zeroNu(object, ...)ExpressionSetListXdeParameterThis function should be regarded as experimental.
The nu parameter models the average expression value in each study. Modeling nu allows one to estimate differential expression across studies that may differ in location and scale (as often occurs when multiple platforms are used). The price to pay for modeling nu are additional assumptions (the nu\'s are assumed Gaussian) and a more heavily parameterized model.
The method zeroNu allows one to fit the Bayesian model without estimating nu:
- each gene is centered at zero
- initial values for the first MCMC are chosen on the basis of empirical starting values
- the initial values for a and rho are set to zero.
- the nu, a, gamma2, and rho parameters are not updated during MCMC
R. Scharpf et al. (2007), A Bayesian Model for Cross-Study Differential Gene Expression, Technical Report 158, Johns Hopkins University, Department of Biostatistics