Sentence examples for multiple testing from from inspiring English sources

For both analyses, the Bonferroni method was adopted to adjust for multiple testing from the number of SNP loci detected.

In comparison with the analysis of correlations of individual genes with clinical traits, module eigengenes (MEs) offer a major advantage because they reduce multiple testing from thousands of transcripts to the number of modules.

The intersection with discovery hits in the prefrontal cortex after correction for multiple testing from Xu et al. were only 2 and 3 % compared with our discovery and meta-analysis, respectively [ 25].

Relating MEs instead of genes to a clinical trait is a major advantage of WGCNA as it diminishes the multiple testing from thousands of transcripts to the number of modules.

The Bonferroni method was adopted to adjust for multiple testing from the number of SNPs tested, and the Bonferroni corrected P value to declare significance was P value <0.05/ N, where N is the number of SNPs tested.

In addition, in the context of whole genome analyses, consideration of variation at the level of a gene reduces the problem of multiple testing, from having to deal with hundreds of thousands of variants, to having to deal with twenty thousand genes.

The distribution of rG between morphological traits (Fig. 7A) differed significantly (after corrections for multiple tests) from all other trait class combinations (Two-sample Kolmogorov Smirnov test, P < 0.003, all tests) except physiological × physiological (P = 0.058).

We used the false discovery rate (FDR) to correct for multiple testing, determined from the number of significant islands identified from 10,000 permutations of the data.

This was due to the fact that the restrictive settings limited the adjustments for taking into account the multiple testing (stemming from the many potential cluster locations and sizes evaluated) [15].

Among these, the power to replicate, after accounting for multiple testing, ranged from 82 to 99%.

The p values are automatically adjusted for the multiple testing stemming from repeated evaluations of different potential clusters during hypothesis testing.