targetsA2C package:limma R Documentation _C_o_n_v_e_r_t _T_w_o-_C_o_l_o_r _T_a_r_g_e_t_s _D_a_t_a_f_r_a_m_e _f_r_o_m _O_n_e-_R_o_w-_P_e_r-_A_r_r_a_y _t_o _O_n_e-_R_o_w-_P_e_r-_C_h_a_n_n_e_l _D_e_s_c_r_i_p_t_i_o_n: Convert a two-color targets dataframe with one row per array to one with one row per channel. _U_s_a_g_e: targetsA2C(targets, channel.codes=c(1,2), channel.columns=list(Target=c("Cy3","Cy5")), grep=FALSE) _A_r_g_u_m_e_n_t_s: targets: data.frame with one row per array giving information about target samples associated covariates. channel.codes: numeric or character vector of length 2 giving codes for the channels channel.columns: named list of character vectors of length 2. Each entry gives a pair of names of columns in 'targets' which contain channel-specific information. This pair of columns should be assembled into one column in the output. grep: logical, if 'TRUE' then the channel column names are found by 'grep'ing, i.e., the actual column names need only contain the names given by 'channel.columns' as substrings _D_e_t_a_i_l_s: The 'targets' dataframe holds information about the RNA samples used as targets in the microarray experiment. It is often read from a file using 'readTargets'. This function is used to convert the dataframe from an array-orientated format with one row for each array and two columns for the two channels into a channel-orientated format with one row for each individual channel observations. In statistical terms, the first format treats the arrays as cases and treats the channels as repeated measurements. The second format treats the individual channel observations as cases. The second format may be more appropriate if the data is to be analyzed in terms of individual log-intensities. _V_a_l_u_e: data.frame with twice as many rows as 'targets'. Any pair of columns named by 'channel.columns' will now be one column. _A_u_t_h_o_r(_s): Gordon Smyth _S_e_e _A_l_s_o: 'targetsA2C' is used by the 'coerce' method from 'RGList' for 'ExpressionSet' in the convert package. An overview of methods for single channel analysis in limma is given by 07.SingleChannel. _E_x_a_m_p_l_e_s: targets <- data.frame(FileName=c("file1.gpr","file2.gpr"),Cy3=c("WT","KO"),Cy5=c("KO","WT")) targetsA2C(targets)