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

