Sentence examples for multiple tests across from inspiring English sources
To test the significance of the resulting P values across all localities, α, the nominal Type 1 error rate, was controlled for multiple tests across locality pairs with a sparse false discovery rate correction [9].
The representation of ipsilateral finger movements was clearly visible in each individual participant (Supplementary Fig. S1) and was significant after correcting for multiple tests across the cortical surface in all regions, including the SMA and parietal cortex (Table 2).
Moreover, 12 locus pairs among the 55 possible comparisons showed significant linkage disequilibrium (P < 0.05) across all populations if no corrections for multiple tests across all populations were made, although none showed significant linkage disequilibrium after Bonferroni's correction.
The results for fat and protein percentage were highly significant even after accounting for multiple testing across the genome.
Contrary to other methods, a pre-selection of electrodes and/or correcting for multiple testing across electrodes is thus not necessary.
The corresponding BH adjusted p-values were used to correct for multiple testing across genes, and the results were visualized using volcano plots.
The Benjamini-Hochberg correction BH [39] was applied to the p-values (corresponding to the moderated t-statistics) to give values adjusted for multiple testing across genes.
To account for multiple testing across the K SNPs, the K-2 p-values (one for each window) were adjusted for multiple comparisons using the False Discovery Rate (FDR -controlling procedure oFDR -controllingHochberg [16].
To correct SNP analyses for multiple testing across all the tests performed, the R software (http://www.r-project.org/) was used to calculate false discovery rate (FDR) q-values [23].
Differential expression was tested for the probesets called present in all experiments, species and treatments (12,137 probesets, according to the present/absent MAS5 algorithm) correcting for multiple testing across all genes using the linear step-up false discovery rate (FDR).
The p-values were adjusted for multiple testing, across all genes and all comparisons, using the method of Benjamini and Hochberg[23] to control the expected false discovery rate (q-value) at less than 5%.
