MArrayTC-class          package:timecourse          R Documentation

_M_i_c_r_o_a_r_r_a_y _T_i_m_e _C_o_u_r_s_e _O_b_j_e_c_t- _c_l_a_s_s

_D_e_s_c_r_i_p_t_i_o_n:

     A list-based class for storing the analysis results from the
     multivariate empirical Bayes models of differential expression for
     longitudinal replicated developmental microarray time course data.
     Objects are normally created by 'mb.long' and 'mb.MANOVA'.

_S_l_o_t_s/_C_o_m_p_o_n_e_n_t_s:

     'MArrayTC' objects do not contain any slots (apart from '.Data')
     but they should contain the following list components:

     '_M': input 'matrix' of log-ratios or log-values of expression for
          a series of microarrays.

     Objects may also contain the following optional components:

     '_p_r_o_p': 'numeric' value giving the proportion of differentially
          expressed genes.

     '_n_u': 'numeric' value containing the estimated amount of
          moderation.

     '_L_a_m_b_d_a': the estimated Lambda.

     '_L_a_m_b_d_a_1': the estimated Lambda1.

     '_e_t_a': the estimated prior scale parameter.

     '_a_l_p_h_a': the estimated common mean of the expected time course
          vector under the null.

     '_a_l_p_h_a._d': the estimated condition-specific      means of the
          expected time course vectors under the alternative.

     '_b_e_t_a': the estimated scale parameter for the common covariance
          matrix of the common expected time course vector under the
          null.

     '_b_e_t_a._d': the estimated condition-specific scale parameters for
          the common covariance matrix of the expected time course
          vectors under the alternative. 

     '_p_e_r_c_e_n_t': 'numeric' matrix containing the percent of moderation 
          corresponding to each sample size for the longitudinal one-
          and two- sample problems.

     '_s_i_z_e': 'numeric' vector or matrix containing the sample sizes for
           all genes corresponding to different biological conditions,
          when the latter are sorted in ascending  order.

     '_c_o_n._g_r_o_u_p': 'numeric' or 'character' vector giving the biological
          condition group of each array. The i_th element of
          'con.group' corresponds to the biological condition of the
          i_th column of 'M'.

     '_r_e_p._g_r_o_u_p': 'numeric' or 'character' vector giving the replicate
          group of each array. The i_th element of 'rep.group'
          corresponds to the  replicate of the i_th column of 'M'.

     '_t_i_m_e._g_r_o_u_p': 'numeric' vector giving the time group of each
          array. The i_th element of 'time.group' corresponds to the 
          time of the i_th column of 'M'.

     '_H_o_t_e_l_l_i_n_g_T_2': 'numeric' vector giving the  tilde{T}^2 statistics
          of differential expression.

     '_M_B': 'numeric' vector giving the MB-statistics of differential
          expression.

     '_p_o_s._H_o_t_e_l_l_i_n_g_T_2': 'numeric' vector whose i_th element corresponds
          to the index of the gene with ranking i in 'HotellingT2'.

     '_p_o_s._M_B': 'numeric' vector whose i_th element corresponds to the
          index of the gene with ranking i in 'MB'.

     '_g_e_n_e_N_a_m_e_s': 'character' vector giving gene names.

     '_d_e_s_c_r_i_p_t_i_o_n_s': 'character' vector giving gene descriptions.

_M_e_t_h_o_d_s:

     MArrayTC extends the  'LargeDataObject' class in package limma,
     and inherits a 'show' method from there.

     The function 'plotProfile' takes 'MArrayTC' as the input argument.

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

     Yu Chuan Tai yuchuan@stat.berkeley.edu

