OpenSEM Forums

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No user picture. RFrank Joined: 06/08/2012

Negative Genetic Correlation and Positive Shared Environmental Correlation?

I recently ran a bivariate cholesky script in OpenMX and am attempting to write up my results.

The results were a bit odd - I found that the genetic correlation was negative while the shared environmental correlation was positive. The phenotypic correlation is positive. If I am understanding correctly, this means that common genetic influences that serve to increase one trait will decrease the other trait, whereas the common shared environmental influences increase both traits.

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No user picture. Lola Joined: 12/28/2016

some doubts

Hi everyone,
I am really new in OpenMx. I am trying to do a bivariate analysis (dicotomic-quantitative) and I have some questions.
1-I would like to know if I should do a univariate analysis previously I mean in the bivariate analysis The best fitting model could be AE for example, for two variables but in the univariate I could have AE model for one variable and ACE model for the other variable.

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No user picture. olleee Joined: 07/28/2016

Testing for heterogeneity of total variances of MZ and DZ pairs

I'm analyzing data from a twin study and wondered if OpenMx can test for the assumption that total variances of MZ and DZ pairs are not significantly different. Any suggestion on how to perform this test would be much appreciated!

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Picture of user. gary.marks@acu… Joined: 07/14/2016

Error in Obtaining Cis

I am running a multivariate model (3 dependent vars) with sex (female MZ, male MZ, female DZ, male DZ, F&M DZ, M&F DZ) the model runs fine with the SLSQP optimizer.

No SEs are suspect and the return code is zero.

However when I try the command:
FitCholMod <- mxRun(CholMod, intervals =TRUE)

It runs as before but I receive this error message.

Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
NLOPT fatal error -1

So the confidence intervals are not produced.

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No user picture. Liz Joined: 04/20/2016

ACE or ADE and results interpretation

Hi,

I'm wondering that in which condition we should choose ACE model, or ADE? Is there any criteria to be referred to? For example, in one trait of my own data, the ACE model indicate the CE model is the best fitted model, while the ADE model indicate the DE model is the best fitted model, is this trait heritable? And in the ADE model, how to calculate the heritability? Only the part of A, or the part of A and D, or only the D?

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No user picture. Liz Joined: 04/20/2016

CI estimation of standardized path coefficients in common path way model

Hi there,

Now I have a problem about CI estimation in a common pathway model. I can not estimate the CI of the path coeffcients of latent factors. I added following codes to the script:

matIl <- mxMatrix( type="Iden", nrow=nf, ncol=nf, name="Il")
invSDl <- mxAlgebra( expression=solve(sqrt(Il*V)), name="iSDl")
sta <- mxAlgebra(iSDl %*% al, name="sta") # standarized path coefficients of A
stc <- mxAlgebra(iSDl %*% cl, name="stc") # standarized path coefficients of C
ste <- mxAlgebra(iSDl %*% el, name="ste") # standarized path coefficients of E

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No user picture. Mumu Joined: 10/23/2016

Need Help about Bivariate ACE model script

Hello, everyone.

I'm new to behavioral genetics. I've learn some knowledge about this area by myself and finish the univariate genetic analysis about twin data. But it's a little difficult for me to find updated bivariate model script. The newest one I found is written on 2012, some lines cannot be read neither by R or me.

I wish someone can throw a web which contain updated bivariate genetic model script.

Posted on
No user picture. EWilliams Joined: 03/08/2016

ACE estimates do not match twin correlations

Hi all,

I am trying to run a bivariate ACE model. My cross-twin-cross trait correlations are as following:

MZM -.36 (-.44 , -.27) DZM -.23(-.25 ,-.09) DOS -.14(-.21, -.07)
MZF -.24 (-.33, -.14) DZF -.16(-.28 , -.04)

My standardized estimates, however, do not seem to match these correlations. Namely, C is estimated much lower than expected based on the twin correlations (esp. for females).

Males A 0.60(0.38, 0.81) C 0.25(0.07, 0.43) E 0.16(0.14, 0.19)
Females A 0.82(0.48, 1.15) C 0.01 (-.30, 0.30) E 0.18(0.10, 0.27)