discretize.tscores           package:macat           R Documentation

_D_i_s_c_r_e_t_i_z_e _r_e_g_u_l_a_r_i_z_e_d _t-_s_c_o_r_e_s

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

     discretize.tscores returns a discretized version of the scores in
     the MACATevalScoring object. Discretization is performed by
     comparing the value gene-wise (location-wise) with the symmetric 
     upper and lower quantile given by margin (in percent margin/2
     lower and upper quantile). discretizeAllClasses produces a
     flatfile readable by PYTHON.

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

     discretize.tscores(scores)
     discretizeAllClasses.tscores(data, chrom, nperms=10, kernel=rbf, kernelparams=NULL, step.width=100000)

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

  scores: a MACATevalScoring object obtained from evalScoring 

    data: a MACATData Object containing all expression values,
          geneLocations and labels  (obtained from preprocessedLoader) 

   chrom: chromosome that is discretized 

  nperms: number of permutations for the computation of empirical p
          values (evalScoring) 

  kernel: kernel function used for smoothing one of rbf, kNN,
          basePairDistance or your own 

kernelparams: list of parameters for the kernels 

step.width: size of a interpolation step in basepairs 

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

     The filename for the python flat files are 
     'discrete_chrom_<chrom>_class_<label>.py'  where <chrom> and
     <label> are the names of the chromosome and class label.

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

discretize.tscores: a vector of discretized tscores 

discretizeAllClasses.tscores: creates python flatfiles (see details) 

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

     The MACAT development team

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

     'evalScoring', 'kernels', 'pythondata'

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

       #loaddatapkg("stjudem")
       data(stjd)
       # simple scoring with short running time
       scores = evalScoring(stjd, "T", 1, nperms=100, cross.validate=FALSE)
       discrete = discretize.tscores(scores)

