rankIvariantNormalise       package:beadarray       R Documentation

_R_a_n_k _I_n_v_a_r_i_a_n_t _n_o_r_m_a_l_i_s_e _d_a_t_a _i_n _a _m_a_t_r_i_x

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

     Normalise expression matrix using rank invariant genes

_U_s_a_g_e:

     rankInvariantNormalise(exprs, T)

_A_r_g_u_m_e_n_t_s:

   exprs: a matrix of expression values

       T: A target distribution vector to normalise the data to. The
          default is NULL in which case the average quantiles are used

_D_e_t_a_i_l_s:

     Using the 'normalize.invariantset' function from the affy package,
      we find a list of rank invariant genes whose rank does not change
     significantly  between the columns of 'exprs'.  We then fit a
     normalising curve to each  array using the values of the rank
     invariant genes of the array and a target distribution.

     The target distribution may be specified by the user and by
     default is the vector of average quantiles across all arrays.

_V_a_l_u_e:

     Matrix of normalised expression data with the same dimensions as
     'exprs'.

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

     Mark Dunning

_E_x_a_m_p_l_e_s:

     data(BSData)

     BSData.ri  = assayDataElementReplace(BSData, "exprs", rankInvariantNormalise(exprs(BSData)))

