normalize-methods            package:affy            R Documentation

_N_o_r_m_a_l_i_z_e _A_f_f_y_m_e_t_r_i_x _P_r_o_b_e _L_e_v_e_l _D_a_t_a - _m_e_t_h_o_d_s

_D_e_s_c_r_i_p_t_i_o_n:

     Method for normalizing Affymetrix Probe Level Data

_U_s_a_g_e:

     normalize.methods(object)
     bgcorrect.methods()
     upDate.bgcorrect.methods(x)
     pmcorrect.methods()
     upDate.pmcorrect.methods(x)

_A_r_g_u_m_e_n_t_s:

  object: An 'AffyBatch'.

       x: A character vector that will replace the existing one.

_D_e_t_a_i_l_s:

     If 'object' is an 'AffyBatch' then 'normalize(object)' returns an
     'AffyBatch' with the intensities normalized using the methodology
     specified by 'getOption("BioC")$affy$normalize.method'. The affy
     package default is 'quantiles'.

     Other methodologies can be used by specifying them with the
     'method' argument. For example to use the invariant set
     methodology described by Li and Wong (2001) one would type:
     'normalize(object, method="invariantset")'.

     Further arguments passed by '...', apart from 'method',  are
     passed along to the  function responsible for the methodology
     defined by the 'method' argument. 

     A character vector of _nicknames_ for the  methodologies available
     is returned by 'normalize.methods(object))', where 'object'  is an
      'AffyBatch', or simply by typing 'normalize.AffyBatch.methods'.
     If the nickname of a method is called "loess", the help page for
     that  specific methodology can be accessed by typing
     '?normalize.loess'. 

     For more on the normalization methodologies currently implemented
     please refer to the vignette `Custom Processing Methods'.

     To add your own normalization procedures please refer to the
     customMethods vignette.

     The functions: 'bgcorrect.methods', 'pmcorrect.methods', provide
     access to internal vectors listing the corresponding capabilities.

_S_e_e _A_l_s_o:

     'AffyBatch-class', 'normalize'.

_E_x_a_m_p_l_e_s:

     if (require(affydata)) {
       data(Dilution)
       normalize.methods(Dilution)
       generateExprSet.methods()
       bgcorrect.methods()
       pmcorrect.methods()
     }

