11 research outputs found

    F^st vs. <i>F</i><sub><i>st</i></sub> and Ï‘^2 for two subpopulations.

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    <p></p><p></p><p></p><p></p><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi><mi>t</mi></p><p></p><p></p><p></p><p></p> vs. <i>F</i><sub><i>st</i></sub> and <p></p><p></p><p></p><p></p><p><mi>Ï‘</mi><mo>^</mo></p><mn>2</mn><p></p><p></p><p></p><p></p> for two subpopulations.<p></p

    F^st between WETH and HapMap 3 samples.

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    <p>* Shown are means (variances) of </p><p></p><p></p><p></p><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi><mi>t</mi></p><p></p><p></p><p></p><p></p>.<p></p><p></p><p></p><p></p><p></p><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi><mi>t</mi></p><p></p><p></p><p></p><p></p> between WETH and HapMap 3 samples.<p></p

    Effect of the number of individuals per subpopulation on bias.

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    <p>The x-axis shows the number of individuals per subpopulation. The y-axis shows the mean (left) and variance (right) of </p><p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mn>1</mn></p><p></p><p></p><p></p><p></p><p></p> (red), <p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mn>2</mn></p><p></p><p></p><p></p><p></p><p></p> (blue), <p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mi>m</mi></p><p></p><p></p><p></p><p></p><p></p> (green), and <p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mn>3</mn></p><p></p><p></p><p></p><p></p><p></p> (orange) values, given <i>F</i><sub><i>st</i></sub> = 0.5 and an average allele frequency <i>p</i> = 0.2. From top to bottom, the plots represent the number of subpopulations <i>r</i> = 10, 20, and 40, respectively.<p></p

    Effect of the number of subpopulations on bias.

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    <p>The x-axis shows the number of subpopulations. The y-axis shows the mean (left) and variance (right) of </p><p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mn>1</mn></p><p></p><p></p><p></p><p></p><p></p> (red), <p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mn>2</mn></p><p></p><p></p><p></p><p></p><p></p> (blue), <p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mi>m</mi></p><p></p><p></p><p></p><p></p><p></p> (green), and <p></p><p></p><p></p><p><mi>F</mi></p><p><mi>s</mi><mi>t</mi></p><p></p><mo>−</mo><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi></p><p><mi>t</mi><mn>3</mn></p><p></p><p></p><p></p><p></p><p></p> (orange) values, given <i>F</i><sub><i>st</i></sub> = 0.5 and average allele frequency <i>p</i> = 0.2. The top plot represents 5 individuals per subpopulation and the bottom plot represents 1000 individuals per subpopulation.<p></p

    The relationship between F^st and Ï‘^ for simulated data.

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    <p>The x-axis shows the difference of allele frequencies between two subpopulations </p><p></p><p></p><p></p><p><mi>ϑ</mi><mo>^</mo></p><p></p><p></p><p></p> (left plots) and <p></p><p></p><p></p><p></p><p><mi>ϑ</mi><mo>^</mo></p><mn>2</mn><p></p><p></p><p></p><p></p> (right plots); the y-axis shows <p></p><p></p><p></p><p></p><p><mi>F</mi><mo>^</mo></p><p><mi>s</mi><mi>t</mi></p><p></p><p></p><p></p><p></p> values for Wright’s (top row), Weir and Cockerham’s (second row), the modified (third row), and Hudson et al.’s estimators (bottom row), and the legend indicates the sample sizes <i>n</i><sub>1</sub> (before hyphen) and <i>n</i><sub>2</sub> (after hyphen).<p></p

    Common and rare exonic <i>MUC5B</i> variants associated with type 2 diabetes in Han Chinese

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    <div><p>Genome-wide association studies have identified over one hundred common genetic risk variants associated with type 2 diabetes (T2D). However, most of the heritability of T2D has not been accounted for. In this study, we investigated the contribution of rare and common variants to T2D susceptibility by analyzing exome array data in 1,908 Han Chinese genotyped with Affymetrix Axiom® Exome Genotyping Arrays. Based on the joint common and rare variants analysis of 57,704 autosomal SNPs within 12,244 genes using Sequence Kernel Association Tests (SKAT), we identified significant associations between T2D and 25 variants (9 rare and 16 common) in <i>MUC5B</i>, <i>p</i>-value 1.01×10<sup>−14</sup>. This finding was replicated (p = 0.0463) in an independent sample that included 10,401 unrelated individuals. Sixty-six of 1,553 possible haplotypes based on 25 SNPs within <i>MUC5B</i> showed significant association with T2D (Bonferroni corrected p values < 3.2×10<sup>−5</sup>). The expression level of <i>MUC5B</i> is significantly higher in pancreatic tissues of persons with T2D compared to those without T2D (p-value = 5×10<sup>−5</sup>). Our findings suggest that dysregulated MUC5B expression may be involved in the pathogenesis of T2D. As a strong candidate gene for T2D, <i>MUC5B</i> may play an important role in the mechanisms underlying T2D etiology and its complications.</p></div

    Exome Array Association Results.

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    <p>The y axis represents the–log<sub>10</sub> (p-value) and the x axis is variant positions by chromosome. Genome-wide and suggestive statistical significance thresholds are illustrated by the two dotted lines.</p
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