calcAdjPP | R Documentation |

Calculates trait-adjusted posterior probabilities for all traits at sharing parameter kappa

calcAdjPP( qt, STR, SS, tau, nsnpspermodel, kappa, PP, beta, SSy, Sxy, xcovo, Mx, N, allVres, covY, Nqq, Nq3, Nq4, fastapprox, NCORES )

`qt` |
vector of trait names |

`STR` |
list consisting of vectors of model configurations for each trait |

`SS` |
list consisting of lists of model configuration SNPs for each trait |

`tau` |
matrix of adjustment terms |

`nsnpspermodel` |
list of number of SNPs per model for each model in STR |

`kappa` |
single value of sharing parameter kappa |

`PP` |
list consisting of vectors of posterior probabilities for the model configurations for each trait |

`beta` |
list of joint effect estimates for models in STR; multi.beta output |

`SSy` |
matrix of trait cross-products |

`Sxy` |
matrix with each column being the cross-product between SNPs and a trait |

`xcovo` |
SNP covariance matrix |

`Mx` |
vector of SNP means |

`N` |
number of individuals with measurements for all traits |

`allVres` |
list of variance residuals |

`covY` |
covariance matrix of traits |

`Nqq` |
matrix of all pair-wise counts of number of individuals with both traits in a pair measured; |

`Nq3` |
vector of counts of number of individuals with three traits measured; all triples considered; NULL if M < 4 |

`Nq4` |
vector of counts of number of individuals with four traits measured; all quadruples considered; NULL if M < 5 |

`fastapprox` |
logical that is TRUE when fast approximation is used that does not include unequal sample size adjustments; default is FALSE |

`NCORES` |
number of cores for parallel computing; recommend NCORES=M, but if on Windows, use NCORES=1; |

list of trait-adjusted posterior probabilities for each trait at sharing parameter kappa

Jenn Asimit

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