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» Data-adaptive test statistics for microarray data
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BMCBI
2010
132views more  BMCBI 2010»
13 years 7 months ago
Parallel multiplicity and error discovery rate (EDR) in microarray experiments
Background: In microarray gene expression profiling experiments, differentially expressed genes (DEGs) are detected from among tens of thousands of genes on an array using statist...
Wayne Wenzhong Xu, Clay J. Carter
BMCBI
2006
153views more  BMCBI 2006»
13 years 7 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
BMCBI
2008
121views more  BMCBI 2008»
13 years 7 months ago
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
BMCBI
2010
84views more  BMCBI 2010»
13 years 7 months ago
Testing the additional predictive value of high-dimensional molecular data
Background: While high-dimensional molecular data such as microarray gene expression data have been used for disease outcome prediction or diagnosis purposes for about ten years i...
Anne-Laure Boulesteix, Torsten Hothorn
BMCBI
2006
213views more  BMCBI 2006»
13 years 7 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson