dksWeights              package:dualKS              R Documentation

_C_a_l_c_u_l_a_t_e _g_e_n_e _w_e_i_g_h_t_s _b_a_s_e_d _o_n _a_v_e_r_a_g_e _e_x_p_r_e_s_s_i_o_n.

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

     Prior to selecting genes it may be desirable to calculate weights 
     for each genes so that some genes are more likely than others to
     be included in the gene signature all other things being equal. 
     This  function will calculate an N x M weight matrix for N genes
     in 'data'  and M unique classes in 'class'.  The weights are based
     on  mean expression of each gene in each class such that genes
     that are  highly expressed on average in a given class will be
     weighted more  highly when scoring genes for that class.

     The resulting weight matrix can be bassed to 'dksTrain' as  the
     'weights' argument.

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

     dksWeights(eset, class)

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

    eset: An 'ExpressionSet' or 'matrix' containing the gene 
          expression data to be used for bootstrapping.

   class: A factor with two or more levels indicating which  class each
          sample in the expression set belongs OR  an integer
          indicating which column of pData(eset)  contains this
          information.

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

     An N x M matrix containing the weights for each gene and each
     class.

_N_o_t_e:

     There are many metrics the user might want to use for weighting. 
     This  convenience function just implements one of the most obvious
     ones.   The user can provide his/her own N x M weight matrix to
     'dksTrain'. The weight matrix calculated by this function will be
     calculated on the fly  if the 'weights' is set to TRUE when
     calling 'dksTrain'.   However, it multiple calls to dksTrain are
     being made (for example when  performing some type of optimization
     or validation), it will save a lot of  time if the weight matrix
     is pre-calculated by a call to this function and the  resulting
     matrix supplied directly to 'dksTrain' rather than having  it
     re-calculate the weight matrix every time.

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

     Eric J. Kort

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

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

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

             data("dks")
             wt <- dksWeights(eset, 1)
             str(wt)

