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To illustrate the functionality of `grmsem`, we carried out several analyses using a range of different [data sets](https://gitlab.gwdg.de/beate.stpourcain/grmsem_external), as described in detail in the vignette. An example of a large data set, with a defined genetic architecture but high run-time, is shown below.
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## Quad-variate Cholesky decomposition model
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An example of a large data set, with a defined genetic architecture but high run-time, is shown [here](https://gitlab.gwdg.de/beate.stpourcain/grmsem_external), base on the files, `G.large.RData`, `ph.large.RData` and a pre-fitted output model `fit.large.RData`.
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An example of a [large data set](https://gitlab.gwdg.de/beate.stpourcain/grmsem_external), with a defined genetic architecture but high run-time, is shown below, base on the files, `G.large.RData`, `ph.large.RData` and a pre-fitted output model `fit.large.RData`.
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* [Data simulation](Data simulation)
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* [Model fit and output](Model fit and output)
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