zeroNu                  package:XDE                  R Documentation

_O_p_t_i_o_n _f_o_r _n_o_t _m_o_d_e_l_i_n_g _N_u

_D_e_s_c_r_i_p_t_i_o_n:

     Nu is the average expression value in each study.

_U_s_a_g_e:

     zeroNu(object, ...)

_A_r_g_u_m_e_n_t_s:

  object: object of class 'ExpressionSetList'

     ...: Not implemented

_D_e_t_a_i_l_s:

     This 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

_V_a_l_u_e:

     object of class 'XdeParameter'

_A_u_t_h_o_r(_s):

     R. Scharpf

_R_e_f_e_r_e_n_c_e_s:

     R. Scharpf et al. (2007), A Bayesian Model for Cross-Study
     Differential Gene Expression, Technical Report 158, Johns Hopkins
     University, Department of Biostatistics

