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# Bivariate analysis - PowerPoint PPT Presentation

Bivariate analysis. HGEN619 class 2006. Univariate ACE model. Expected Covariance Matrices. Bivariate Questions I. Univariate Analysis: What are the contributions of additive genetic, dominance/shared environmental and unique environmental factors to the variance?

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## PowerPoint Slideshow about 'Bivariate analysis' - treva

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### Bivariate analysis

HGEN619 class 2006

• Univariate Analysis: What are the contributions of additive genetic, dominance/shared environmental and unique environmental factors to the variance?

• Bivariate Analysis: What are the contributions of genetic and environmental factors to the covariance between two traits?

• Two or more traits can be correlated because they share common genes or common environmental influences

• e.g. Are the same genetic/environmental factors influencing the traits?

• With twin data on multiple traits it is possible to partition the covariation into its genetic and environmental components

• Goal: to understand what factors make sets of variables correlate or co-vary

(cross-twin within-trait)

covariance

(within-twin within-trait

co)variance

(cross-twin within-trait)

covariance

cross-twin cross-trait

covariance

VX1 CX1X2

CX2X1 VX2

CX1Y1

CX2Y2

CX1Y2

CX2Y1

CY1X1

CY2X2

CY1X2

CY2X1

VY1 CY1Y2

CY2Y1 VY2

a112+e112

a112

a21*a11+

e21*e11

a222+a212+

e222+e212

a21*a11

a222+a212

a112+e112

.5a112

a21*a11+

e21*e11

a222+a212+

e222+e212

.5a21*a11

.5a222+

.5a212

• Within-twin cross-trait covariances imply common etiological influences

• Cross-twin cross-trait covariances imply familial common etiological influences

• MZ/DZ ratio of cross-twin cross-trait covariances reflects whether common etiological influences are genetic or environmental

• Dataset: MCV-CVT Study

• 1983-1993

• BMI, skinfolds (bic,tri,calf,sil,ssc)

• Longitudinal: 11 years

• N MZF: 107, DZF: 60

• Dataset: NL MRI Study

• 1990’s

• Working Memory, Gray & White Matter

• N MZFY: 68, DZF: 21