Performance of the imputation methods under various conditions using real data sets.

<p>Each label along x-axis represents a specific combination of LD level and marker density. Within each label, “L”, “M”, and “H” refer to, respectively, low, medium and high LD level when they are the first letter or marker density when they are the second letter.</p

Effects of MAF of untyped SNPs on accuracy rates in real datasets.

<p>The results are based on the medium marker density (1 SNP per 6 kb). (a) Low LD level; (b) Medium LD level; (c) High LD level.</p

Effects of MAF of untyped SNPs on accuracy rates.

<p>The results are based on 90 reference haplotypes and the medium marker density (1 SNP per 6 kb). (a) Low LD level; (b) Medium LD level; (c) High LD level.</p

Effects of marker density on accuracy rates.

<p>The results are based on 90 reference haplotypes at the medium LD level. X-axis represents marker density: low marker density: one SNP per 10 kb; medium marker density: one SNP per 6 kb and high marker density: one SNP per 3 kb.</p

Effects of LD level on accuracy rates.

<p>The results are based on 90 reference haplotypes and a medium marker density (one SNP per 6 kb).</p

Application of the proposed method to the GAW16 simulated datasets.

<p>The GAW16 simulated HDL and TG traits were analyzed. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-g001" target="_blank">Figure 1A</a>, the quantile-quantile (QQ) plot (left), and log-QQ plot (right); <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-g001" target="_blank">Figure 1B</a>, raw p-values of the genome-wide scan.</p

Power estimates at various levels of residual correlations.

<p>Power was estimated at the nominal level of 5% based on 1,000 replicates. The value of <i>r</i>² between test and causal sites was set to 1.0, and the recombination rate between the sites was set to 0.01. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-t002" target="_blank">2</a> legends for simulation and abbreviation details.</p

The effects of LD level and family structures on power estimates.

<p>The number of children per family varied from 1 to 3, with the total number of individuals being constrained at 800. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-t002" target="_blank">2</a> legends for simulation and abbreviation details.</p

Power estimates at various levels of residual correlations when parents are missing.

<p>Parents were deleted from the simulation. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-t002" target="_blank">2</a> legends for simulation and abbreviation details.</p

P-values at pleiotropic SNPs.

<p>For univariate tests, e.g., QTDT and UT, the uniform bivariate p-value was obtained by adjusting the minimum of the two univairate p-values by multiple testing correction (multiplying by 2). See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0008133#pone-0008133-t001" target="_blank">Table 1</a> legend for abbreviation details.</p