Correcting for population structure reduces the power of rare variant association methods.

<p>The figure shows the power of logistic regression methods when including ten PC covariates. The x-axis shows the odds ratio (OR), where 1.0 is the null model. “No Structure” indicates simulations where power was estimated from sampling cases and controls from a single panmictic population, but still corrected for structure. The dashed black line represents α = 0.05 and the dotted lines represent the 95% bootstrap confidence intervals.</p

Rare variant association methods exhibit higher than expected rates of spurious associations.

<p>Each square represents a confounding scenario set by different values of disease risks, parameterized by <i>Y</i>, and the proportions of each sampled subpopulation, parameterized by <i>X</i> as presented in the text. A value of 0.0 for <i>X</i> indicates an equal proportion of each subpopulation in the study pool and 0.00 for <i>Y</i> indicates an equal disease risk. Spurious association rates (SAR) lower than 5% are represented as white, with other levels signified by sequential coloration with red the lowest and blue the highest. Actual values of the SAR can be found in Figure S2 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065834#pone.0065834.s001" target="_blank">File S1</a>.</p

SAR of rare variant association methods as a function of F_ST

<p>. We tested for spurious association rates at various divergence times, presented as F_ST estimates for comparison with European populations in HGDP (light blue shading). The various lines represent differences in disease risk according to the equations <i>P(d = c|i = 1) = 0.02+ X</i> and <i>P(d = c|i = 2) = 0.02 − X</i>. The dashed black line represents the α = 0.05 value used to determine significance and the dotted lines represent the 95% confidence intervals calculated by bootstrapping.</p

The effects of PCA correction on logistic CMC.

<p>The top figure has the spurious association rate (SAR) of CMC without correcting for population structure. The middle figure shows the SAR of CMC when a single PC is included as a covariate. The bottom figure shows the SAR of CMC when 10 PCs are included as covariates. Each square represents a confounding scenario parameterized by <i>X</i> and <i>Y</i> as presented in the text. SAR lower than 5% are represented as white, with other levels signified by sequential coloration with red the lowest and blue the highest. Actual values of the SAR can be found in Figure S4 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065834#pone.0065834.s001" target="_blank">File S1</a>.</p

Probability of being a case as a function of PC1 and PC2.

<p>Individuals (dots) are colored according to the logistic regression with β values scaled so that for this example an odds ratio (OR) of 5 for a distance of a fourth of the minimal and maximal values for each axis. In other words, individuals separated by a fourth of the PC distance will have an OR of 5 compared to each other. The probability of being a case is thus indicated by the color of each dot on a scale from 0.06 to 1, as indicated by the gradient (lower right corner).</p

Schematic of demographic model used in the simulations.

<p>Parameter values were inferred by calibrating to patterns of variation in exome data from 316 European Americans.</p

Spurious association rates in the exome data.

<p>The values are the average spurious association rate for ten run using 1,000 cases and controls from the European Americans in the Exome Sequencing Project. These are the rates at the 5% significance threshold for parameters defined as odds ratios (ORs) of 1/5, 1, or 5 for a fourth, half, or full distance between the minimum and maximum for each axis: PC1 are the columns, and PC2 are the probabilities calculated for each individual. Smaller values indicate larger differences in disease risk among individuals in PC space.</p

The Czech Confederation as a Constitutional Basis for Union of Central Europe

Katedra právních dějinDepartment of Legal HistoryFaculty of LawPrávnická fakult

Genome-wide analysis of mRNA and microRNA confirms efficient pluripotent reprogramming of mGriPSCs and hGriPSCs.

<p>mGriPSC-EBs and mESC-EBs have comparable microarray expression profiles <b>(A)</b>. All ESC or EB samples show minimal steroidogenic mRNA compared to adult ovary samples <b>(B).</b> Principal component analysis (PCA) indicates attached and unattached mGriPSC-EBs are more disparate relative to the analogous mESC-EBs <b>(C)</b>. microRNA heatmaps support efficient stem cell reprogramming of mGriPSCs <b>(D)</b>.</p

Correlation between the NC statistic and PolyPhen2 predictions.

<p>Within each minor allele count, derived missense alleles are positively correlated (Spearman's ) with PolyPhen2 predictions (pph2_prob), while no such correlation exists for ancestral missense alleles. P-values are 1-sided (alternative hypothesis ).</p