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Gene ontology analysis was performed for the functional categorization of differentially expressed genes using agriGO tool (http://bioinfo.cau.edu.cn/agriGO/), and the p-values were corrected by applying the false discovery rate correction to control falsely rejected hypothesis during the analysis.
The p values were corrected by applying the false discovery rate (FDR) correction [ 59].
Multiple hypotheses testing was controlled by applying the false discovery rate (FDR) algorithm [ 16].
Multiple testing was corrected by applying the false discovery rate method (FDR) implemented in R (Storey and Tibshirani 2003).
Multiple testing was corrected by applying the false discovery rate (FDR) method implemented in R (Storey and Tibshirani 2003).
We eventually assessed the robustness of the associations observed by applying the false discovery rate (FDR) method, setting the threshold at 0.05.
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Differentially expressed genes (DEGs) were extracted by applying the threshold false discovery rate (FDR) of less than 0.05 to adjusted P values, which were generated by using Benjamini and Hochberg approach [ 31].
Pairwise comparisons between means were carried out by the least significant difference test, applying the "false discovery rate" approach [ 34] to adjust probabilities for multiple comparisons.
Adjustment for multiple comparisons was done by applying the Benjamini-Hochberg false discovery rate (FDR) [ 29].
We corrected the results for multiple testing effects by applying the Benjamini and Hochberg false discovery rate correction (FDR ≤ 0.2).
The resulting p-values were adjusted for multiple testing by applying the Benjamini-Hochberg procedure (false discovery rate (FDR) adjustment) [ 13].
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by conceiving the false
by applying the direct
by applying the second
by using the false
by accepting the false
by applying the long
by fixing the false
by expressing the false
by estimating the false
by applying the basic
by applying the first
by applying the same
by including the false
by applying the finite
by adding the false
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