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» AMDA: an R package for the automated microarray data analysi...
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BMCBI
2007
127views more  BMCBI 2007»
13 years 7 months ago
A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments
Background: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across...
Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, D...
BMCBI
2006
130views more  BMCBI 2006»
13 years 7 months ago
CARMA: A platform for analyzing microarray datasets that incorporate replicate measures
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
BMCBI
2006
100views more  BMCBI 2006»
13 years 7 months ago
Empirical array quality weights in the analysis of microarray data
Background: Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or &qu...
Matthew E. Ritchie, Dileepa S. Diyagama, Jody Neil...
BMCBI
2008
98views more  BMCBI 2008»
13 years 7 months ago
Assessing probe-specific dye and slide biases in two-color microarray data
Background: A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is...
Ruixiao Lu, Geun-Cheol Lee, Michael Shultz, Chris ...
BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
NITPICK: peak identification for mass spectrometry data
Background: The reliable extraction of features from mass spectra is a fundamental step in the automated analysis of proteomic mass spectrometry (MS) experiments. Results: This co...
Bernhard Y. Renard, Marc Kirchner, Hanno Steen, Ju...