsaid, Federico M., Guo, Lei, Croner, Lisa J., Boysen, Cecilie, Fang, Hong, Qian, Feng, Amur, Shashi, Bao, Wenjun, Barbacioru, Catalin C., Bertholet, Vincent, Cao, Xiaoxi M., Chu, Tzu-Ming, Collins, Patrick J., Fan, Xiao-hui, Frueh, Felix W., Fuscoe, James C., Guo, Xu, Han, Jing, Herman, Damir, Hong, Huixiao, Kawasaki, Ernest S., Li, Quan-Zhen, Luo, Yuling, Ma, Yunqing, Mei, Nan, Peterson, Ron L., Puri, Raj K., Shippy, Richard, Su, Zhenqiang, Sun, Yongming A., Sun, Hongmei, Thorn, Brett, Turpaz, Yaron, Wang, Charles, Wang, Sue J., Warrington, Janet A., Willey, James C., Wu, Jie, Xie, Qian, Zhang, Liang, Zhang, Lu, Zhong, Sheng, Wolfinger, Russell D., and Tong, Weida

Abstract

Background Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists. Results Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan - the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent P-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on P-value ranking is an expected mathematical consequence of the high variability of the t-values; the more stringent the P-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations. Conclusion We recommend the use of FC-ranking plus a non-stringent P cutoff as a straightforward and baseline practice in order to generate more repro

Published
2008

25. The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

Author

Shi, Leming, primary, Jones, Wendell D, additional, Jensen, Roderick V, additional, Harris, Stephen C, additional, Perkins, Roger G, additional, Goodsaid, Federico M, additional, Guo, Lei, additional, Croner, Lisa J, additional, Boysen, Cecilie, additional, Fang, Hong, additional, Qian, Feng, additional, Amur, Shashi, additional, Bao, Wenjun, additional, Barbacioru, Catalin C, additional, Bertholet, Vincent, additional, Cao, Xiaoxi Megan, additional, Chu, Tzu-Ming, additional, Collins, Patrick J, additional, Fan, Xiao-hui, additional, Frueh, Felix W, additional, Fuscoe, James C, additional, Guo, Xu, additional, Han, Jing, additional, Herman, Damir, additional, Hong, Huixiao, additional, Kawasaki, Ernest S, additional, Li, Quan-Zhen, additional, Luo, Yuling, additional, Ma, Yunqing, additional, Mei, Nan, additional, Peterson, Ron L, additional, Puri, Raj K, additional, Shippy, Richard, additional, Su, Zhenqiang, additional, Sun, Yongming Andrew, additional, Sun, Hongmei, additional, Thorn, Brett, additional, Turpaz, Yaron, additional, Wang, Charles, additional, Wang, Sue Jane, additional, Warrington, Janet A, additional, Willey, James C, additional, Wu, Jie, additional, Xie, Qian, additional, Zhang, Liang, additional, Zhang, Lu, additional, Zhong, Sheng, additional, Wolfinger, Russell D, additional, and Tong, Weida, additional

Published
2008
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26. Inhibition of Platelet Aggregation With Eptifibatide, Bivalirudin, and Heparin in Patients Undergoing Percutaneous Coronary Intervention Receiving Clopidogrel Pretreatment (The PharmacoDynamic Evaluation of Angiomax, Clopidogrel With Or Without INtegrilin [DEACON] Study)

Author

Saucedo, Jorge F., primary, Aude, Wady, additional, Pacheco, Rebecca, additional, Thorn, Brett, additional, Matin, Zakaria, additional, Husain, Khawaja, additional, and Garza, Luis, additional

Published
2005
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27. Bradycardia during therapy for multiple myeloma with thalidomide

Author

Fahdi, Ibrahim Elias, primary, Gaddam, Venkat, additional, Saucedo, Jorge F, additional, Kishan, Channarayapatna V, additional, Vyas, Keyur, additional, Deneke, Matthew G, additional, Razek, Hani, additional, Thorn, Brett, additional, Bissett, Joseph K, additional, Anaisse, Elias, additional, Barlogie, Bart, additional, and Mehta, Jawahar L, additional

Published
2004
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31. Bioassays of Shortened Duration for Drugs: Statistical Implications.

Author

Kodell, Ralph L., Lin, Karl K., Thorn, Brett T., and Chen, James J.

