Consistency of predictive signature genes and classifiers generated using different microarray platforms

被引：36

作者：

Fan, X. ^{[1
]}

Lobenhofer, E. K. ^{[2
]}

Chen, M. ^{[3
]}

Shi, W. ^{[4
]}

Huang, J. ^{[1
,3
]}

Luo, J. ^{[5
]}

Zhang, J. ^{[5
]}

Walker, S. J. ^{[6
]}

Chu, T-M ^{[7
]}

Li, L. ^{[7
]}

Wolfinger, R. ^{[7
]}

Bao, W. ^{[7
]}

Paules, R. S. ^{[8
]}

Bushel, P. R. ^{[8
]}

Li, J. ^{[8
]}

Shi, T. ^{[9
]}

Nikolskaya, T. ^{[4
,10
]}

Nikolsky, Y. ^{[4
]}

Hong, H. ^{[3
]}

Deng, Y. ^{[11
]}

Cheng, Y. ^{[1
]}

Fang, H. ^{[12
]}

Shi, L. ^{[3
]}

Tong, W. ^{[3
]}

机构：

[1] Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310003, Zhejiang, Peoples R China

[2] Cogenics, Morrisville, NC USA

[3] US FDA, Ctr Toxicoinformat, Natl Ctr Toxicol Res, Jefferson, AR 72079 USA

[4] GeneGo Inc, St Joseph, MI USA

[5] Syst Analyt Inc, Waltham, MA USA

[6] Wake Forest Inst Regenerat Med, Winston Salem, NC USA

[7] SAS Inst Inc, Cary, NC USA

[8] NIEHS, Biostat Branch, Res Triangle Pk, NC 27709 USA

[9] Chinese Acad Sci, Shanghai Informat Ctr Sci, Shanghai, Peoples R China

[10] Russian Acad Sci, NI Vavilov Gen Genet Res Inst, Moscow, Russia

[11] Univ So Mississippi, Dept Biol Sci, Hattiesburg, MS 39406 USA

[12] US FDA, Z Tech, NCTR, Tempe, AR USA

来源：

PHARMACOGENOMICS JOURNAL | 2010年 / 10卷 / 04期

基金：

高等学校博士学科点专项科研基金; 美国国家科学基金会;

关键词：

microarray; cross-platform; gene signature; classifier; MAQC; hepatotoxicity; CONTROL MAQC PROJECT; CROSS-PLATFORM; DNA MICROARRAY; EXPRESSION MEASUREMENTS; DECISION FOREST; PERFORMANCE; TECHNOLOGIES; REPRODUCIBILITY; NORMALIZATION; VISUALIZATION;

D O I：

10.1038/tpj.2010.34

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Microarray-based classifiers and associated signature genes generated from various platforms are abundantly reported in the literature; however, the utility of the classifiers and signature genes in cross-platform prediction applications remains largely uncertain. As part of the MicroArray Quality Control Phase II (MAQC-II) project, we show in this study 80-90% cross-platform prediction consistency using a large toxicogenomics data set by illustrating that: (1) the signature genes of a classifier generated from one platform can be directly applied to another platform to develop a predictive classifier; (2) a classifier developed using data generated from one platform can accurately predict samples that were profiled using a different platform. The results suggest the potential utility of using published signature genes in cross-platform applications and the possible adoption of the published classifiers for a variety of applications. The study reveals an opportunity for possible translation of biomarkers identified using microarrays to clinically validated non-array gene expression assays. The Pharmacogenomics Journal (2010) 10, 247-257; doi: 10.1038/tpj.2010.34

引用

页码：247 / 257

页数：11

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