deGenesANOVA           package:maigesPack           R Documentation

_F_u_n_c_t_i_o_n _t_o _d_o _d_i_f_f_e_r_e_n_t_i_a_l _e_x_p_r_e_s_s_i_o_n _a_n_a_l_y_s_i_s, _u_s_i_n_g _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' and do
     differential expression analysis for the genes onto dataset,
     comparing more than two samples using ANalysis Of VAriance (ANOVA)
     models.

_U_s_a_g_e:

     deGenesANOVA(data=NULL, eBayes=FALSE, retOrig=FALSE,
                  retF=FALSE, doClust=TRUE, ...)

_A_r_g_u_m_e_n_t_s:

    data: object of class 'maigesANOVA'.

  eBayes: logical indicating the use or not (default) of empirical
          Bayes statistics implemented in _limma_ package.

 retOrig: logical indicating if the object of class 'MArrayLM' from
          _limma_ package must be returned. Defaults to FALSE.

    retF: logical asking to return the results associated with the F
          test (TRUE) or with the individual contrasts (FALSE -
          default).

 doClust: logical indicating if the object generated from this analysis
          will be used for cluster analysis. Defaults to TRUE.

     ...: additional parameters to function 'lmFit'.

_D_e_t_a_i_l_s:

     The object of class 'maigesANOVA' of the argument 'data' is
     created by the function 'designANOVA'. This function calculate
     statistics and p-values using the function 'lmFit' from package
     _limma_.

_V_a_l_u_e:

     The result of this function is an object of class 'MArrayLM' when
     'retOrig' is TRUE. When it is FALSE, the result is an object of
     class 'maigesDE' if 'doClust' if FALSE or of class
     'maigesDEcluster' if it is TRUE.

_A_u_t_h_o_r(_s):

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

_S_e_e _A_l_s_o:

     'designANOVA', 'lmFit', 'MArrayLM'.

_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")

     ## Fitting the ANOVA model designed by the above command
     gastro.ANOVAfit = deGenesANOVA(gastro.ANOVA, retF=TRUE)
     gastro.ANOVAfit

