dataTransform            package:Envisage            R Documentation

_G_e_n_e _e_x_p_r_e_s_s_i_o_n _d_a_t_a _f_o_r_m_a_t_t_i_n_g _f_o_r _E_n_v_i_s_a_g_e

_D_e_s_c_r_i_p_t_i_o_n:

     Ensures that the gene expression data from the 'ExpressionSet'
     object is in the correct format for package 'Envisage'.

_U_s_a_g_e:

       dataTransform(expData)  

_A_r_g_u_m_e_n_t_s:

 expData: Object of class 'ExpressionSet' containing gene expression
          data.

_D_e_t_a_i_l_s:

     The 'Envisage' package contains methods allowing the use of 
     linear models (LMs) for analysing significantly changing genes in 
     experiments with a variety of sources of variation, be they
     experimentally controlled variables such as drug treatment or
     time, or non-controlled sources of confounding variation such as
     phenotypic or environmental differences. This allows all sources
     of variation to be considered when analysing for significant
     differential expression, ensuring resulting genes are biologically
     relevent to the experimental question. 

     The function 'dataTransform' is an internal function that ensures
     that the gene expression data (in the form of an object of class
     'ExpressionSet') is in the correct format for future processing.
     In particular, this function ensures that data is in a logged
     format.

     'dataTransform' is an internal function and is not designed to be
     accessed by users.

_V_a_l_u_e:

     Returns a matrix of processed expression values (this may be very
     large).

_A_u_t_h_o_r(_s):

     Sam Robson S.C.Robson@warwick.ac.uk

_R_e_f_e_r_e_n_c_e_s:

     Robson, S. C., Hunter, E., Bird, H., Turner, H. (2008)  _Envisage:
     model-based significance analysis of microarray gene expression
     data_, manuscript in preparation

_S_e_e _A_l_s_o:

     For the main 'Envisage' method, see 'envisage'.

