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 = NULL, model = NULL, 
         levels = NULL, adjust = NULL, permutation = FALSE, nperm = NULL, 
         sampling = FALSE, ndraws = NULL, verbose = TRUE) 

_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

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: Indicates the model the test uses:  Use 'model = "logistic"'
          for a two-valued outcome 'Y'  (the default) or 'model =
          "linear"' for a continuous  outcome. If 'model' is not
          supplied, globaltest will try to determine the model from
          'Y'.

  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.

  adjust: Confounders or risk factors for which the test must  be
          adjusted. Must be either a data frame or the names of 
          covariates in the phenoData slot of the exprSet 'X'

permutation: A logical flag. If 'TRUE' 'nperm'  permutations are used
          to calculate the p-value instead of the  asymptotic formulas.
          Recommended for small sample size. Not  possible if an
          adjusted globaltest is used.

   nperm: The number permutations used. The default is 10,000.  If a
          number is specified for 'nperm', 'permutation' is 
          automatically set to 'TRUE'.

sampling: A logical flag. If 'TRUE' 'ndraws'  random sets of genes are
          drawn with the same number of genes as  the tested group.
          Using this draws, an extra column of output  'comparative.p'
          is generated, reporting how many of these  random sets have a
          lower p-value than the tested group.

  ndraws: The number of random groups of genes to be drawn. The default
          is 1,000. If a number is specified for 'ndraws', 'sampling'
          is automatically set to 'TRUE'.

 verbose: Prints some progress information if set to 'TRUE'

     .

_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 outcome. 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-class'.

_N_o_t_e:

     If the number of rows of a matrix 'X' does not match  the length
     of the vector 'Y', but the number of columns  does, the matrix 'X'
     given is tacitly replaced by  't(X)' to make 'X' and 'Y' match. A
     warning is  printed if 'X' is square.

_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',  '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

