Your English writing platform
Discover LudwigExact(60)
Given that we were performing multiple testing, the level of significance was set at p < 0.025.
To account for multiple testing, the indicated levels of statistical significance were lowered to 0.01.
To correct for multiple testing, the Holm Bonferroni method was applied to adjust the significance levels.
75 genes remained significant q < 0.05 after correction for multiple testing, the most significant of which was PHLDA1, p = 8.89 × 10−9, q = 0.0001, fold change 0.29.
Based on adjustments for multiple testing, the p-value required to reach significance in this analysis was p≤0.0167.
To adjust this p-value for within-gene multiple testing, the principle of 'seemingly unrelated estimation' [33] was used.
Density of B-cells and the presence of LN structures were higher in tissues with immature vessels but after correction for multiple testing the difference was non-significant.
For the dam mutant, the cutoff was 0.01 without multiple testing The reasoning is explained in context in the results section.
To correct for multiple testing the False Discovery Rate (FDR) Q-value estimates were calculated using QVALUE software (http://www.genomics.princeton.edu/storeylab/qvalue/index.html) [5], [6].
However, when applying a conservative Bonferroni correction for multiple testing, the significant level will be set at 0.05/28 for 28 haplogroups we analyzed.
To control the False Discovery Rate (FDR) during multiple testing, the FDR criterion introduced by Benjamini and Hochberg [101] was applied to p-values.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com