normexp.signal             package:limma             R Documentation

_E_x_p_e_c_t_e_d _S_i_g_n_a_l _G_i_v_e_n _O_b_s_e_r_v_e_d _F_o_r_e_g_r_o_u_n_d _U_n_d_e_r _N_o_r_m_a_l+_E_x_p _M_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     Adjust foreground intensities for observed background using
     Normal+Exp Model. This function is called by 'backgroundCorrect'
     and is not normally called directly by the user.

_U_s_a_g_e:

     normexp.signal(par, x)

_A_r_g_u_m_e_n_t_s:

     par: numeric vector containing the parameters of the Normal+Exp
          distribution, see 'normexp.fit' for details.

       x: numeric vector of (background corrected) intensities

_D_e_t_a_i_l_s:

     In general the vector 'normmean' is computed conditional on
     background at each spot.

_V_a_l_u_e:

     Numeric vector containing adjusted intensities.

_A_u_t_h_o_r(_s):

     Gordon Smyth

_R_e_f_e_r_e_n_c_e_s:

     McGee, M., and Chen, Z. (2006). Parameter estimation for the
     exponential-normal convolution model for background correction of
     Affymetrix GeneChip data. _Stat Appl Genet Mol Biol_, 5(1),
     Article 24.

     Ritchie, M. E., Silver, J., Oshlack, A., Silver, J., Holmes, M.,
     Diyagama, D., Holloway, A., and Smyth, G. K. (2007). A comparison
     of background correction methods for two-colour microarrays.
     _Bioinformatics_ <URL:
     http://bioinformatics.oxfordjournals.org/cgi/content/abstract/btm412>

_S_e_e _A_l_s_o:

     'normexp.fit'

     An overview of background correction functions is given in
     '04.Background'.

_E_x_a_m_p_l_e_s:

     # See normexp.fit