Difference between revisions of "Inference of Overall Heritability Captured by GWA-Data"

 
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'''Background'''
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Although GWA studies uncovered many loci having an effect on complex phenotypic traits, they typically can acount only for a fraction of the total heritability (fraction of phenotypic variance that can be accounted for by relatedness of individuals). This has been termed the missing heritability problem
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We will try to use a relatively new method for analysis of two complex traits, namely height and BMI. Roughly, the method tries to estimate how much of the heritability we could maximally explain by just using our markers.
 
We will try to use a relatively new method for analysis of two complex traits, namely height and BMI. Roughly, the method tries to estimate how much of the heritability we could maximally explain by just using our markers.
 
We will compare these estimates with heritability estimates coming from known loci.
 
We will compare these estimates with heritability estimates coming from known loci.
 
We’ll try to evaluate our findings with respect to the missing heritability problem.
 
We’ll try to evaluate our findings with respect to the missing heritability problem.

Revision as of 21:47, 23 February 2012

Background

Although GWA studies uncovered many loci having an effect on complex phenotypic traits, they typically can acount only for a fraction of the total heritability (fraction of phenotypic variance that can be accounted for by relatedness of individuals). This has been termed the missing heritability problem

We will try to use a relatively new method for analysis of two complex traits, namely height and BMI. Roughly, the method tries to estimate how much of the heritability we could maximally explain by just using our markers. We will compare these estimates with heritability estimates coming from known loci. We’ll try to evaluate our findings with respect to the missing heritability problem.