result.output            package:Envisage            R Documentation

_O_u_t_p_u_t _s_i_g_n_i_f_i_c_a_n_t _g_e_n_e_s _f_o_r _p_a_c_k_a_g_e _E_n_v_i_s_a_g_e

_D_e_s_c_r_i_p_t_i_o_n:

     This function takes the adjusted p-values for the model terms for
     each gene and outputs those genes that are significant to the
     user.

_U_s_a_g_e:

       result.output(adjp, pCutoff, pData, exprData, errorGenes,
         fileResults, MEorINT, param4INT, failedAnova)    

_A_r_g_u_m_e_n_t_s:

    adjp: An object of class 'data.frame' containing the adjusted
          p-values for each model term for each gene.

 pCutoff: A number defining the p value cutoff to be used in 
          significance analysis.  Must be between 0 and 1 (default
          0.05.)

   pData: An object of class 'phenoData' containing the phenotypic
          information for the experiment.

exprData: A matrix of expression values for each gene for each sample.
          Usually calculated using 'exprs' on an object of class
          'ExpressionSet'.

errorGenes: A list of the genes that failed and the model terms for
          which aliasing was detected.

fileResults: The folder in which to save the results of the modelling
          procedure. Defaults to the current working directory.

 MEorINT: Character string defining whether to look at first order
          interactions ("INT") or only main effect terms ("ME") in the
          model.

param4INT: A character vector that defines the model variables for
          which interactions should be calculated.

failedAnova: A vector of genes for which the Anova Type II sum of
          squares failed, indicating model aliasing.

_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 'result.output' outputs significant gene lists for
     each of the terms within the model. For each model term, a vector
     is created containing any genes for which the adjusted p-value for
     that terms is below 'pCutoff' (along with the corresponding
     adjusted p-value). A list, 'results', is created containing all
     such data frames for all model terms.

     The resulting p-values for each model term are output in a tab
     delimitted text file within the directory 'EnvisageResults/' which
     is created within the directory specified by 'fileResults'
     (defaults to the working directory). If this  directory already
     exists, existing files are appended with the suffix 'OLD' to
     distingiush them from the most recent files. This avoids
     overwriting data, but please be aware that continually writing to
     the same file will result in an increase in the directory size.

     Also created are two output files pertaining to aliasing
     information. 'AliasGenes.txt' gives the names of the genes that
     show problems due to model aliasing, and 'AliasReport.txt' gives a
     more in depth report on the variable levels for which aliasing was
     detected. For more information, please see the package vignette.

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

_V_a_l_u_e:

     A list 'results' is returned containing the following slots:

model term: For each model term, significnat genes and their p-values
          are comntained within individual slots.

AliasGenes: A vector of genes which showed problems through the
          modelling procedure due to aliasing in the model.

_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'.

