predict.tsp              package:tspair              R Documentation

_P_r_e_d_i_c_t_i_o_n _b_a_s_e_d _o_n _a _t_s_p _o_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     This function can be used to predict outcome values for a data set
     based on a tsp object.

_U_s_a_g_e:

       ## S3 method for class 'tsp':
       predict(object,dat=NULL,select=NULL,...)

_A_r_g_u_m_e_n_t_s:

  object: A tsp object

     dat: Can take two values: (a) an m genes by n arrays matrix of
          expression data or (b) an eSet object

  select: An indicator of which TSP to use,defaults to the first TSP.

     ...: Plotting arguments (ignored)

_D_e_t_a_i_l_s:

     predict() accepts a tsp object calculated on an expression set or
     gene expression matrix. If no other data set is included, the tsp
     predictions for the original data set are produced. If a second
     gene expression matrix or expression set is included, predict()
     looks for the gene names of the TSP in tspobj and attempts to
     match them in the rownames or featureNames of the gene expression
     matrix. If rownames or featureNames are not available, the
     prediction is based on the row numbers.  If a match is identified,
     predict() makes a prediction for each gene based on the output.

_V_a_l_u_e:

 predict: A class prediction for each array of dat based on the TSP
          from tspobj

_A_u_t_h_o_r(_s):

     Jeffrey T. Leek jtleek@jhu.edu

_R_e_f_e_r_e_n_c_e_s:

     D. Geman, C. d'Avignon, D. Naiman and R. Winslow, "Classifying
     gene expression profiles from pairwise mRNA comparisons," 
     Statist. Appl. in Genetics and Molecular Biology, 3, 2004.

     A.C. Tan, D.Q. Naiman, L. Xu, R.L. Winslow, D. Geman, "Simple
     decision rules for classifying human cancers from gene expression
     profiles," Bioinformatics, 21:3896-3904, 2005.

_S_e_e _A_l_s_o:

     'tspplot','ts.pair', 'tspcalc','tspsig','summary.tsp'

_E_x_a_m_p_l_e_s:

       ## Not run: 
       ## Load data
       data(tspdata) 

       ## Run tspcalc() on a data matrix and grp vector
       tsp1 <- tspcalc(dat,grp)

       ## Get predictions for a new eSet or data matrix
       predict.tsp(tsp1,dat2,1)
       predict(tsp1,eSet2,1)
      ## End(Not run)

