designANOVA            package:maigesPack            R Documentation

_F_u_n_c_t_i_o_n _t_o _c_o_n_s_t_r_u_c_t _d_e_s_i_g_n _a_n _c_o_n_t_r_a_s_t_s _m_a_t_r_i_c_e_s _f_o_r _A_N_O_V_A _m_o_d_e_l_s

_D_e_s_c_r_i_p_t_i_o_n:

     This function takes an object of class 'maiges' together with
     other arguments and construct the matrices of design and contrasts
     for adjusting ANOVA models. The design matrix are generated using
     the function 'model.matrix'.

_U_s_a_g_e:

     designANOVA(data=NULL, factors=names(data@Slabels), model=NULL,
                 contrasts=NULL, ...)

_A_r_g_u_m_e_n_t_s:

    data: object of class 'maiges'.

 factors: vector of character strings specifying the sample labels IDs
          to be used as factors in the models.

   model: a formula specifying the model to be fitted.

contrasts: character vector specifying the contrasts to be done. This
          is done by the function 'makeContrasts' from package _limma_.
          Pay attention that we use the treatment-control
          parametrisation.

     ...: additional parameters for function 'model.matrix'.

_V_a_l_u_e:

     The result of this function is an object of class 'maigesANOVA'.

_A_u_t_h_o_r(_s):

     Gustavo H. Esteves <gesteves@vision.ime.usp.br>

_S_e_e _A_l_s_o:

     'model.matrix', 'makeContrasts', 'deGenesANOVA'.

_E_x_a_m_p_l_e_s:

     ## Loading the dataset
     data(gastro)

     ## Constructing a maigesANOVA object for the 'Tissue' sample label using
     ## default model (simple linear model with intercept) and contrasts (all
     ## parameters are equal between themselves)
     gastro.ANOVA = designANOVA(gastro.summ, factors="Tissue")
     gastro.ANOVA

