globaltest            package:globaltest            R Documentation

_G_l_o_b_a_l _T_e_s_t

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

     In microarray data, tests a (list of) group(s) of  genes for
     significant association with a given clinical variable.

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

     globaltest(X, Y, test.genes, model, 
         levels, d, event = 1, adjust, ...) 

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

       X: Either a matrix of gene expression data, where columns
          correspond to samples and rows to genes or a Bioconductor
          'exprSet'. The data  should be properly normalized beforehand
          (and log- or otherwise  transformed), but missing values are
          allowed (coded as  'NA'). Gene and sample names can be
          included as the row and  column names of 'X'.

       Y: A vector with the clinical outcome of interest, having one
          value for each sample. If 'X' is an  'exprSet' it can also be
          the  name of a covariate in the  'phenoData' slot of the 
          exprSet, or a 'formula' object using   these names. If the
          clinical outcome is survival, 'Y' should  contain the
          survival times.

test.genes: Either a vector or a list of vectors. Indicates  the
          group(s) of genes to be tested. Each vector in  'test.genes'
          can be given in three formats. Either it can be  a vector
          with 1 ('TRUE') or 0 ('FALSE') for each gene  in 'X', with 1
          indicating that the gene belongs to the  group. Or it can be
          a vector containing the column numbers (in  'X') of the genes
          belonging to the group. Or it can be a  subset of the
          rownames or 'geneNames'  for 'X'.

   model: Globaltest will try to determine the correct model from  the
          input of 'Y' and 'd'. To override the automatic choice, use
          'model = "logistic"' for a two-valued outcome 'Y' ,  'model =
          "linear"' for a continuous outcome and  'model = "survival"'
          for a survival outcome.

  levels: If 'Y' is a factor (or a category in the PhenoData slot of
          'X')  and contains more than 2 levels: 'levels' is a vector
          of levels of 'Y' to test. If  'levels' is length 2: test
          these 2 groups against each other.  If levels is length 1:
          test that level against the others.

       d: A vector or the name of a covariate in the phenoData slot  of
          the exprSet 'X', to indicate which samples experienced an
          event.  Providing a value for 'd' automatically sets 'model =
          "survival"'

   event: The value or values of 'd' that indicates that  there was an
          event.

  adjust: Confounders or risk factors for which the test must  be
          adjusted. Must be either a data frame or (if 'X' is an 
          exprSet) the names of covariates in the phenoData slot 'X' 
          or a 'formula' object using these  names. Default: no
          adjustment.

     ...: Captures deprecated input for compatibility with older
          versions of  globaltest.

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

     The Global Test tests whether a group of genes (of any  size from
     one single gene to all genes on the array) is  significantly
     associated with a clinical variable. The group could  be for
     example a known pathway, an area on the genome or the set  of all
     genes. The test investigates whether samples with similar 
     clinical outcomes tend to have similar gene expression patterns. 
     For a significant result it is not necessary that the genes in 
     the group have similar expression patterns, only that many of 
     them are correlated with the outcome.

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

     The function returns an object of class  'gt.result'.

_N_o_t_e:

     The options globaltest options sampling and permutation  have been
     replaced by separate functions from version 3.0. See  'sampling'
     and 'permutations'.

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

     Jelle Goeman: j.j.goeman@lumc.nl; Jan Oosting

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

     J. J. Goeman, S. A. van de Geer, F. de Kort and J. C.  van
     Houwelingen, 2004, _A global test for groups of genes:  testing
     association with a clinical outcome_,  _Bioinformatics_ 20 (1)
     93-99. See also the vignette  Globaltest.pdf included with this
     package.

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

     'geneplot', 'sampleplot',  'sampling', 'permutations', 
     'checkerboard', 'regressionplot'.

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

         data(exampleX)      # Expression data (40 samples; 1000 genes)
         data(exampleY)      # Clinical outcome for the 40 samples
         pathway1 <- 1:25    # A pathway contains genes 1 to 25
         pathway2 <- 26:50   # another pathway
         gt <- globaltest(exampleX, exampleY, list(pathway1,pathway2))
         gt

