dksSelectGenes            package:dualKS            R Documentation

_E_x_t_r_a_c_t _g_e_n_e _s_i_g_n_a_t_u_r_e_s _f_r_o_m _a _D_K_S_G_e_n_e_S_c_o_r_e_s _o_b_j_e_c_t.

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

     The 'DKSGeneScores' returned by 'dksTrain' holds  the rank data
     for all the genes in the original 'ExpressioSet'.  However,
     generally only the top n genes for each class are desired  for
     classification.  Rather than needing to re-run 'dksTrain'  every
     time a signature of different size (n) is desired, you  simply
     extract that top n genes from this object using dksSelectGenes.

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

     dksSelectGenes(data, n)

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

    data: An object of class 'DKSGeneScores', typically generated by
          'dksTrain'

       n: The number of genes, per class, to include in the
          classification  signature.

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

     An object of class 'DKSGeneScores'

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

     Eric J. Kort, Yarong Yang

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

     'dksTrain', 'dksSelectGenes', 'dksClassify', 'DKSGeneScores',
     'DKSPredicted',  'DKSClassifier'

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

             data("dks")
             tr <- dksTrain(eset, 1, "up")
             cl <- dksSelectGenes(tr, 100)
             pr <- dksClassify(eset, cl)
             summary(pr, pData(eset)[,1])
             show(pr)
             plot(pr, actual=pData(eset)[,1])        