Subjects
BIOLOGICAL assay, CARCINOGENESIS, GENETIC toxicology, DRUG toxicity, DOSE-response relationship in biochemistry, MONTE Carlo method
Abstract

Declining survival rates in rodent carcinogenesis bioassays have raised a concern that continuing the practice of terminating such studies at 24 months could result in too few live animals at termination for adequate pathological evaluation. One option for ensuring sufficient numbers of animals at the terminal sacrifice is to shorten the duration of the bioassay, but this approach is accompanied by a reduction in statistical power for detecting carcinogenic potential. The present study was conducted to evaluate the loss of power associated with early termination. Data from drug studies in rats were used to formulate biologically based dose-response models of carcinogenesis using the 2-stage clonal expansion model as a context. These dose-response models, which were chosen to represent 6 variations of the initiation-promotion-completion cancer model, were employed to generate a large number of representative bioassay data sets using Monte Carlo simulation techniques. For a variety of tumor dose-response trends, tumor lethality, and competing risk-survival rates, the power of age-adjusted statistical tests to assess the significance of carcinogenic potential was evaluated at 18 and 21 months, and compared to the power at the normal 24-month stopping time. The results showed that stopping at 18 months would reduce power to an unacceptable level for all 6 submodels of the 2-stage clonal expansion model, with the pure-promoter and pure-completer models being most adversely affected. For the 21-month stopping time, the results showed that, unless pure promotion can be ruled out a priori as a potential carcinogenic mode of action, the loss of power is too great to warrant early stopping. [ABSTRACT FROM PUBLISHER]

Published
2000
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34. The fine art of frying.

Author

THORN, BRETT

Subjects
COOKS, COOKING, FRIED food
Abstract

The article focuses on how chefs balance performance and flavor to find the right oils and techniques for any ingredient. Topics discussed include Americans' love for fried food, the various approaches restaurants take particularly when it comes to the type of fat used, and the respective strategies of chefs Mike Tambasco at The Mug, Erik Niel at Main Street Meats, and John Perkins of Juniper in St. Louis, Missouri, among several others.

Published
2015

35. Pulling profits from pork.

Author

Thorn, Brett

Subjects
COOKING with pork, COOKS
Abstract

The article reports on the diversity of protein hogs among thrifty chefs who want to please patrons in the U.S. Chef Jay Denham of Park Place puts pickled, potted and cured section at the top of the restaurant's menu in the form of country ham, cured shoulder and head cheese. Joe Ng of Chinatown Brasserie uses boneless pork to prepare a spicy sliced pork stir-fry and his signature ground pork with flowering chives. Tom Harvey of One Midtown Kitchen coats pork shoulder with a barbecue rub.

Published
2008

36. Renewing Rice.

Author

Thorn, Brett

Subjects
RICE, ONIONS, PEPPERS, FOOD industry, COOKING
Abstract

The article offers information on the cookery innovations of rice. Among the chefs from various restaurants in the U.S. that have innovated on rice include Chris Dwyer, Jean-Paul Labadie, and Sarah Stegner. It mentions that these chefs have combined Italian or white rice with baby bamboo, red onions, zucchini, peppers, cilantro to make innovated rice dishes like paella and arroz verde.

Published
2009

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

Author

Shi L, Campbell G, Jones WD, Campagne F, Wen Z, Walker SJ, Su Z, Chu TM, Goodsaid FM, Pusztai L, Shaughnessy JD Jr, 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, Li 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, Zhang L, Zhang M, Zhao C, Puri RK, Scherf U, Tong W, and Wolfinger RD

Subjects
Animals, Breast Neoplasms diagnosis, Breast Neoplasms genetics, Disease Models, Animal, Female, Gene Expression Profiling methods, Gene Expression Profiling standards, Guidelines as Topic, Humans, Liver Diseases etiology, Liver Diseases pathology, Lung Diseases etiology, Lung Diseases pathology, Multiple Myeloma diagnosis, Multiple Myeloma genetics, Neoplasms diagnosis, Neuroblastoma diagnosis, Neuroblastoma genetics, Predictive Value of Tests, Quality Control, Rats, Survival Analysis, Liver Diseases genetics, Lung Diseases genetics, Neoplasms genetics, Neoplasms mortality, Oligonucleotide Array Sequence Analysis methods, Oligonucleotide Array Sequence Analysis standards
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.

Published
2010
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