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
)

Arguments

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;

Value

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