Consistency of predictive signature genes and classifiers generated using different microarray platforms.
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.
Fan
X
X
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Lobenhofer
E K
EK
Chen
M
M
Shi
W
W
Huang
J
J
Luo
J
J
Zhang
J
J
Walker
S J
SJ
Chu
T-M
TM
Li
L
L
Wolfinger
R
R
Bao
W
W
Paules
R S
RS
Bushel
P R
PR
Li
J
J
Shi
T
T
Nikolskaya
T
T
Nikolsky
Y
Y
Hong
H
H
Deng
Y
Y
Cheng
Y
Y
Fang
H
H
Shi
L
L
Tong
W
W
D000465:Algorithms; D000818:Animals; D015342:DNA Probes; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D005796:Genes; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010597:Pharmacogenetics / Q000379:methods*; D010641:Phenotype; D011237:Predictive Value of Tests; D011786:Quality Control; D043922:Toxicogenetics / Q000379:methods*
D015342:DNA Probes