lumiT                  package:lumi                  R Documentation

_T_r_a_n_s_f_e_r _t_h_e _I_l_l_u_m_i_n_a _d_a_t_a _t_o _s_t_a_b_i_l_i_z_e _t_h_e _v_a_r_i_a_n_c_e

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

     Transfer the Illumina data to stabilize the variance.

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

     lumiT(x.lumi, method = c("vst", 'log2', 'cubicRoot'), ifPlot = FALSE, stdCorrection = TRUE, simpleOutput = TRUE, verbose = TRUE, ...)

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

  x.lumi: LumiBatch object 

  method: four methods are supported: "vst", "log2", "cubicRoot" 

  ifPlot: determine whether to plot the intermediate results 

stdCorrection: determine transfer the standard error of the mean as the
          standard deviation, used for 'vst' method. 

simpleOutput: determine whether to simplify the output LumiBatch
          object, which will set the se.exprs, detection and beadNum
          slots as NULL. 

 verbose: a boolean to decide whether to print out some messages 

     ...: other parameters used by 'vst' 

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

     lumiT is an interface of difference variance stabilizing
     transformation. See 'vst' for details of VST (Variance Stabilizing
     Transform) of Illumina data.

     The adding of the parameter "stdCorrection" is for the value
     correction of the STDEV (or STDERR) columns when 'vst' method is
     selected. The STDEV (or STDERR) columns of the BeadStudio output
     file is the standard error of the mean of the bead intensities
     corresponding to the same probe. (Thanks Gordon Smyth kindly
     provided this information.). As the variance stabilization (see
     'vst' function) requires the information of the standard deviation
     instead of the standard error of the mean, the value correction is
     required. The corrected value will be x * sqrt(N), where x is the
     old value (standard error of the mean), N is the number of beads
     corresponding to the probe.

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

     Return a LumiBatch object with transformed expression values. It
     also includes the VST transform function and its parameters as
     attributes: "transformFun", "parameter". See 'inverseVST' for
     details.

_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.,  {\it Model-based
     Variance-stabilizing Transformation for Illumina Microarray Data},
     submitted

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

     'vst'

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

     ## load example data
     data(example.lumi)

     ## Do default VST variance stabilizing transform
     lumi.T <- lumiT(example.lumi, ifPlot=TRUE)

