GlobalAncova.closed       package:GlobalAncova       R Documentation

_M_e_t_h_o_d_s _f_o_r _F_u_n_c_t_i_o_n _G_l_o_b_a_l_A_n_c_o_v_a._c_l_o_s_e_d

_D_e_s_c_r_i_p_t_i_o_n:

     There are three possible ways of using 'GlobalAncova', use
     'methods ? GlobalAncova' for getting more information. Also
     'GlobalAncova.closed' can be invoked with these three
     alternatives.

_M_e_t_h_o_d_s:

     _x_x = "_m_a_t_r_i_x", _t_e_s_t._g_e_n_e_s="_l_i_s_t", _f_o_r_m_u_l_a._f_u_l_l = "_f_o_r_m_u_l_a", _f_o_r_m_u_l_a._r_e_d = "_f_o_r_m_u_l_a", _m_o_d_e_l._d_a_t = "_A_N_Y", _g_r_o_u_p = "_m_i_s_s_i_n_g", _c_o_v_a_r_s = "_m_i_s_s_i_n_g", _t_e_s_t._t_e_r_m_s = "_m_i_s_s_i_n_g" 
          In this method, besides the expression matrix 'xx' and the
          list of gene groups 'test.genes', model formulas for the full
          and reduced model and a data frame 'model.dat' specifying
          corresponding model terms have to be given. Terms that are
          included in the full but not in the reduced model are those
          whose association with differential expression will be
          tested. The arguments 'group', 'covars' and 'test.terms' are
          '"missing"' since they are not needed for this method.

     _x_x = "_m_a_t_r_i_x", _t_e_s_t._g_e_n_e_s="_l_i_s_t", _f_o_r_m_u_l_a._f_u_l_l = "_f_o_r_m_u_l_a", _f_o_r_m_u_l_a._r_e_d = "_m_i_s_s_i_n_g", _m_o_d_e_l._d_a_t = "_A_N_Y", _g_r_o_u_p = "_m_i_s_s_i_n_g", _c_o_v_a_r_s = "_m_i_s_s_i_n_g", _t_e_s_t._t_e_r_m_s = "_c_h_a_r_a_c_t_e_r" 
          In this method, besides the expression matrix 'xx' and the
          list of gene groups 'test.genes', a model formula for the
          full model and a data frame 'model.dat' specifying
          corresponding model terms are required. The character
          argument 'test.terms' names the terms of interest whose
          association with differential expression will be tested. The
          arguments 'formula.red', 'group' and 'covars' are '"missing"'
          since they are not needed for this method.

     _x_x = "_m_a_t_r_i_x", _t_e_s_t._g_e_n_e_s="_l_i_s_t", _f_o_r_m_u_l_a._f_u_l_l = "_m_i_s_s_i_n_g", _f_o_r_m_u_l_a._r_e_d = "_m_i_s_s_i_n_g", _m_o_d_e_l._d_a_t = "_m_i_s_s_i_n_g", _g_r_o_u_p = "_A_N_Y", _c_o_v_a_r_s = "_A_N_Y", _t_e_s_t._t_e_r_m_s = "_m_i_s_s_i_n_g" 
          Besides the expression matrix 'xx' and the list of gene
          groups 'test.genes' a clinical variable 'group' is required.
          Covariate adjustment is possible via the argument 'covars'
          but more complex models have to be specified with the methods
          described above. This method emulates the function call in
          the first version of the package. The arguments
          'formula.full', 'formula.red', 'model.dat' and 'test.terms'
          are '"missing"' since they are not needed for this method.

