subColSummarize        package:preprocessCore        R Documentation

_S_u_m_m_a_r_i_z_e _c_o_l_u_m_n_s _w_h_e_n _d_i_v_i_d_e_d _i_n_t_o _g_r_o_u_p_s _o_f _r_o_w_s

_D_e_s_c_r_i_p_t_i_o_n:

     These functions summarize columns of a matrix when the rows of the
     matrix are classified into different groups

_U_s_a_g_e:

     subColSummarizeAvg(y, group.labels)
            subColSummarizeAvgLog(y, group.labels)
            subColSummarizeBiweight(y, group.labels)
            subColSummarizeBiweightLog(y, group.labels)
            subColSummarizeLogAvg(y, group.labels)
            subColSummarizeLogMedian(y, group.labels)
            subColSummarizeMedian(y, group.labels)
            subColSummarizeMedianLog(y, group.labels)
            subColSummarizeMedianpolish(y, group.labels)
            subColSummarizeMedianpolishLog(y, group.labels)
            convert.group.labels(group.labels)

_A_r_g_u_m_e_n_t_s:

       y: A numeric 'matrix'

group.labels: A vector to be treated as a factor variable. This is used
          to assign each row to a group. NA values should be used to
          exclude rows from consideration

_D_e_t_a_i_l_s:

     These functions are designed to summarize the columns of a matrix
     where the rows of the matrix are assigned to groups. The
     summarization is by column across all rows in each group.

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_A_v_g Summarize by taking mean

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_A_v_g_L_o_g 'log2' transform the data and then take means
        in column-wise manner

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_B_i_w_e_i_g_h_t Use a one-step Tukey Biweight to summarize
        columns

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_B_i_w_e_i_g_h_t_L_o_g 'log2' transform the data and then use a
        one-step Tukey Biweight to summarize columns

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_L_o_g_A_v_g Summarize by taking mean and then taking
        'log2'

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_L_o_g_M_e_d_i_a_n Summarize by taking median and then taking
        'log2'

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_M_e_d_i_a_n Summarize by taking median

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_M_e_d_i_a_n_L_o_g 'log2' transform the data and then
        summarize by taking median

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_M_e_d_i_a_n_p_o_l_i_s_h Use the median polish to summarize each
        column, by also using a row effect (not returned)

   _s_u_b_C_o_l_S_u_m_m_a_r_i_z_e_M_e_d_i_a_n_p_o_l_i_s_h_L_o_g 'log2' transform the data and then
        use the median polish to summarize each column, by also using a
        row effect (not returned)

_V_a_l_u_e:

     A 'matrix' containing column summarized data. Each row corresponds
     to data column summarized over a group of rows.

_A_u_t_h_o_r(_s):

     B. M. Bolstad <bmb@bmbolstad.com>

_E_x_a_m_p_l_e_s:

     ### Assign the first 10 rows to one group and
     ### the second 10 rows to the second group
     ###
     y <- matrix(c(10+rnorm(50),20+rnorm(50)),20,5,byrow=TRUE)

     subColSummarizeAvgLog(y,c(rep(1,10),rep(2,10)))
     subColSummarizeLogAvg(y,c(rep(1,10),rep(2,10)))
     subColSummarizeAvg(y,c(rep(1,10),rep(2,10)))

     subColSummarizeBiweight(y,c(rep(1,10),rep(2,10)))
     subColSummarizeBiweightLog(y,c(rep(1,10),rep(2,10)))

     subColSummarizeMedianLog(y,c(rep(1,10),rep(2,10)))
     subColSummarizeLogMedian(y,c(rep(1,10),rep(2,10)))
     subColSummarizeMedian(y,c(rep(1,10),rep(2,10)))


     subColSummarizeMedianpolishLog(y,c(rep(1,10),rep(2,10)))
     subColSummarizeMedianpolish(y,c(rep(1,10),rep(2,10)))