sagmbSimulateData            package:vsn            R Documentation

_S_i_m_u_l_a_t_e _d_a_t_a _a_n_d _a_s_s_e_s_s _v_s_n'_s _p_a_r_a_m_e_t_e_r _e_s_t_i_m_a_t_i_o_n

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

     Functions to validate and assess the performance of vsn through
     simulation of data.

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

     sagmbSimulateData(n=8064, d=2, de=0, up=0.5, nrstrata=1)
     sagmbAssess(h1, sim)

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

       n: Numeric. Number of probes (rows).

       d: Numeric. Number of arrays (columns).

      de: Numeric. Fraction of differentially expressed genes.

      up: Numeric. Fraction of up-regulated genes among the
          differentially expressed genes.

nrstrata: Numeric. Number of probe strata.

      h1: Matrix. Calibrated and transformed data, according, e.g., to
          vsn

     sim: List. The output of a previous call to 'sagmbSimulateData',
          see Value

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

     Please see the vignette.

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

     For 'sagmbSimulateData', a list with four components: 'hy', an 'n
     x d' matrix with the true (=simulated) calibrated, transformed
     data; 'y', an 'n x d' matrix with the simulated uncalibrated raw
     data - this is intended to be fed into 'vsn'; 'is.de', a logical
     vector of length 'n', specifying which probes are simulated to be
     differentially expressed. 'strata', a factor of length 'n'.

     For 'sagmbSimulateData', a number: the root mean squared
     difference between true and estimated transformed data.

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

     Wolfgang Huber <URL: http://www.dkfz.de/abt0840/whuber>

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

     Wolfgang Huber, Anja von Heydebreck, Holger Sueltmann, Annemarie
     Poustka, and Martin Vingron (2003) "Parameter estimation for the
     calibration and variance stabilization of microarray data",
     Statistical Applications in Genetics and Molecular Biology: Vol.
     2: No. 1, Article 3. http://www.bepress.com/sagmb/vol2/iss1/art3

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

     'vsn'

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

       sim <- sagmbSimulateData(nrstrata=4)
       ny  <- vsn(sim$y, strata=sim$strata)
       res <- sagmbAssess(exprs(ny), sim)
       res

