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Study-wide significance level taking into account of the LD between SNPs to keep a type 1 error of 5% for multiple testing was determined using the Nyholt's procedure (Nyholt, 2004).
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Levels of significance for multiple tests were determined using sequential Bonferroni adjustments for simultaneous tests [ 70] whenever relevant.
This package uses the Fisher´s Exact Test with multiple testing corrections and, since multiple categories are examined simultaneously, the Benjamini and Hochberg False Discovery Rate correction (FDR) for multiple testing was determined for all functional category analyses.
The significance of normally distributed data (Kolmogorov-Smirnoff test) was determined using analysis of variance (ANOVA) plus Bonferroni or Tamhane post-hoc tests for multiple comparisons.
Statistical differences between the 2 groups were determined using the Mann-Whitney U test followed by Bonferroni's correction for multiple testing, and the statistical significance among the groups was determined using the Kruskal-Wallis test.
For other data, statistical significance was determined using the unpaired t test or one-way ANOVA corrected for multiple comparisons as appropriate.
For all other experiments, statistical significance was determined using the two-tailed Student's t test with corrections for multiple comparisons against a single control group, where appropriate.
Statistical significance was determined using the χ2 test, corrected for multiple comparisons by the Holm-Bonferroni method [35].
Significance was determined using Tukey's multiple comparison tests for unequal replicates or Student's t-test.
Significant overrepresentation of particular GO terms in the dataset was determined using the software GeneMerge with corrections for multiple tests [50].
Statistical significance for in vivo anthelmintic activity effect of the extracts was determined using one way ANOVA and LSD multiple comparison tests.
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