stat.Newton               package:sma               R Documentation

_A_p_p_l_y _N_e_w_t_o_n_s _s_i_n_g_l_e _s_l_i_d_e _m_e_t_h_o_d

_D_e_s_c_r_i_p_t_i_o_n:

     Applies Newtons single slide method.

_U_s_a_g_e:

     stat.Newton(RG,layout,norm="p", image.id=1,pout=TRUE)

_A_r_g_u_m_e_n_t_s:

      RG: a list with 4 elements, each represents a matrix with p rows
          for p genes and n columns for n slides. 
           The first element "R" contains the raw red intensities from
          slide i=1,...,n .
           Similarly, the second element "G" contains the raw green
          intensities. 
           The third element "Rb"  contains the background red
          intensities and 
           the fourth element "Gb" contains the  background green
          intensities.
           This list structure can be generated by the interactive
          function 'init.data'. 

  layout: a list specifying the dimensions of the spot matrix and the
          grid matrix.  This can be generated by calling 'init.grid'.

    norm: Character string, one of "n", "m", "l", "p" or "s".  This
          argument specifies the type of normalization method to be
          performed: "n" no normalization between the 2 channels; "m"
          'median' normalization, which sets the median of log
          intensity ratios to zero; "l" global 'lowess' normalization;
          "p" print-tip group lowess normalization and "s" scaled
          print-tip group lowess normalization. The default method is
          set to print-tip normalization.

image.id: Specifies image to which Chen's method will be applied.

    pout: if TRUE, an M vs. A plot will be produced with limits due to
          Newton, Specifically limits at the 1:1, 1:10 and 1:100 log
          odds ratio. If FALSE, return a list with pertinant
          information

_V_a_l_u_e:

     List containing the following components:

   theta: parameters estimated by EM algorithm

     lod: Log odds ratio of being differentially expressed for each
          gene

_A_u_t_h_o_r(_s):

     Ben Bolstad, bolstad@stat.berkeley.edu

_R_e_f_e_r_e_n_c_e_s:

     Newton, M.N., C.M. Kendziorski, C.S. Richmond, F.R. Blattner, and
     K.W. Tsui . On differential variability of expression ratios:
     Improving statistical inference about gene expression changes from
     microarray data. Technical Report 139, Department of Biostatistics
     and Medical Informatics, UW Madison, 1999. <URL:
     http://www.stat.wisc.edu/~newton/papers/abstracts/btr139a.html>

_S_e_e _A_l_s_o:

     'stat.Chen','stat.ChurSap'

_E_x_a_m_p_l_e_s:

     data(MouseArray)
     ##mouse.setup <- init.grid() 
     ##mouse.data <- init.data() ## see \emph{init.data}
     stat.Newton(mouse.data,mouse.setup,image.id=3)

