Sentence examples for testing burden from inspiring English sources

While kernel density estimation methods produce stable and geographically detailed patterns of the late testing burden, the resulting pattern depends critically on the definition of the at-risk population.

While all new vectors will require extensive preclinical testing to validate safety and performance prior to clinical use, regulatory testing burden for follow-on products can be reduced by combining carefully designed synthetic genes with existing validated vector backbones.

If a gene spans multiple regions of linkage disequilibrium, then the latter choice is preferable because it requires less genotyping and induces a smaller statistical testing burden.

Here, by specifically examining those single-SNPs which had main effects which did not replicate for pairwise interactions the multiple testing burden is further reduced.

Note that testing ratios between two metabolites a and b is independent of their order, as log(a/b) = −log(b/a), which halves multiple testing burden.

Pe'er et al. [3] estimate a multiple testing burden of approximately one million tests for genome-wide association analyses in European samples.

In this study, we present a novel eQTL detection method, " network-based, large-scale identification o f dis tal eQTL" (NetLIFT), which, rather than performing causal model selection or randomization, uses pairwise partial correlations derived from gene expression data to restrict distal association testing, thereby reducing the multiple-testing burden and highlighting candidate regulatory genes.

However, although the number of tests are considerably increased, the test statistics are highly correlated and therefore the actual multiple-testing burden increases less steeply than the number of tests if we use permutation.

The testing of such huge numbers of SNPs results in a massive multiple-testing burden in statistical analysis.

Through choosing a model implication score cutoff the number of models to test can be reduced, thus avoiding the prohibitive computational and multiple-testing burden of an exhaustive pairwise analysis.

The principal disadvantage is the fairly severe multiple-testing burden (i.e., the need to account for the possibility that when 1 million tests are conducted, some positive results will be obtained due to chance alone) imposed by GWASs, which results in the requirement for statistical significance to be denoted by P values of 5 × 10−8 and lower.