randomDiana2means          package:adSplit          R Documentation

_G_e_n_e_r_a_t_e _n_u_l_l-_d_i_s_t_r_i_b_u_t_i_o_n_s _o_f _D_L_D-_s_c_o_r_e_s

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

     Draws a number of random sets of probe-sets consisting of the
     needed size and applies 'diana2means' to compute DLD scores.

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

     randomDiana2means(nprobes, data, chip, ndraws = 10000, 
                       ngenes = 50, ignore.genes = 5)

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

 nprobes: the size of gene sets.

    data: a matrix of expression data, rows corerspond to genes,
          columns to samples.

    chip: the name of the used chip.

  ndraws: the number of DLD scores computed.

  ngenes: the number of genes used to compute DLD scores (passed to
          'diana2means').

ignore.genes: the number of best scoring genes to be ignored when
          computing DLD scores (passed to 'diana2means')

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

     This function uses 'drawRandomPS' to draw 'ndraws' gene sets. On
     these it applies 'diana2means' to determine a null-distribution of
     DLD-scores.

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

     A vector of DLD-scores.

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

     Joern Toedling, Claudio Lottaz

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

     'drawRandomPS', 'diana2means'

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

     # prepare data
     library(vsn) 
     library(golubEsets) 
     data(Golub_Merge) 

     # generate DLD scores
     scores <- randomDiana2means(20, exprs(Golub_Merge), "hu6800", ndraws = 500) 

