Empirical and null pathway (<i>top</i>) and SNP (<i>bottom</i>) selection frequency distributions for the SiMES dataset.

<p>. For both empirical (red) and null (blue) distributions, variables (pathways and SNPs) are ranked along the <i>x</i>-axis in order of their empirical selection frequencies.</p

SP2 dataset: Pearson correlation coefficients (<i>r</i>) and p-values for the data plotted in Figure 13.

<p><i>n</i> denotes the number of predictors considered. For SNPs, coefficients describe correlations for all predictors selected with nonzero empirical selection frequencies only, since a large number of SNPs are not selected by the model at any subsample.</p

Comparison of top-<i>k</i> SP2 and SiMES pathway rankings.

<p><i>Left:</i> Variation of normalised Canberra distance, with <i>k</i> (7) (blue curve). Corresponding mean values over permutations of SiMES rankings (8) (green curve). <i>Right:</i> FDR <i>q</i>-values (blue curve). Dotted green line shows the threshold for FDR control at the 5% level.</p

SiMES dataset: Scatter plots comparing empirical and null pathway (<i>left</i>) and SNP (<i>right</i>) selection frequencies presented in Figure 14.

<p>For clarity, SNP selection frequencies are plotted for the top 1000 SNPs (by empirical selection frequency) only.</p

Simulation study 3: Six scenarios tested.

<p>Simulation study 3: Six scenarios tested.</p

SP2 dataset: scatter plots comparing empirical and null selection frequencies presented in Figures 11 and 12.

<p><i>Top row:</i> Pathway selection frequencies with . <i>Bottom row:</i> SNP selection frequencies for the same values. For clarity, SNP selection frequencies are plotted for the top 1000 SNPs (by empirical selection frequency) only. Corresponding correlation coefficients (for all ranked SNPs) are presented in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003939#pgen-1003939-t006" target="_blank">Table 6</a>. Note that pathway and SNP selection frequencies are much higher at the lower value (left hand plots), since many more variables are selected (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003939#pgen-1003939-t005" target="_blank">Table 5</a>.)</p

Simulation study 2: Mean number of pathways and SNPs selected by each model at each effect size, <i>γ</i>, across 2000 MC simulations.

<p>Simulation study 2: Mean number of pathways and SNPs selected by each model at each effect size, <i>γ</i>, across 2000 MC simulations.</p

SGL vs Lasso: distribution over 500 MC simulations of power to detect 5 causal SNPs.

<p>Each plot represents the power distribution at a single data point in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003939#pgen-1003939-g002" target="_blank">Figure 2</a>. The power distribution is discrete, since each method can identify 0, 1, 2, 3, 4 or 5 causal SNPs, with corresponding power 0, 0.2, 0.4, 0.6, 0.8 or 1.0. <i>Top row:</i> Causal SNPs drawn from single causal pathway. <i>Bottom row:</i> Causal SNPs drawn at random.</p

SP2 dataset: SNP to pathway mapping.

<p>SP2 dataset: SNP to pathway mapping.</p

Summary of genes analysed and ranked in SP2 and SiMES datasets.

<p>Summary of genes analysed and ranked in SP2 and SiMES datasets.</p