Sentence examples for markers with smaller from inspiring English sources

We also define as false positives those markers with smaller P-values, larger Bayes factors, or smaller absolute regression coefficients or scores lying outside a window of 100 kb either side of the causal variant.

A relatively higher frequency of markers with smaller size InDels (2 to 6 bp) identified in chickpea could be due to the use of NGS-based short sequence reads (<200 bp) and/or user-specific computational genomics tools/algorithms for detection of InDels among chickpea accessions at a genome-wide scale.

Based on the results of this study and the previous GWAS in European ancestry women (Spurdle et al. 2011), it is unlikely that there exist any common variants with large effects on the risk of EC, although there may be many markers with smaller effects.

Consequently, a GWAS with 12,000 cases and 24,000 controls triple the sample size of the two European ancestry GWAS conducted to date should identify three or more markers with HNF1B-like effect sizes with 85%% probability, as well as other markers with smaller effects.

Rearranging the formula, we will get the interval of σ as: [ n χ 1 − α 2,   n 2 ∗ R M S E, n χ α 2,   n 2 ∗ R M S E ] Therefore, we estimated the confidence interval of each QTL peak to include all the nearby markers with smaller RMSE than the upper bound of the best model's 95% confidence interval when all the other parameters were fixed.

Forcing additional genetic markers with small effect sizes into predictive models only marginally improves prediction over traditional risk factors [ 19].

Therefore, if the phenotype is controlled by many markers with small effects, ridge regression will capture those effects (Heffner et al., 2009), whereas LASSO will capture large effects with a small number of markers.

BIRR, which assigns a constant prior variance (as standard Bayesian ridge regression), tends to over- or undershrink; this would favor markers with small singular values while penalizing markers with large singular values.

Another possibility is to let the score of a marker depend on the p-values obtained from an association study, such that markers with small p-values have a higher score.

Methods based on conditional search can greatly reduce the computational burden by a couple of orders of magnitude, but with the risk of missing markers with small marginal effect.

Relative to the Gaussian, these densities have higher mass at zero (inducing strong shrinkage toward zero of estimates of effects of markers with small effects) and thicker tails (inducing, relative to the BRR, less shrinkage of estimates of markers with sizable effects).