cov_udi: Compute a list of covariance matrices corresponding to the...

In mashr: Multivariate Adaptive Shrinkage

Compute a list of covariance matrices corresponding to the "Unassociated", "Directly associated" and "Indirectly associated" models

Description

Compute a list of covariance matrices corresponding to the "Unassociated", "Directly associated" and "Indirectly associated" models

Usage

cov_udi(data, model = udi_model_matrix(n_conditions(data)))

Arguments

data	a mash data object, eg as created by mash_set_data
model	a model matrix with R columns, where R is the number of conditions in the data; each row should be a vector of length R with elements "U","D" and "I" indicating whether each effect is Unassociated, Directly associated or Indirectly associated

Details

If model is specified then this returns the covariance matrices for those models. The default creates all possible models. For a desription of the "Unassociated", "Directly associated" and "Indirectly associated" models see Stephens M (2013), A unified framework for Association Analysis with Multiple Related Phenotypes, PloS ONE.

Value

a named list of covariance matrices

Examples

data = mash_set_data(Bhat = cbind(c(1,2),c(3,4)), Shat = cbind(c(1,1),c(1,1)))
cov_udi(data)
cov_udi(data,c('I','D'))

mashr documentation built on Oct. 18, 2023, 5:08 p.m.