tranest                package:LMGene                R Documentation

_G_l_o_g _t_r_a_n_s_f_o_r_m_a_t_i_o_n _p_a_r_a_m_e_t_e_r _e_s_t_i_m_a_t_i_o_n _f_u_n_c_t_i_o_n

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

     Finds the best parameters for glog transformation.

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

     tranest(eS, ngenes = -1, starting = FALSE, lambda = 1000, alpha = 0, gradtol = 0.001, lowessnorm = FALSE, method=1, mult=FALSE, model=NULL)

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

      eS: Array data. must be an 'ExpressionSet' object.

  ngenes: Number of genes that is going to be used for the parameter
          estimation.

starting: TRUE, if the given initial parameter values are used.

  lambda: Initial parameter value for lambda.

   alpha: Initial parameter value for alpha.

 gradtol: a positive scalar giving the tolerance at which the scaled
          gradient is considered close enough to zero to terminate the
          algorithm.

lowessnorm: TRUE, if lowess method is going to be used.

  method: Determines optimization method. Default is 1, which
          corresponds to a Newton-type method (see 'nlm'). Method 2 is
          based on the Nelder-Mead method (see 'optim').

    mult: If true, tranest will use a vector alpha with one entry per
          sample. Default is false (same alpha for every sample).

   model: Specifies model to be used. Default is to use all variables
          from eS without interactions. See details.

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

     The argument 'eS' must be an 'ExpressionSet' object from the
     Biobase package.  If you have a data in a 'matrix' and information
     about the considered factors, then you can use 'neweS' to convert
     the data into an 'ExpressionSet' object. Please see 'neweS' in
     more detail.

     The 'model' argument is an optional character string, constructed
     like the right-hand side of a formula for lm. It specifies which
     of the variables in the 'ExpressionSet' will be used in the model
     and whether interaction terms will be included. If 'model=NULL',
     it uses all variables from the 'ExpressionSet' without
     interactions. Be careful of using interaction terms with factors;
     this often leads to overfitting, which will yield an error.

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

 tranpar: A list containing the best parameter for 'lambda' and
          'alpha'.

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

     David Rocke, Geun-Cheol Lee and John Tillinghast

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

     B. Durbin and D.M. Rocke, (2003) Estimation of Transformation
     Parameters for Microarray Data,  Bioinformatics, 19, 1360-1367.

     <URL: http://www.idav.ucdavis.edu/~dmrocke/>

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

     #library
     library(Biobase)
     library(LMGene)

     #data
     data(sample.eS)

     tranpar <- tranest(sample.eS, 100)
     tranpar
     tranpar <- tranest(sample.eS, mult=TRUE)
     tranpar

