lmscFit                package:limma                R Documentation

_S_i_n_g_l_e _C_h_a_n_n_e_l _L_i_n_e_a_r _M_o_d_e_l _f_o_r _S_e_r_i_e_s _o_f _A_r_r_a_y_s

_D_e_s_c_r_i_p_t_i_o_n:

     Fit single channel linear model for each gene given a series of
     arrays

_U_s_a_g_e:

     lmscFit(object, design, correlation)

_A_r_g_u_m_e_n_t_s:

  object: an 'MAList' object or a list from which 'M' and 'A' values
          may be extracted

  design: a numeric matrix containing the design matrix for linear
          model in terms of the individual channels. The number of rows
          should be twice the number of arrays. The number of columns
          will determine the number of coefficients estimated for each
          gene.

correlation: numeric value giving the intra-spot correlation

_D_e_t_a_i_l_s:

     For two color arrays, the channels measured on the same set of
     arrays are correlated. The 'M' and 'A' however are uncorrelated
     for each gene. This function fits a linear model to the set of M
     and A-values for each gene after re-scaling the M and A-values to
     have equal variances. The input correlation determines the scaling
     required.

     Missing values in 'M' or 'A' are not allowed.

_V_a_l_u_e:

     An object of class 'MArrayLM'

_A_u_t_h_o_r(_s):

     Gordon Smyth

_S_e_e _A_l_s_o:

     'lm.fit'.

     An overview of methods for single channel analysis in limma is
     given by 6.SingleChannel.

