designANOVA            package:maigesPack            R Documentation

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_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

