The Student's t-test was used for statistical comparisons, and P-values obtained from the microarray were adjusted for multiple comparisons using the false discovery rate correction, in order to obtain an adjusted Q-value for each observation.
Each of the four microarray datasets was adjusted for estrogen and progesterone receptor (ER/PR) status as well as age to avoid their influence.
In the microarray statistical analysis, when the delta value was adjusted even slightly lower, the FDR estimate increases from 0%to~78%8%.
Microarrays were hybridized according to the Two-Colour Microarray Based Gene Expression Analysis protocol (Agilent), except that it was adjusted for the use of cDNA by omitting the fragmentation step.
Because microarray datasets use different platforms and the data are presented in different formats, the microarray data were adjusted to similar scale and distribution patterns before class prediction based on four guidelines (for detail, see Additional file 2).
Due to the large number of observations present in the microarray, P-values were adjusted for multiple comparisons using the false discovery rate correction, as previously described [ 14], in order to obtain an adjusted Q-value for each observation.
Adjusted p-value using using Benjamini and Hochberg method as represented in four microarray platforms (significance cutoff is adjusted p-value < 0.01).
As for the microarray analysis, p-values were adjusted by the procedure of Benjamini and Hochberg to control the type I error rate, and a cut off of p ≤ 0.05, and a fold change of ≥ 2 were used as a threshold to define differential expression.
Because experimental variability is common among microarray data sets, the p-values were adjusted for multiple hypothesis testing using the Benjamini-Hochberg procedure [49] to control the false discovery rate (FDR).
P-values were adjusted for multiple testing across all the microarray probes using the Benjamini-Hochberg method.
