getEAWP                package:limma                R Documentation

_E_x_t_r_a_c_t _B_a_s_i_c _D_a_t_a _f_r_o_m _M_i_c_r_o_a_r_r_a_y _D_a_t_a _O_b_j_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Given a microarray data object of any known class, get the
     expression values, weights, probe annotation and A-values, which
     are needed for linear modelling. This function is called by the
     linear modelling functions in LIMMA.

_U_s_a_g_e:

     getEAWP(object)

_A_r_g_u_m_e_n_t_s:

  object: a microarray data object. An object of class 'list',
          'MAList', 'marrayNorm', 'PLMset', 'vsn', or any class
          inheriting from 'ExpressionSet', or any object that can be
          coerced to a numeric matrix.

_D_e_t_a_i_l_s:

     In the case of two-color objects, the 'Amean' is computed from the
     matrix of A-values. For single-channel objects, 'Amean' is
     computed from the matrix of expression vales. 'PLMset', 'vsn' and
     'ExpressionSet' are assumed to be single-channel for this purpose.

     If 'object' is a matrix, it is assumed to contain log-intensities
     if the values are all positive and log-ratios otherwise. 'Amean'
     is computed in the former case but not the latter.

_V_a_l_u_e:

     A list with components 

   exprs: numeric matrix of log-ratios or log-intensities

 weights: numeric matrix of weights

  probes: data.frame of probe-annotation

   Amean: numeric vector of average log-expression for each probe

_A_u_t_h_o_r(_s):

     Gordon Smyth

_S_e_e _A_l_s_o:

     02.Classes gives an overview of data classes used in LIMMA.

