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After applying the conservative Bonferroni correction for multiple testing, even fewer correlations remained significant.
The strengths of the associations of both the rs2004640 T allele and the haplotype were high enough to surpass the correction for multiple testing, even with all of the variants in the human genome.
The association observed between European global ancestry and QRS duration at p = 6.7x10−5 survives correction for multiple testing even if a conservative Bonferroni correction (p = 0.0014) is applied.
However, the smallest observed unadjusted p-value of 0.05 would not be significant after correction for multiple testing even if a less conservative adjustment (such as adjusting for the ~7 independent tests once LD is taken into account) were used.
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We also found significant classification in PMv, SMA, and pre-SMA, each of which was highly significant after correcting for multiple tests, even though the classification accuracies were somewhat lower in these regions.
This problem of multiple testing is even more extreme for the test of epistasis.
The candidate gene study era was unsuccessful in identifying many reproducible associations, partly due to the liberal thresholds used to declare statistical significance, and the issue of multiple testing became even more pronounced with the advent of GWAS.
In the down-regulated gene set for sch9Δ, ras2Δ, and tor1Δ (fold change with respect to wild type greater than -1.8), no motif is found to be enriched after multiple testing correction even at a significance level of 0.01.
Controlling for multiple testing is important even for candidate gene study.
Empirical Bayes robustification and adjustment for multiple testing was included even in this analysis, using the limma tool [ 40].
We conduct enrichment analysis using the procedure outlined by Arava et al. (2003), which allows us to estimate q-values for multiple hypothesis tests, even when the statistics being measured are correlated (as is the case for GO and pattern annotations).
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