| The MicroArray Quality Control (MAQC)-IIII study of common practices for the development and validation of microarray-based predictive models | |
| Shi, Leming1; Campbell, Gregory2; Jones, Wendell D.3; Campagne, Fabien4; Wen, Zhining1; Walker, Stephen J.5; Su, Zhenqiang6; Chu, Tzu-Ming7; Goodsaid, Federico M.8; Pusztai, Lajos9; Shaughnessy, John D., Jr.10; Oberthuer, Andre11,12; Thomas, Russell S.13; Paules, Richard S.14; Fielden, Mark15; Barlogie, Bart10; Chen, Weijie2; Du, Pan16; Fischer, Matthias11,12; Furlanello, Cesare17; Gallas, Brandon D.2; Ge, Xijin18; Megherbi, Dalila B.19; Symmans, W. Fraser20; Wang, May D.21,22; Zhang, John23; Bitter, Hans24; Brors, Benedikt25; Bushel, Pierre R.14; Bylesjo, Max26; Chen, Minjun1; Cheng, Jie27; Cheng, Jing28; Chou, Jeff14; Davison, Timothy S.29; Delorenzi, Mauro30; Deng, Youping31; Devanarayan, Viswanath32; Dix, David J.33; Dopazo, Joaquin34; Dorff, Kevin C.; Elloumi, Fathi33; Fan, Jianqing35; Fan, Shicai36; Fan, Xiaohui37; Fang, Hong6; Gonzaludo, Nina38; Hess, Kenneth R.39; Hong, Huixiao1; Huan, Jun40; Irizarry, Rafael A.41; Judson, Richard33; Juraeva, Dilafruz25; Lababidi, Samir42; Lambert, Christophe G.43; Li, Li7; Li, Yanen44; Li, Zhen33; Lin, Simon M.16; Liu, Guozhen45; Lobenhofer, Edward K.46; Luo, Jun23; Luo, Wen47; McCall, Matthew N.41; Nikolsky, Yuri48; Pennello, Gene A.2; Perkins, Roger G.1; Philip, Reena2; Popovici, Vlad30; Price, Nathan D.49; Qian, Feng6; Scherer, Andreas50; Shi, Tieliu51,52; Shi, Weiwei48; Sung, Jaeyun49; Thierry-Mieg, Danielle53; Thierry-Mieg, Jean53; Thodima, Venkata54; Trygg, Johan26; Vishnuvajjala, Lakshmi2; Wang, Sue Jane8; Wu, Jianping55; Wu, Yichao56; Xie, Qian57; Yousef, Waleed A.58; Zhang, Liang55; Zhang, Xuegong36; Zhong, Sheng59; Zhou, Yiming10; Zhu, Sheng55; Arasappan, Dhivya6; Bao, Wenjun7; Lucas, Anne Bergstrom60; Berthold, Frank11,12; Brennan, Richard J.48; Buness, Andreas61; Catalano, Jennifer G.42; Chang, Chang51,52; Chen, Rong62; Cheng, Yiyu37; Cui, Jian51,52; Czika, Wendy7; Demichelis, Francesca63,64; Deng, Xutao65; Dosymbekov, Damir66; Eils, Roland25; Feng, Yang35; Fostel, Jennifer14; Fulmer-Smentek, Stephanie60; Fuscoe, James C.1; Gatto, Laurent67; Ge, Weigong1; Goldstein, Darlene R.68; Guo, Li69; Halbert, Donald N.70; Han, Jing42; Harris, Stephen C.1; Hatzis, Christos71; Herman, Damir72; Huang, Jianping37; Jensen, Roderick V.73; Jiang, Rui36; Johnson, Charles D.74; Jurman, Giuseppe17; Kahlert, Yvonne11,12; Khuder, Sadik A.75; Kohl, Matthias76; Li, Jianying77; Li, Li78; Li, Menglong79; Li, Quan-Zhen80; Li, Shao37; Li, Zhiguang1; Liu, Jie1; Liu, Ying36; Liu, Zhichao1; Meng, Lu36; Madera, Manuel19; Martinez-Murillo, Francisco2; Medina, Ignacio81; Meehan, Joseph6; Miclaus, Kelci7; Moffitt, Richard A.21,22; Montaner, David81; Mukherjee, Piali; Mulligan, George J.82; Neville, Padraic7; Nikolskaya, Tatiana48; Ning, Baitang1; Page, Grier