Description Usage Arguments Value Author(s) References
Estimates posterior probability of a difference between two sample groups for each genomic variable (e.g., methylation site), using shared kernels and a given prior probability of equality. Returns the results for each MCMC iteration, including the kernel weights.
1 | DictFitTestFixedP(X,Class,mu,Sigma,pA=0.5,Concentration = 0.5,NumDraws = 1000)
|
X |
A matrix in which rows represent variables (e.g., methylation sites) and columns represent samples. The entries of the matrix must be continuous between 0 and 1. |
Class |
A vector giving a class label for each sample. |
mu |
Vector of kernel means. |
Sigma |
Vector of kernel standard deviations |
Concentration |
Dirichlet hyperparameter for kernel weights |
NumDraws |
Number of MCMC draws for posterior inference. |
Returns an object with the following values:
postDraws |
M X NumDraws array, giving the posterior probability of no difference for each marker, for each MCMC draw. |
tao0Draws |
M X K X NumDraws array, giving the K kernel weights for each marker, for each MCMC draw, for class 0. |
tao1Draws |
M X K X NumDraws array, giving the K kernel weights for each marker, for each MCMC draw, for class 1. |
Eric F. Lock
Lock, E. F. & Dunson, D. B. (2016). Bayesian genome- and epigenome-wide association studies with gene level dependence. Preprint.
Lock, E. F. & Dunson, D. B. (2015). Shared kernel Bayesian screening. Biometrika, 102 (4): 829-842.
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