tranestmult              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 _f_o_r _m_u_l_t_i_p_l_e _p_a_r_a_m_e_t_e_r_s

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

     A sub-function of 'tranest' which searches the best parameters for
     glog transformation.

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

     tranestmult (eS, starting = FALSE, lambda = 1000, alpha = 0, gradtol = 0.001, lowessnorm=FALSE, method=1, max_iter=200, model=NULL)

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

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

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: Set optimization method; default is modified Gauss-Newton
          (nlm). See 'tranest'.

max_iter: Max. number of iterations of 'nlm' to use in optimization.

   model: Model in terms of vlist which is compared to transformed
          expression data. See 'tranest'.

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

     This is primarily an internal function. The normal way of calling
     it would  be to call 'tranest' with the option mult=TRUE.

     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 (not a vector) containing the best parameter for
          'lambda' and the best vector for 'alpha'.

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

     David Rocke and Geun-Cheol Lee

_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/>

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

     'tranest', 'tranest2'

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

     #library
     library(Biobase)
     library(LMGene)

     #data
     data(sample.eS)

     tranpar <- tranestmult(sample.eS, lambda= 500, alpha=50)
     tranpar