P.83; Parker, Joel3; Parry, R. Mitchell21,22; Peng, Xuejun84; Peterson, Ron L.85; Phan, John H.21,22; Quanz, Brian40; Ren, Yi86; Riccadonna, Samantha17; Roter, Alan H.87; Samuelson, Frank W.2; Schumacher, Martin M.88; Shambaugh, Joseph D.89; Shi, Qiang1; Shippy, Richard90; Si, Shengzhu91; Smalter, Aaron40; Sotiriou, Christos92; Soukup, Mat8; Staedtler, Frank88; Steiner, Guido93; Stokes, Todd H.21,22; Sun, Qinglan55; Tan, Pei-Yi7; Tang, Rong2; Tezak, Zivana2; Thorn, Brett1; Tsyganova, Marina66; Turpaz, Yaron94; Vega, Silvia C.95; Visintainer, Roberto17; von Frese, Juergen96; Wang, Charles65; Wang, Eric23; Wang, Junwei51,52; Wang, Wei97; Westermann, Frank25; Willey, James C.98; Woods, Matthew23; Wu, Shujian99; Xiao, Nianqing100; Xu, Joshua6; Xu, Lei1; Yang, Lun1; Zeng, Xiao45; Zhang, Jialu8; Zhang, Li8; Zhang, Min1; Zhao, Chen51,52; Puri, Raj K.42; Scherf, Uwe2; Tong, Weida1; Wolfinger, Russell D.7; MAQC Consortium; Shi, LM | |
| 2010-08-01 | |
| 发表期刊 | NATURE BIOTECHNOLOGY
 |
| ISSN | 1087-0156 |
| 卷号 | 28期号:8页码:827-U109 |
| 摘要 | 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. |
| 关键词 | Gene-expression Data Control Maqc Project Multiple-myeloma Breast-cancer Published Microarray Follicular Lymphoma Risk-stratification Dna Microarrays Classification Performance |
| 文章类型 | Article |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| DOI | 10.1038/nbt.1665 |
| 收录类别 | SCI |
| 语种 | 英语 |
| 关键词[WOS] | GENE-EXPRESSION DATA ; CONTROL MAQC PROJECT ; MULTIPLE-MYELOMA ; BREAST-CANCER ; PUBLISHED MICROARRAY ; FOLLICULAR LYMPHOMA ; RISK-STRATIFICATION ; DNA MICROARRAYS ; CLASSIFICATION ; PERFORMANCE |
| WOS研究方向 | Biotechnology & Applied Microbiology |
| WOS类目 | Biotechnology & Applied Microbiology |
| WOS记录号 | WOS:000280757500023 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 版本 | 出版稿 |
| 条目标识符 | http://ir.ipe.ac.cn/handle/122111/6111 |
| 专题 | 多相复杂系统国家重点实验室 |
| 通讯作者 | Shi, LM |
| 作者单位 | 1.US FDA, Natl Ctr Toxicol Res, Jefferson, AR 72079 USA 2.US FDA, Ctr Devices & Radiol Hlth, Silver Spring, MD USA 3.Express Anal Inc, Durham, NC USA 4.Cornell Univ, Dept Physiol & Biophys, Weill Med Coll, New York, NY 10021 USA 5.Wake Forest Univ, Wake Forest Inst Regenerat Med, Winston Salem, NC 27109 USA 6.Z Tech, Jefferson, AR USA 7.SAS Inst Inc, Cary, NC USA 8.US FDA, Ctr Drug Evaluat & Res, Silver Spring, MD USA 9.Univ Texas MD Anderson Canc Ctr, Breast Med Oncol Dept, Houston, TX 77030 USA 10.Univ Arkansas Med Sci, Myeloma Inst Res & Therapy, Little Rock, AR 72205 USA 11.Univ Cologne, Dept Pediat Oncol & Hematol, Cologne, Germany 12.Univ Cologne, Ctr Mol Med CMMC, Cologne, Germany 13.Hamner Inst Hlth Sci, Res Triangle Pk, NC USA 14.Natl Inst Environm Hlth Sci, NIH, Res Triangle Pk, NC USA 15.Roche Palo Alto LLC, San Francisco, CA USA 16.Northwestern Univ, Biomed Informat Ctr, Chicago, IL 60611 USA 17.Fdn Bruno Kessler, Povo, Italy 18.S Dakota State Univ, Dept Math & Stat, Brookings, SD 57007 USA 19.Univ Massachusetts Lowell, CMINDS Res Ctr, Dept Elect & Comp Engn, Lowell, MA USA 20.UI MD Anderson Canc Ctr, Dept Pathol, Houston, TX USA 21.Georgia Inst Technol, Dept Biomed Engn, Atlanta, GA 30332 USA 22.Emory Univ, Atlanta, GA 30322 USA 23.Syst Analyt Inc, Waltham, MA USA 24.Hoffmann LaRoche, Nutley, NJ USA 25.German Canc Res Ctr, Dept Theoret Bioinformat, Heidelberg, Germany 26.Umea Univ, Computat Life Sci Cluster CLiC, Chem Biol Ctr KBC, Umea, Sweden 27.GlaxoSmithKline Inc, Collegeville, PA USA 28.Tsinghua Univ, Sch Med, Med Syst Biol Res Ctr, Beijing 100084, Peoples R China 29.Almac Diagnost Ltd, Craigavon, North Ireland 30.Swiss Inst Bioinformat, Lausanne, Switzerland 31.Univ So Mississippi, Dept Biol Sci, Hattiesburg, MS 39406 USA 32.Global Pharmaceut R&D, Abbott Labs, Souderton, PA USA 33.US EPA, Natl Ctr Computat Toxicol, Res Triangle Pk, NC 27711 USA 34.CIPF, Dept Bioinformat & Genom, Valencia, Spain 35.Princeton Univ, Dept Operat Res & Financial Engn, Princeton, NJ 08544 USA 36.Tsinghua Univ, MOE Key Lab Bioinformat, TNLIST, Dept Automat, Beijing 100084, Peoples R China 37.Zhejiang Univ, Coll Pharmaceut Sci, Inst Pharmaceut Informat, Hangzhou 310003, Zhejiang, Peoples R China 38.Roche Palo Alto LLC, Palo Alto, CA USA 39.UT MD Anderson Canc Ctr, Dept Biostat, Houston, TX USA 40.Univ Kansas, Dept Elect Engn & Comp Sci, Lawrence, KS 66045 USA 41.Johns Hopkins Univ, Dept Biostat, Baltimore, MD 21205 USA 42.US FDA, Ctr Biol Evaluat & Res, Bethesda, MD USA 43.Golden Helix Inc, Bozeman, MT USA 44.Univ Illinois, Dept Comp Sci, Urbana, IL 61801 USA 45.SABiosciences Corp, Frederick, MD USA 46.Cogenics, Morrisville, NC USA 47.Ligand Pharmaceut Inc, La Jolla, CA 92037 USA 48.GeneGo Inc, Encinitas, CA USA 49.Univ Illinois, Dept Chem & Biomol Engn, Urbana, IL 61801 USA 50.Spheromics, Kontiolahti, Finland 51.E China Normal Univ, Ctr Bioinformat, Shanghai 200062, Peoples R China 52.E China Normal Univ, Inst Biomed Sci, Sch Life Sci, Shanghai 200062, Peoples R China 53.Natl Ctr Biotechnol Informat, NIH, Bethesda, MD USA 54.Mem Sloan Kettering Canc Ctr, Rockefeller Res Labs, New York, NY 10021 USA 55.CapitalBio Corp, Beijing, Peoples R China 56.N Carolina State Univ, Dept Stat, Raleigh, NC 27695 USA 57.SRA Int FMMFS, Rockville, MD USA 58.Helwan Univ, Helwan, Egypt 59.Univ Illinois, Dept Bioengn, Urbana, IL 61801 USA 60.Agilent Technol, Santa Clara, CA USA 61.F Hoffmann La Roche Ltd, Basel, Switzerland 62.Stanford Univ, Stanford Ctr Biomed Informat Res, Stanford, CA 94305 USA 63.Cornell Univ, Weill Med Coll, Dept Pathol, HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsau, New York, NY 10021 USA 64.Cornell Univ, Weill Med Coll, Lab Med, HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsau, New York, NY 10021 USA 65.Univ Calif Los Angeles, Cedars Sinai Med Ctr, David Geffen Sch Med, Los Angeles, CA 90048 USA 66.Russian Acad Sci, Vavilov Inst Gen Genet, Moscow, Russia 67.DNAVision SA, Gosselies, Belgium 68.Ecole Polytech Fed Lausanne, Lausanne, Switzerland 69.