intraspotCorrelation          package:limma          R Documentation

_I_n_t_r_a-_S_p_o_t _C_o_r_r_e_l_a_t_i_o_n _f_o_r _T_w_o _C_o_l_o_r _D_a_t_a

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

     Estimate the within-block correlation associated with spots for
     spotted two color microarray data.

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

     intraspotCorrelation(object, design, trim=0.15)

_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. The number of rows should agree with the number of
          columns of M. The number of columns will determine the number
          of coefficients estimated for each gene.

    trim: the fraction of observations to be trimmed from each end of
          the atanh-correlations when computing the consensus
          correlation. See 'mean'.

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

     This function estimates the correlation between two channels
     observed on each spot. The correlation is estimated by fitting a
     heteroscedastic regression model to the M and A-values of each
     gene. The function also returns a consensus correlation, which is
     a robust average of the individual correlations, which can be used
     as input for  functions 'lmsc.series'.

     The function may take long time to execute.

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

     A list with components 

consensus.correlation: the average estimated inter-duplicate
          correlation. The average is the 0.1 trimmed mean of the
          correlations for individual genes on the tanh-transformed
          scale.

all.correlations: a numeric vector giving the individual genewise
          correlations on the atanh scale

      df: numeric matrix of degrees of freedom associated with the
          correlations. The first column gives the degrees of freedom
          for estimating the within-spot or M-value mean square while
          the second gives the degrees of freedom for estimating the
          between spot or A-value mean square.

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

     Gordon Smyth

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

     This function uses 'remlscore' from the statmod package.

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

_E_x_a_m_p_l_e_s:

     #  See lmsc.series

