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Identifying Rare Variants with Bidirectional Effects on Quantitative Traits

Identifying Rare Variants with Bidirectional Effects on Quantitative Traits. Qunyuan Zhang, Ingrid Borecki, Michael Province Division of Statistical Genomics Washington University School of Medicine. Quantitative Trait & Bidirectional Effects. Distribution of Quantitative Trait.

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Identifying Rare Variants with Bidirectional Effects on Quantitative Traits

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  1. Identifying Rare Variants with Bidirectional Effects on Quantitative Traits Qunyuan Zhang, Ingrid Borecki, Michael Province Division of Statistical Genomics Washington University School of Medicine

  2. Quantitative Trait & Bidirectional Effects Distribution of Quantitative Trait Enriched with negative-effect (-) variants Enriched with non-causal (.) variants Enriched with positive-effect (+) variants

  3. Apolipoprotein A-I (apoA-I) (An example of gene with bidirectional variants) High HDL Variants(-) with negative effects apo A-I Milano apo A-I Marburg apo A-I Giessen apo A-I Munster apo A-I Paris . High-density lipoprotein cholesterol (HDL) -560 A -> C -151 C ->T 181 A -> G Variants(+) with positive effects Low HDL

  4. When there are only causal(+) variants … Collapsing (Li & Leal,2008) works well, power increased

  5. When there are causal(+) and non-causal(.) variants … Collapsing stillworks, power reduced

  6. When there are causal(+) non-causal(.) and causal (-) variants … Power of collapsing test significantly down

  7. P-value Weighted Sum (pSum) Test Rescaled left-tail p-value [-1,1] is used as weight

  8. P-value Weighted Sum (pSum) Test Power of collapsing test is retained even there are bidirectional variants

  9. Q-Q Plots Under the Null Inflation of type I error Corrected by permutation test (permutation of phenotype)

  10. Sum Test Collapsing test (Li & Leal, 2008) wi=1 and s=1 if s>1 Weighted-sum test (Madsen & Browning ,2009) wicalculated based-on allele freq. in control group aSum: Adaptive sum test (Han & Pan ,2010) wi= -1 if b<0 and p<0.1, otherwise wj=1 pSum: p-value weighted sum test wi = rescaled left tail p value incorporating both significance and directions

  11. Simulation • Allele frequency: 0.002 • Variant numbers: n(+), n(-), n(.) • Additive effect: 0.5 or -0.5 SD • Total N: 2000 • Sample size: 300 • Three designs (below) random sampling two-tail sampling two-tail plus central sampling

  12. n(+)=10, n(-)=0, n(.)=10 n(+)=10, n(-)=0, n(.)=20 Collapsing test (Li & Leal) pSum test aSum test (Han & Pan) n(+)=10, n(-)=10, n(.)=10 n(+)=10, n(-)=10, n(.)=10 n(+)=10, n(-)=10, n(.)=10 n(+)=10, n(-)=10, n(.)=10 n(+)=0, n(-)=10, n(.)=10 n(+)=0, n(-)=10, n(.)=10 n(+)=0, n(-)=10, n(.)=20

  13. n(+)=10, n(-)=0, n(.)=10 n(+)=10, n(-)=0, n(.)=20 Collapsing test (Li & Leal) pSum aSum test (Han & Pan) n(+)=10, n(-)=10, n(.)=10 n(+)=10, n(-)=10, n(.)=10 n(+)=10, n(-)=10, n(.)=10 n(+)=10, n(-)=10, n(.)=10 n(+)=0, n(-)=10, n(.)=10 n(+)=0, n(-)=10, n(.)=10 n(+)=0, n(-)=10, n(.)=20

  14. n(+)=10, n(-)=0, n(.)=10 Collapsing test (Li & Leal) pSum test aSum test (Han & Pan) Weighted-sum test (Madsen & Browning) n(+)=10, n(-)=10, n(.)=10 n(+)=0, n(-)=10, n(.)=10

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