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing, Peoples R China 70.Abbott Labs, Abbott Pk, IL 60064 USA 71.Nuvera Biosci Inc, Woburn, MA USA 72.Univ Arkansas Med Sci, Winthrop P Rockefeller Canc Inst, Little Rock, AR 72205 USA 73.VirginiaTech, Blacksburg, VA USA 74.BioMath Solut LLC, Austin, TX USA 75.Univ Toledo, Bioinformat Program, Toledo, OH 43606 USA 76.Univ Bayreuth, Dept Math, Bayreuth, Germany 77.Univ N Carolina, Lineberger Comprehens Canc Ctr, Chapel Hill, NC 27599 USA 78.Stanford Univ, Dept Pediat, Stanford, CA 94305 USA 79.Sichuan Univ, Coll Chem, Chengdu 610064, Sichuan, Peoples R China 80.Univ Texas SW Med Ctr Dallas, Dallas, TX 75390 USA 81.CIPF, Valencia, Spain 82.Millennium Pharmaceut Inc, Cambridge, MA USA 83.RTI Int, Atlanta, GA USA 84.Takeda Global R&D Ctr Inc, Deerfield, IL USA 85.Novartis Inst Biomed Res, Cambridge, MA USA 86.Rutgers State Univ, WM Keck Ctr Collaborat Neurosci, Piscataway, NJ USA 87.Entelos Inc, Foster City, CA USA 88.Novartis Pharma AG, Biomarker Dev, Novartis Inst BioMed Res, Basel, Switzerland 89.Genedata Inc, Lexington, MA USA 90.Affymetrix Inc, Santa Clara, CA USA 91.Hefei Teachers Coll, Dept Chem & Chem Engn, Hefei, Anhui, Peoples R China 92.Inst Jules Bordet, B-1000 Brussels, Belgium 93.F Hoffmann La Roche Ltd, Biostat, Basel, Switzerland 94.Lilly Singapore, Ctr Drug Discovery, Immunos, Singapore, Singapore 95.Microsoft Corp, US Hlth Solut Grp, Redmond, WA 98052 USA 96.Data Anal Solut DA SOL GmbH, Greifenberg, Germany 97.Cornell Univ, Ithaca, NY USA 98.Univ Toledo Hlth Sci Campus, Dept Med, Div Pulm & Crit Care Med, Toledo, OH USA 99.Bristol Myers Squibb, Pennington, NJ USA 100.OpGen Inc, Gaithersburg, MD USA 101.Tsinghua Univ, TNLIST, Dept Automat, Bioinformat Div, Beijing 100084, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shi, Leming,Campbell, Gregory,Jones, Wendell D.,et al. The MicroArray Quality Control (MAQC)-IIII study of common practices for the development and validation of microarray-based predictive models[J]. NATURE BIOTECHNOLOGY,2010,28(8):827-U109. |
| APA | Shi, Leming.,Campbell, Gregory.,Jones, Wendell D..,Campagne, Fabien.,Wen, Zhining.,...&Shi, LM.(2010).The MicroArray Quality Control (MAQC)-IIII study of common practices for the development and validation of microarray-based predictive models.NATURE BIOTECHNOLOGY,28(8),827-U109. |
| MLA | Shi, Leming,et al."The MicroArray Quality Control (MAQC)-IIII study of common practices for the development and validation of microarray-based predictive models".NATURE BIOTECHNOLOGY 28.8(2010):827-U109. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| 20131115-1199复件 nbt.（1151KB） | 开放获取 | CC BY-NC-SA | 浏览 请求全文 | |||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
修改评论