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BMCBI
2005
110views more  BMCBI 2005»
13 years 4 months ago
Considerations when using the significance analysis of microarrays (SAM) algorithm
Background: Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments...
Ola Larsson, Claes Wahlestedt, James A. Timmons
BMCBI
2007
139views more  BMCBI 2007»
13 years 4 months ago
Significance analysis of microarray transcript levels in time series experiments
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...
Barbara Di Camillo, Gianna Toffolo, Sreekumaran K....
BIOINFORMATICS
2006
89views more  BIOINFORMATICS 2006»
13 years 4 months ago
Maximum significance clustering of oligonucleotide microarrays
Affymetrix high-density oligonucleotide microarrays measure expression of DNA transcripts using probesets, i.e. multiple probes per transcript. Usually, these multiple measurement...
Dick de Ridder, Frank J. T. Staal, Jacques J. M. v...
BMCBI
2010
190views more  BMCBI 2010»
13 years 4 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
BMCBI
2005
163views more  BMCBI 2005»
13 years 4 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...