CoHyperGResult-class         package:PCpheno         R Documentation

_C_l_a_s_s "_C_o_H_y_p_e_r_G_R_e_s_u_l_t"

_D_e_s_c_r_i_p_t_i_o_n:

     This class represents the results of a test for
     over-representation of genes in a selected gene set based among
     protein complexes upon the  Hypergeometric distribution.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects is created by calls to the funtion hyperGTest.

_S_l_o_t_s:


     '_p_v_a_l_u_e_s': '"numeric"' vector: the ordered p-values for each
          category term tested.

     '_g_e_n_e_C_o_u_n_t_s': '"integer"' vector: for each category term tested,
          the number of genes from the gene set that are annotated at
          the term.

     '_u_n_i_v_e_r_s_e_C_o_u_n_t_s': '"integer"' vector: for each category term
          tested, the number of genes from the gene universe that are
          annotated at the term.

     '_c_a_t_T_o_G_e_n_e_I_d': Object of class '"list"'.  The names of the list
          are category IDs.  Each element is a vector of gene IDs
          annotated at the given category ID and in the specified gene
          universe.

     '_a_n_n_o_t_a_t_i_o_n': A string giving the name of the chip annotation data
          package used.

     '_g_e_n_e_I_d_s': Object of class '"ANY"': the input vector of gene
          identifiers intersected with the universe of gene identifiers
          used in the computation.  The class of this slot is specified
          as '"ANY"' because gene IDs may be integer or character
          vectors depending on the annotation package.

     '_t_e_s_t_N_a_m_e': A string identifying the testing method used.

     '_p_v_a_l_u_e_C_u_t_o_f_f': Numeric value used a a p-value cutoff.  Used by
          the 'show' method to count number of significant terms.


_E_x_t_e_n_d_s:

     Class '"HyperGResultBase"', directly.

_M_e_t_h_o_d_s:


     _g_e_n_e_C_o_u_n_t_s 'signature(r = "CoHyperGResult")': return an
          '"numeric"' vector: for each category term tested, the number
          of genes from the gene set that are annotated at the term.

     _p_v_a_l_u_e_s 'signature(r = "HyperGResult")': return a '"numeric"'
          vector: the ordered p-values for each category term tested.

     _o_d_d_s_R_a_t_i_o_s 'signature(r = "HyperGResult")': return a '"numeric"'
          vector: the odds ratio for each category term tested.

     _e_x_p_e_c_t_e_d_C_o_u_n_t_s 'signature(r = "HyperGResult")': return a
          '"numeric"' vector: the expected number of genes for each GO
          term tested.

     _u_n_i_v_e_r_s_e_C_o_u_n_t_s 'signature(r = "HyperGResult")': return an
          '"numeric"' vector: for each category term tested, the number
          of genes from the gene universe that are annotated at the
          term.

     _g_e_n_e_I_d_U_n_i_v_e_r_s_e 'signature(r = "CoHyperGResult")': return a list
          named by the protein Complexes.  Each element of the list is
          a vector of gene identifiers (from the gene universe)
          annotated at the corresponding protein complex.

     _s_u_m_m_a_r_y 'signature(r = "CoHyperGResult")': Returns a 'data.frame'
          summarizing the test result. Optional arguments 'pvalue' and
          'categorySize' allow specification of minimum p-value and
          cateogyrSize, respectively. Optional argument 'htmlLinks' is
          a logical value indicating whether to add HTML links (useful
          in conjunction with xtables print method with 'type' set to
          '"html"').


_A_u_t_h_o_r(_s):

     S. Falcon and N. LeMeur

_S_e_e _A_l_s_o:

     'HyperGResultBase-class'

_E_x_a_m_p_l_e_s:

     data(DudleyPhenoM)
     data(ScISIC)

     ## Select genes sensitive to paraquat
     DudleyPhenoL <- apply(DudleyPhenoM,2,function(x) names(which(x==1)))
     paraquat <- DudleyPhenoL[["Paraq"]]

     ## Apply a hypergeometric test
     params <- new("CoHyperGParams",
                   geneIds=paraquat, 
                   universeGeneIds=rownames(ScISIC),
                   annotation="org.Sc.sgd.db",
                   categoryName="ScISIC",
                   pvalueCutoff=0.01,
                   testDirection="over")

     paraquat.complex <- hyperGTest(params)

     ## access the p-values
     pvalues(paraquat.complex)[1:5]

     ## Display a summary of the results
     summary(paraquat.complex)[,1:4]

