normalizeMedianAbsValues        package:limma        R Documentation

_N_o_r_m_a_l_i_z_e _C_o_l_u_m_n_s _o_f _a _M_a_t_r_i_x _t_o _h_a_v_e _t_h_e _M_e_d_i_a_n _A_b_s_o_l_u_t_e _V_a_l_u_e

_D_e_s_c_r_i_p_t_i_o_n:

     Performs scale normalization of an M-value matrix or an A-value
     matrix across a series of arrays. Users do not normally need to
     call these functions directly - use 'normalizeBetweenArrays'
     instead.

_U_s_a_g_e:

     normalizeMedianAbsValues(x)

_A_r_g_u_m_e_n_t_s:

       x: numeric matrix

_D_e_t_a_i_l_s:

     If 'x' is a matrix of log-ratios of expression (M-values) then
     'normalizeMedianAbsValues' is very similar to scaling to equalize
     the median absolute deviation (MAD) as in Yang et al (2001, 2002).
     Here the median-absolute value is used for preference to as to not
     re-center the M-values.

     'normalizeMedianAbsValues' is also used to scale the A-values when
     scale-normalization is applied to an 'MAList' object.

_V_a_l_u_e:

     A numeric matrix of the same size as that input which has been
     scaled so that each column as the same median-absolute value.

_A_u_t_h_o_r(_s):

     Gordon Smyth

_S_e_e _A_l_s_o:

     An overview of LIMMA functions for normalization is given in
     05.Normalization.

_E_x_a_m_p_l_e_s:

     M <- cbind(Array1=rnorm(10),Array2=2*rnorm(10))
     normalizeMedianAbsValues(M)