normalize.invariantset package:affy R Documentation _I_n_v_a_r_i_a_n_t_e _S_e_t _n_o_r_m_a_l_i_z_a_t_i_o_n _D_e_s_c_r_i_p_t_i_o_n: Normalize arrays in an 'AffyBatch' using an invariant set. _U_s_a_g_e: normalize.AffyBatch.invariantset(abatch, prd.td=c(0.003, 0.007), verbose=FALSE,baseline.type=c("mean","median","pseudo-mean","pseudo-median"),type=c("separate","pmonly","mmonly","together")) normalize.invariantset(data, ref, prd.td=c(0.003,0.007)) _A_r_g_u_m_e_n_t_s: abatch: an 'AffyBatch' data: a vector of intensities on a chip (to normalize to the reference). ref: a vector of reference intensities. prd.td: cutoff parameter (details in the bibliographic reference) baseline.type: Specify how to determine the baseline array type: A string specifying how the normalization should be applied. See details for more. verbose: A flag to have a dumps throughout the normalization _D_e_t_a_i_l_s: The set of invariant intensities between 'data' and 'ref' is found through an iterative process (based on the respective ranks the intensities). This set of intensities is used to generate a normalization curve by smoothing. The 'type' argument should be one of '"separate","pmonly","mmonly","together"' which indicates whether to normalize only one probe type (PM,MM) or both together or separately. _V_a_l_u_e: Respectively a 'AffyBatch' of normalized objects, or a vector of normalized intensities, with an attribute "invariant.set" holding the indexes of the 'invariant' intensities. _A_u_t_h_o_r(_s): L. Gautier (Thanks to Cheng Li for the discussions about the algorithm.) _R_e_f_e_r_e_n_c_e_s: Cheng Li and Wing Hung Wong, Model-based analysis of oligonucleotides arrays: model validation, design issues and standard error application. Genome Biology 2001, 2(8):research0032.1-0032.11 _S_e_e _A_l_s_o: 'normalize' to normalize 'AffyBatch' objects.