mas5                   package:xps                   R Documentation

_M_A_S _5._0 _E_x_p_r_e_s_s_i_o_n _M_e_a_s_u_r_e

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

     This function converts a 'DataTreeSet' into an 'ExprTreeSet' using
     the XPS implementation of Affymetrix's MAS 5.0 expression measure.

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

     mas5(xps.data,
          filename   = character(0),
          filedir    = getwd(),
          tmpdir     = "",
          normalize  = FALSE,
          sc         = 500,
          option     = "transcript",
          exonlevel  = "",
          update     = FALSE,
          xps.scheme = NULL,
          add.data   = TRUE,
          verbose    = TRUE)

     xpsMAS5(object, ...)

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

xps.data: object of class 'DataTreeSet'.

filename: file name of ROOT data file.

 filedir: system directory where ROOT data file should be stored.

  tmpdir: optional temporary directory where temporary ROOT files
          should be stored.

normalize: logical. If 'TRUE' scale normalization is used after an
          'ExprTreeSet' is obtained.

      sc: value at which all arrays will be scaled to.

  option: option determining the grouping of probes for summarization,
          one of  transcript, exon, probeset; exon arrays only.

exonlevel: exon annotation level determining which probes should be
          used for summarization; exon/genome arrays only.

  update: logical. If 'TRUE' the existing ROOT data file 'filename'
          will be updated.

xps.scheme: optional alternative 'SchemeTreeSet'.

add.data: logical. If 'TRUE' expression data will be included as slot
          'data'.

 verbose: logical, if 'TRUE' print status information.

  object: object of class 'DataTreeSet'.

     ...: arguments
          'filename','filedir','tmpdir','option','exonlevel','xps.scheme'.

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

     This function computes the Affymetrix MAS 5.0 expression measure
     as implemented in XPS. Although this implementation is based on
     the Affymetrix sadd_whitepaper.pdf, it  can be used to compute
     an expression level for both expression arrays and exon arrays. 
     For exon arrays it is necessary to supply the requested 'option'
     and 'exonlevel'.

     Following 'option's are valid for exon arrays:

       'transcript':  expression levels are computed for transcript clusters, i.e. probe sets containing the same transcript_cluster_id.
       'exon':        expression levels are computed for exon clusters, i.e. probe sets containing the same exon_id, where each exon cluster consists of one or more 'probeset's.
       'probeset':    expression levels are computed for individual probe sets, i.e. for each probeset_id.

     Following 'exonlevel' annotations are valid for exon arrays:

         'core':          probesets supported by RefSeq and full-length GenBank transcripts.
         'metacore':      core meta-probesets.
         'extended':      probesets with other cDNA support.
         'metaextended':  extended meta-probesets.
         'full':          probesets supported by gene predictions only.
         'metafull':      full meta-probesets.
         'ambiguous':     ambiguous probesets only.
         'affx':          standard AFFX controls.
         'all':           combination of above (including affx).

     Following 'exonlevel' annotations are valid for whole genome
     arrays:

         'core':      probesets with category unique, similar and mixed.
         'metacore':  probesets with category unique only.
         'affx':      standard AFFX controls.
         'all':       combination of above (including affx).

     Exon levels can also be combined, with following combinations
     being most useful:

       'exonlevel="metacore+affx"':       core meta-probesets plus AFFX controls
       'exonlevel="core+extended"':       probesets with cDNA support
       'exonlevel="core+extended+full"':  supported plus predicted probesets

     Exon level annotations are described in the Affymetrix whitepaper 
     exon_probeset_trans_clust_whitepaper.pdf.

     If 'normalize=TRUE' then the expression levels will be scaled to
     'sc'.  For 'sc=0' the expression levels will be scaled to the mean
     expression level.

     If 'update=TRUE' then the existing 'ROOT' file 'filename' will be
     updated, however, this is usually only recommended as option for
     function 'express'.

     In order to use an alternative 'SchemeTreeSet' set the
     corresponding SchemeTreeSet  'xps.scheme'.

     'xpsMAS5' is the 'DataTreeSet' method called by function 'mas5',
     however,  expression levels will not be scaled to a common mean
     expression level.

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

     An 'ExprTreeSet'

_N_o_t_e:

     In contrast to function 'mas5', expression levels computed with
     'xpsMAS5'  will not be scaled to a common mean expression level.

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

     Christian Stratowa

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

     Affymetrix (2002) Statistical Algorithms Description Document,
     Affymetrix Inc.,  Santa Clara, CA, whitepaper. <URL:
     http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf>

     Affymetrix (2005) Exon Probeset Annotations and Transcript Cluster
     Groupings, Affymetrix Inc.,  Santa Clara, CA,
     exon_probeset_trans_clust_whitepaper.pdf.

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

     'express'

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

     ## first, load ROOT scheme file and ROOT data file
     scheme.test3 <- root.scheme(paste(.path.package("xps"),"schemes/SchemeTest3.root",sep="/"))
     data.test3 <- root.data(scheme.test3, paste(.path.package("xps"),"rootdata/DataTest3_cel.root",sep="/"))

     data.mas5 <- mas5(data.test3,"tmp_Test3MAS5",tmpdir="",normalize=TRUE,sc=500,update=TRUE,verbose=FALSE)

     ## get data.frame
     expr.mas5 <- validData(data.mas5)
     head(expr.mas5)

     ## plot results
     if (interactive()) {
     boxplot(data.mas5)
     boxplot(log2(expr.mas5))
     }

     rm(scheme.test3, data.test3)
     gc()

