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BMCBI
2006
131views more  BMCBI 2006»
13 years 5 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
BMCBI
2004
135views more  BMCBI 2004»
13 years 4 months ago
Determination of the differentially expressed genes in microarray experiments using local FDR
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
Julie Aubert, Avner Bar-Hen, Jean-Jacques Daudin, ...
BMCBI
2005
121views more  BMCBI 2005»
13 years 4 months ago
Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data
Background: A critical step in processing oligonucleotide microarray data is combining the information in multiple probes to produce a single number that best captures the express...
Kerby Shedden, Wei Chen, Rork Kuick, Debashis Ghos...
BMCBI
2004
113views more  BMCBI 2004»
13 years 4 months ago
Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide array
Background: To identify differentially expressed genes across experimental conditions in oligonucleotide microarray experiments, existing statistical methods commonly use a summar...
Leah Barrera, Chris Benner, Yong-Chuan Tao, Elizab...
CSB
2005
IEEE
137views Bioinformatics» more  CSB 2005»
13 years 10 months ago
A Learned Comparative Expression Measure for Affymetrix GeneChip DNA Microarrays
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...