... | @@ -69,7 +69,7 @@ An example of a [large data set](https://gitlab.gwdg.de/beate.stpourcain/grmsem_ |
... | @@ -69,7 +69,7 @@ An example of a [large data set](https://gitlab.gwdg.de/beate.stpourcain/grmsem_ |
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* [Factorial co-heritabilities and environmentalities](Factorial coheritabilities and environmentalities)
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* [Factorial co-heritabilities and environmentalities](Factorial coheritabilities and environmentalities)
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* [Bivariate heritabilities](Bivariate heritabilities)
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* [Bivariate heritabilities](Bivariate heritabilities)
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## Comparison of bi-variate GCTA and GRMSEM estimates
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## Comparison of bi-variate GREML and GRMSEM estimates
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The software [gcta](https://cnsgenomics.com/software/gcta/) can be used to estimate bivariate genetic correlations based on variance/covariance estimates for two traits. Transforming the quad-variate simulated data `large` grmsem data above into GCTA format (`large.gcta.grm.gz`,`large.gcta.phe`, `large.gcta.grm.id`), the bivariate model estimates from `GREML` and `grmsem` analyses can be compared, [here shown for traits Y1 and Y2](GCTA GRMSEM comparison).
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The software [gcta](https://cnsgenomics.com/software/gcta/) can be used to estimate bivariate genetic correlations based on variance/covariance estimates for two traits. Transforming the quad-variate simulated data `large` grmsem data above into GCTA format (`large.gcta.grm.gz`,`large.gcta.phe`, `large.gcta.grm.id`), the bivariate model estimates from `GREML` and `grmsem` analyses can be compared, [here shown for traits Y1 and Y2](GCTA GRMSEM comparison).
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# References
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# References
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