G.small: Symmetric GRM data: small data set
In grmsem: Genetic-Relationship-Matrix Structural Equation Modelling (GRMSEM)
Description
A genetic relationship matrix for a small tri-variate data set was simulated assuming an underlying
Cholesky model, with 100 observations per trait and low polygenicity (150 SNPs per genetic factor).
Genetic trait variances were set to 0.30, 0.60, 0.60 and 0.70 respectively, and residual variances
to 0.70, 0.40, 0.40 and 0.30. The data set is described in full, including genetic and residual
covariances, in the vignette. The traits are influenced by three independent genetic factors
(A1, A2 and A3, based on a 150 SNPs each) and three independent residual factors (E1, E2 and E3).
Usage
1
Format
Symmetric GRM data frame with 100 rows and 100 columns (observations)
grmsem documentation built on Jan. 29, 2021, 5:07 p.m.
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Description
A genetic relationship matrix for a small tri-variate data set was simulated assuming an underlying Cholesky model, with 100 observations per trait and low polygenicity (150 SNPs per genetic factor). Genetic trait variances were set to 0.30, 0.60, 0.60 and 0.70 respectively, and residual variances to 0.70, 0.40, 0.40 and 0.30. The data set is described in full, including genetic and residual covariances, in the vignette. The traits are influenced by three independent genetic factors (A1, A2 and A3, based on a 150 SNPs each) and three independent residual factors (E1, E2 and E3).
Usage
1 |
Format
Symmetric GRM data frame with 100 rows and 100 columns (observations)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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