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P-values generated from this test were then adjusted for multiple testing among all 200 populations using the Hochberg method [58], which is a conservative p-value adjustment method that is valid for the case in which p-values are non-negatively correlated.
Our review revealed that only 15 (10.7%) and 28 (18.4%) of the application and methodology papers respectively explicitly reported the P-value adjustment method applied.
Pairwise t-tests with pooled SD and Holm p-value adjustment method for multiple comparisons were used for post-hoc comparison of genotype × temperature treatments, and to assess genotypic differences in unreduced gamete production.
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To address the issue of multiple hypothesis testing, false discovery rate P value adjustment method was used.
By default, the P value adjustment method selected was the "BY" option representing the "Benjamini, Hochberg, and Yekutieli" method.
There were a fewer number of edges, which passed through the P value adjustment methods.
To address multiple testing problem while computing the correlation coefficients for all pairs of genes, various P value adjustment methods such as "Holm," "Hochberg," and "Bonferroni" were applied.
For addressing false positives and true negatives in large number of multiple testing, we applied different P value adjustment methods and obtained the same results.
Differential expression of transcripts between human psoriatic skin samples and control skin samples was evaluated using the Limma linear modeling package [57], with P-value adjustment using the Benjamini-Hochberg method [58].
P-value adjustment was performed by the method of Shaffer [ 22].
Differences between groups were determined by multiple comparisons using contrasts, and the Sidak method for P-value adjustment.
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