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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...
BMCBI
2007
120views more  BMCBI 2007»
13 years 5 months ago
Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures
Background: When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff be...
Xin Lu, David L. Perkins
BMCBI
2006
95views more  BMCBI 2006»
13 years 4 months ago
A simple method for assessing sample sizes in microarray experiments
In this short article, we discuss a simple method for assessing sample size requirements in microarray experiments. Our method starts with the output from a permutation-based anal...
Robert Tibshirani
BMCBI
2005
153views more  BMCBI 2005»
13 years 4 months ago
A comparative review of estimates of the proportion unchanged genes and the false discovery rate
Background: In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by...
Per Broberg
BMCBI
2008
99views more  BMCBI 2008»
13 years 5 months ago
Ranking analysis of F-statistics for microarray data
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
Yuan-De Tan, Myriam Fornage, Hongyan Xu