permCor               package:GolubRR               R Documentation

_C_o_m_p_u_t_e _P_e_r_m_u_t_a_t_i_o_n_s

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

     In Note 17 and in the caption for Figure 2, Golub et al discuss a
     permutation test. This function computes the relevant permutations
     of the data set.

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

     permCor(exprSet, c, seed, nPerm)

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

 exprSet: An object of class 'exprSet' 

       c: A vector defining two classes, the length is the same as the
          number of samples. 

    seed: A seed for the random number generator, so results can be
          reproduced. 

   nPerm: The number of permutations desired. 

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

     For each permutation the elements of 'c' are rearranged and the
     correlation ('P') for each gene is computed.

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

     A list with one entry for each permutation. The element is the
     vector of correlations, one for each gene, with the permuted class
     vector.

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

     R. Gentleman

_R_e_f_e_r_e_n_c_e_s:

     Molecular Classification of Cancer: Class Discovery and Class
     Prediction by  Gene Expression Monitoring, Science, 531-537, 1999,
     T. R. Golub and D. K. Slonim and P. Tamayo and C. Huard and M.
     Gaasenbeek and J. P. Mesirov and H. Coller and M.L. Loh and J. R.
     Downing and M. A. Caligiuri and C. D. Bloomfield and E. S. Lander

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

     'P'

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

       library(golubEsets)
       pC1 <- permCor(golubTest[1:100,], golubTest$ALL, 1234, 10)

