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Based on this statistical model, statistical significances were calculated using Fisher's exact test and likelihood ratio test, and then corrected for multiple testing according to Benjamini-Hochberg multiple test method [ 62].
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Multiple test methods were used to characterize these materials.
When comparisons were required between several groups, Tukey's multiple tests method was applied.
FDRmax values for each contrast were calculated using the method of Benjamini and Hochberg [ 53], the default multiple testing method in Limma.
An analysis of variance (ANOVA) was performed to determine differential expression levels between conditions and time points using the Bonferroni multiple testing method (p < 0.05).
The numbers of significant GO terms were large; therefore multiple testing method was performed in order to control the rate of errors.
To enhance the detection capability of a false discovery rate control test, we applied the likelihood ratio-based multiple testing method in neuroimage data and compared the performance with the existing methods.
Multiple comparison correction by controlling the FDR, which provides a useful alternative to traditional multiple testing method, further corroborated that preoperative high ESR levels, but not ALP, were a significant predictor for CSS PFDRR adjusted <0.01).
For homogeneity, differentially expressed genes were identified by first filtering on a fold change ≥ 2 and then performing statistical tests using the Benjamini-Hochberg multiple testing method with a false discovery rate set at 0.05.
The third and last stage was 5 dpa fruits, representing the 4 16 cell embryo stage and fruit landmark 3. Differentially expressed genes were identified using the resampling-based multiple testing method [ 40].
We were able to observe differences in gene expression between exponential phase conditions by microarray, but not at levels considered significant using the Bonferroni multiple testing method (p < 0.05).
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