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 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.

    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 'lmscFit'.

     The function may take long time to execute.

_V_a_l_u_e:

     A list with components 

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

atanh.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 07.SingleChannel.

_E_x_a_m_p_l_e_s:

     #  See lmscFit
     ## Not run: 
     corfit <- dupclicateCorrelation(MA, design)
     all.correlations <- tanh(corfit$atanh.correlations)
     boxplot(all.correlations)
     ## End(Not run)

