mappings               package:exonmap               R Documentation

_M_a_p _b_e_t_w_e_e_n _p_r_o_b_e_s, _p_r_o_b_e_s_e_t_s, _e_x_o_n_s, _t_r_a_n_s_c_r_i_p_t_s _a_n_d _g_e_n_e_s

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

     A set of functions of the form X.to.Y. That take a character
     vector of database identifiers of type X, and return a set of type
     Y, either as a character vector, or as rows in a dataframe.

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

     probeset.to.probe(v,as.vector=TRUE,unique=TRUE,mt.rm=TRUE)
     probeset.to.exon(v,as.vector=TRUE,unique=TRUE,subset=c("core","est","prediction"))
     probeset.to.transcript(v,as.vector=TRUE,unique=TRUE,subset=c("core","est","prediction"))
     probeset.to.gene(v,as.vector=TRUE,unique=TRUE,subset=c("core","est"))
     exon.to.probeset(v,as.vector=TRUE,unique=TRUE,subset=c("core","est","prediction"),probes.min=4)
     exon.to.transcript(v,as.vector=TRUE,unique=TRUE,subset=c("core","est","prediction"))
     exon.to.gene(v,as.vector=TRUE,unique=TRUE,subset=c("core","est"))
     transcript.to.probeset(v,as.vector=TRUE,unique=TRUE,subset=c("core","est","prediction"),probes.min=4)
     transcript.to.exon(v,as.vector=TRUE,unique=TRUE,subset=c("core","est","prediction"))
     transcript.to.gene(v,as.vector=TRUE,unique=TRUE,subset=c("core","est"))
     gene.to.probeset(v,as.vector=TRUE,unique=TRUE,subset=c("core","est"),probes.min=4)
     gene.to.exon(v,as.vector=TRUE,unique=TRUE,subset=c("core","est"))
     gene.to.transcript(v,as.vector=TRUE,unique=TRUE,subset=c("core","est"))
     symbol.to.gene(v,as.vector=TRUE,unique=TRUE)
     gene.to.exon.probeset(v,unique=TRUE,probes.min=4)
     gene.to.exon.probeset.expr(x,v,probes.min=4)
     exon.to.sequence(v,as.vector=TRUE,unique=TRUE,subset=c("core","est"))

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

       v: A character vector of database identifiers

as.vector: If TRUE, return a character vector otherwise return a
          'data.frame'

  unique: If TRUE, remove duplicates from the results

   mt.rm: If TRUE, remove multitarget probesets before returning the
          result

probes.min: Only return probesets with at least this many probes

  subset: Which subset of the database to perform the mapping against?
          'core' refers to Ensembl genes, 'est' refers to Ensembl ESTs
          and 'prediction' refers to Ensembl predictions.

       x: An 'ExpressionSet' object or a 'matrix' containing expression
          data. If the latter, then the rownames must specify the exon
          array probeset names.

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

     Connects to the X:Map database to retrieve data. Before these
     functions can be used, 'xmapConnect' must have been called.

     By default the results are returned as a vector, and duplicate
     entries are removed. Note that the function 'probeset.to.probe',
     by default, also removes multitarget probesets.

     'gene.to.exon.probeset' generates a single 'data.frame' with
     mappings between genes, exons and probesets.
     'gene.to.exon.probeset.exprs' does the same but adds the
     expression data for the corresponding probesets onto the beginning
     of the 'data.frame'.

     Mappings against the prediction subset of the database are made
     slightly more complicated since there are no predicted genes, only
     transcripts and exons. In addition, their IDs are integers not
     strings. The additional functions 'genscan.label.to.id' and
     'genescan.id.to.label' should be used to provide the mapping
     between names of the form 'GENSCAN0000...' and the integer ids
     used for the transcripts.

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

     A character vector, or, if 'as.vector=FALSE', a 'data.frame'.

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

     C.J. Miller, M.J. Okoniewski

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

     <URL: http://xmap.picr.man.ac.uk>

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

     xmapConnect filters details

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

       if(interactive()) {
         xmapConnect()
         probeset.to.gene(c("3743919"))
         probeset.to.gene(c("3743919"),as.vector=FALSE)
         probeset.to.gene(c("3743919","3743919"),as.vector=FALSE,unique=TRUE)
         gene <-  probeset.to.gene(c("3743919"))
         gene.to.probeset(gene,as.vector=TRUE)
         gene.to.exon.probeset(gene)
       }

