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» Detecting multivariate differentially expressed genes
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BMCBI
2010
80views more  BMCBI 2010»
13 years 7 months ago
Power and sample size estimation in microarray studies
Background: Before conducting a microarray experiment, one important issue that needs to be determined is the number of arrays required in order to have adequate power to identify...
Wei-Jiun Lin, Huey-miin Hsueh, James J. Chen
BMCBI
2007
145views more  BMCBI 2007»
13 years 7 months ago
The utility of MAS5 expression summary and detection call algorithms
Background: Used alone, the MAS5.0 algorithm for generating expression summaries has been criticized for high False Positive rates resulting from exaggerated variance at low inten...
Stuart D. Pepper, Emma K. Saunders, Laura E. Edwar...
BMCBI
2010
97views more  BMCBI 2010»
13 years 7 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on es...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard ...
BMCBI
2007
134views more  BMCBI 2007»
13 years 7 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
Testing for mean and correlation changes in microarray experiments: an application for pathway analysis
Background: Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the resp...
Mayer Alvo, Zhongzhu Liu, Andrew Williams, Carole ...