justmmgMOS               package:puma               R Documentation

_C_o_m_p_u_t_e _m_m_g_m_o_s _D_i_r_e_c_t_l_y _f_r_o_m _C_E_L _F_i_l_e_s

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

     This function converts CEL files into an 'exprReslt' using mmgmos.

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

     justmmgMOS(..., filenames=character(0),
               widget=getOption("BioC")$affy$use.widgets,
               compress=getOption("BioC")$affy$compress.cel,
               celfile.path=getwd(),
               sampleNames=NULL,
               phenoData=NULL,
               description=NULL,
               notes="",
               background=TRUE, gsnorm=c("median", "none", "mean", "meanlog"), savepar=FALSE, eps=1.0e-6)

     just.mmgmos(..., filenames=character(0),
                phenoData=new("AnnotatedDataFrame"),
                description=NULL,
                notes="",
                compress=getOption("BioC")$affy$compress.cel,
                background=TRUE, gsnorm=c("median", "none", "mean", "meanlog"), savepar=FALSE, eps=1.0e-6)

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

     ...: file names separated by comma.

filenames: file names in a character vector.

  widget: a logical specifying if widgets should be used.

compress: are the CEL files compressed?

celfile.path: a character denoting the path 'ReadAffy' should look for
          cel files.

sampleNames: a character vector of sample names to be used in the
          'AffyBatch'.

phenoData: an 'AnnotatedDataFrame' object

description: a 'MIAME' object

   notes: notes 

background: Logical value. If 'TRUE', then perform background
          correction before applying mmgmos.

  gsnorm: character. specifying the algorithm of global scaling
          normalisation.

 savepar: Logical value. If 'TRUE', the the estimated parameters of the
          model are saved in file par_mmgmos.txt and phi_mmgmos.txt.

     eps: Optimisation termination criteria.

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

     This method should require much less RAM than the conventional
     method of first creating an 'AffyBatch' and then running 'mmgmos'.

     Note that this expression measure is given to you in log base 2
     scale. This differs from most of the other expression measure
     methods.

     The algorithms of global scaling normalisation can be one of
     "median", "none", "mean", "meanlog". "mean" and "meanlog" are
     mean-centered normalisation on raw scale and log scale
     respectively, and "median"  is median-centered normalisation.
     "none" will result in no global scaling normalisation being
     applied.

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

     An 'exprReslt'.

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

     Related class 'exprReslt-class' and related method 'mmgmos'

