vsnh                   package:vsn                   R Documentation

_A _f_u_n_c_t_i_o_n _t_h_a_t _t_r_a_n_s_f_o_r_m_s _a _m_a_t_r_i_x _o_f _m_i_c_r_o_a_r_r_a_y _i_n_t_e_n_s_i_t_i_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     A function that transforms a matrix of microarray intensities

_U_s_a_g_e:

     vsnh(y, p)

_A_r_g_u_m_e_n_t_s:

       y: A numeric matrix containing intensity values from an array
          experiment.  It may contain NA values.

       p: A numeric vector with the transformation parameters, of
          length 2*ncol(y).  NA values are not allowed. See Details.

_D_e_t_a_i_l_s:

     The transformation is defined as:

     vsnh(y,p)[k,i] = asinh( p[i] + p[i+d] * y[k,i] )

     where d=ncol(y) is the number of samples,  i=1:d counts over the
     samples, p[1:d] are the additive calibration offsets,
     p[(d+1):(2*d)] are the calibration factors, and k=1:nrow(y) counts
     over the probes.

_V_a_l_u_e:

     A numeric matrix of the same size as y, with the transformed data.

_A_u_t_h_o_r(_s):

     Wolfgang Huber <URL: http://www.dkfz.de/mga/whuber>

_R_e_f_e_r_e_n_c_e_s:

     Variance stabilization applied to microarray data calibration and
     to the quantification of differential expression, Wolfgang Huber,
     Anja von Heydebreck, Holger Sueltmann, Annemarie Poustka, Martin
     Vingron; Bioinformatics (2002) 18 Suppl.1 S96-S104.

_S_e_e _A_l_s_o:

     'vsn'

_E_x_a_m_p_l_e_s:

     ##see vsn

