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» Detecting multivariate differentially expressed genes
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BMCBI
2010
181views more  BMCBI 2010»
13 years 7 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
GCB
2009
Springer
141views Biometrics» more  GCB 2009»
14 years 2 months ago
Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series
: A wealth of time series of microarray measurements have become available over recent years. Several two-sample tests for detecting differential gene expression in these time seri...
Oliver Stegle, Katherine J. Denby, David L. Wild, ...
BMCBI
2005
113views more  BMCBI 2005»
13 years 7 months ago
Normal uniform mixture differential gene expression detection for cDNA microarrays
Background: One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the ...
Nema Dean, Adrian E. Raftery
BMCBI
2006
103views more  BMCBI 2006»
13 years 7 months ago
Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression
Background: The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level ...
Sébastien Lemieux
BMCBI
2011
12 years 11 months ago
Proportion statistics to detect differentially expressed genes: a comparison with log-ratio statistics
Background: In genetic transcription research, gene expression is typically reported in a test sample relative to a reference sample. Laboratory assays that measure gene expressio...
Tracy L. Bergemann, Jason Wilson