dupcor.series             package:limma             R Documentation

_C_o_r_r_e_l_a_t_i_o_n _B_e_t_w_e_e_n _D_u_p_l_i_c_a_t_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Estimate the correlation between duplicate spots (replicate spots
     on the same array) from a series of arrays.

_U_s_a_g_e:

     duplicateCorrelation(object,design=rep(1,ncol(M)),ndups=2,spacing=1,initial=0.8,trim=0.15,weights=NULL)
     dupcor.series(M,design=rep(1,ncol(M)),ndups=2,spacing=1,initial=0.7,trim=0.15,weights=NULL)

_A_r_g_u_m_e_n_t_s:

  object: a numeric matrix of log-ratios or an 'MAList' object from
          which the log-ratios can be extracted. If 'object' is an
          'MAList' then the arguments 'design', 'ndups', 'spacing' and
          'weights' will be extracted from it if available and do not
          have to be specified as arguments.

       M: a numeric matrix. Usually the log-ratios of expression for a
          series of cDNA microarrrays with rows corresponding to genes
          and columns to arrays.

  design: the design matrix of the microarray experiment, with rows
          corresponding to arrays and columns to comparisons to be
          estimated. The number of rows must match the number of
          columns of 'M'. Defaults to the unit vector meaning that the
          arrays are treated as replicates.

   ndups: a positive integer giving the number of times each gene is
          printed on an array. 'nrow(M)' must be divisible by 'ndups'.

 spacing: the spacing between the rows of 'M' corresponding to
          duplicate spots, 'spacing=1' for consecutive spots

 initial: a numeric value between -1 and 1 giving an initial estimate
          for the correlation.

    trim: the fraction of observations to be trimmed from each end of
          'tanh(cor.genes)' when computing the trimmed mean.

 weights: an optional numeric matrix of the same dimension as 'M'
          containing weights for each spot. If smaller than 'M' then it
          will be filled out the same size.

_D_e_t_a_i_l_s:

     This function estimates the between-duplicate correlation using
     REML individually for each gene. It also returns a robust average
     of the individual correlations which can be used as input for 
     functions such as 'gls.series'.

     'duplicateCorrelation' is a more object-orientated version of
     'dupcor.series' but produces the same value.

_V_a_l_u_e:

     A list with components 

     cor: 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.

cor.genes: a numeric vector of length 'nrow(M)/ndups' giving the
          individual gene correlations.

_N_o_t_e:

     This function may take long time to execute as it makes a call to
     'gls' for each gene. Execution could be speeded up greatly if it
     could be assumed that 'M' contains no NAs.

_A_u_t_h_o_r(_s):

     Gordon Smyth

_R_e_f_e_r_e_n_c_e_s:

     Smyth, G. K., Michaud, J., and Scott, H. (2003). The use of
     within-array duplicate spots for assessing differential expression
     in microarray experiments. <URL:
     http://www.statsci.org/smyth/pubs/dupcor.pdf>

_S_e_e _A_l_s_o:

     These functions use 'gls' in the nlme package.

     An overview of linear model functions in limma is given by
     5.LinearModels.

_E_x_a_m_p_l_e_s:

     #  See gls.series for an example

