Hierarchical Semiparametric Model for Incorporating Intergene Information for Analysis of Genomic Data

For analysis of genomic data, e.g., microarray data from gene expression profiling experiments, the two‐component mixture model has been widely used in practice to detect differentially expressed genes. However, it naïvely imposes strong exchangeability assumptions across genes and does not make act...

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Veröffentlicht in:	Biometrics Jg. 68; H. 4; S. 1168 - 1177
Hauptverfasser:	Qu, Long, Nettleton, Dan, Dekkers, Jack C. M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Malden, USA Blackwell Publishing Inc 01.12.2012 Wiley-Blackwell Blackwell Publishing Ltd
Schlagworte:	A priori knowledge Algorithms Bioinformatics BIOMETRIC METHODOLOGY Biometrics biometry Chromosome Mapping - methods Computer Simulation Data analysis Data Interpretation, Statistical DNA, Intergenic - genetics Domain ontologies Exchange False discovery rates Gene expression Gene Expression Profiling - methods gene expression regulation Gene ontology Genes Genomics Hierarchical model Microarray microarray technology Modeling Models, Statistical Multidimensional scaling Nonparametric models Nonparametric regression Oligonucleotide Array Sequence Analysis - methods Parametric models Profiling Regression Regression Analysis Strategy
ISSN:	0006-341X, 1541-0420, 1541-0420
Online-Zugang:	Volltext
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