vst                   package:lumi                   R Documentation

_V_a_r_i_a_n_c_e _S_t_a_b_i_l_i_z_i_n_g _T_r_a_n_s_f_o_r_m_a_t_i_o_n

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

     Stabilizing the expression variance based on the bead level
     expression variance and mean relations

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

     vst(u, std, nSupport = min(length(u), 500), method = c('iterate', 'quadratic'), ifPlot = FALSE)

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

       u: mean expression of the beads with same sequence 

     std: expression standard deviation of the beads with same sequence 

nSupport: the number of down-sampling to speed processing 

  method: methods of fitting the relations between expression variance
          and mean relations 

  ifPlot: plot intermediate results or not 

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

     The variance-stabilizing transformation (VST) takes the advantage
     of larger number of technical replicates available on the Illumina
     microarray. It models the mean-variance relationship of the
     within-array technical replicates at the bead level of Illumina
     microarray. An arcsinh transform is then applied to stabilize the
     variance. See reference for more details.

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

     Return the transformed (variance stabilized) expression values.

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

     Pan Du, Simon Lin

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

     Lin, S.M., Du, P., Kibbe, W.A.,  "Model-based Variance-stabilizing
     Transformation for Illumina Mi-croarray Data", submitted

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

     'lumiT', 'inverseVST'

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

     ## load example data
     data(example.lumi)

     ## get the gene expression mean for one chip
     u <- exprs(example.lumi)[,1]
     ## get the gene standard deviation for one chip
     std <- se.exprs(example.lumi)[,1]

     ## do variance stabilizing transform
     transformedU <- vst(u, std)

     ## do variance stabilizing transform with plotting intermediate result 
     transformedU <- vst(u, std, ifPlot=TRUE)

