Sentence examples for multiple testing based from inspiring English sources
After correction for multiple testing based on false discovery rate and considering the number of analyzed polymorphisms, significant associations were shown for four variants, even though none of these associations survived a genome-wide correction (P < 5 ∗ 10− 8).
A Bonferroni-adjusted nominal p-value threshold of 0.00015 was used to account for multiple testing, based on 341 effective independent marker loci (N*) among 363 SNPs studied.
The second approach was to determine the overall statistical significance of the combined data sets using Fisher's combined P method and the q-value to account for multiple testing based on a specified false discovery rate (FDR) [31].
gPLINK v. 2.049, PLINK v. 1.01 (http://pngu.mgh.harvard.edu/purcell/plink/) [27], and Haploview v. 4.0 [23] were used for haplotype-specific tests, incorporating gender, age, height, and weight of the subjects as covariables, with the false discovery rate set at 0.05 for correction of multiple testing, based on a previous report [28].
We applied the Bonferroni correction to multiple testing based on the number of haplotypes.
In addition, a correction for multiple testing based on the Benjamini Hochberg procedure was performed.
To get a reliable result, it is persuasive to combine multiple tests based on different assumptions for the dataset, and only the outliers supported by multiple tests are considered as reliable candidates (Simonson et al., 2010; Zhao et al., 2013).
Differentially expressed genes were selected using a Benjamini-Hochberg correction of the p-value for multiple tests, based on a p-value below 0.05 and a fold change cut off (logRatio>0.5).
These correlations however are not significant after correction for multiple tests based on sequential Bonferroni [ 70].
However, the gene-gender interaction altered to null after the multiple test based on the FDR approach.
The markers were tested for the expected segregation ratio of 1 1 using chi-square statistics (p < 0.05) corrected for multiple tests based on Bonferroni's method.
