maCompNormA              package:marray              R Documentation

_W_e_i_g_h_t_s _f_o_r _c_o_m_p_o_s_i_t_e _n_o_r_m_a_l_i_z_a_t_i_o_n

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

     This function is used for composite normalization with intensity
     dependent weights. The function should be used as an argument to
     the main normalization function 'maNormMain'. It only applies when
     two normalization procedures are combined.

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

     maCompNormA()
     maCompNormEq()

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

     A function which takes as arguments 'x' and 'n', the spot average
     log-intensities A and the number of normalization procedures. This
     latter function returns a matrix of weights for combining two
     normalization procedures, rows correspond to spots and columns to
     normalization procedures. The weights for the first procedure are
     given by the empirical cumulative distribution function of the
     spot average log-intensities A. Note that when performing
     composite normalization as described in Yang et al. (2002), the
     first normalization procedure is the global fit and the second
     procedure is the within-print-tip-group fit.

      For 'maCompEq', equal weights are given for each procedure.

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

     Sandrine Dudoit, <URL: http://www.stat.berkeley.edu/~sandrine>,
     Yee Hwa (Jean) Yang.

_R_e_f_e_r_e_n_c_e_s:

     S. Dudoit and Y. H. Yang. (2002). Bioconductor R packages for
     exploratory analysis and normalization of cDNA microarray data. In
     G. Parmigiani, E. S. Garrett, R. A. Irizarry and S. L. Zeger,
     editors, _The Analysis of Gene Expression Data: Methods and
     Software_, Springer, New York.


     Y. H. Yang, S. Dudoit, P. Luu, D. M. Lin, V. Peng, J. Ngai, and T.
     P. Speed (2002). Normalization for cDNA microarray data: a robust
     composite method addressing single and multiple slide systematic
     variation. _Nucleic Acids Research_, Vol. 30, No. 4.

_S_e_e _A_l_s_o:

     'maNormMain', 'maNormLoess', 'ecdf'.

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

     # See examples for maNormMain

