si                  package:exonmap                  R Documentation

_C_a_l_c_u_l_a_t_e _t_h_e _s_p_l_i_c_i_n_g _i_n_d_e_x

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

     Calculates the splicing index for the probesets in one or more
     genes, as defined in the Affymetrix white paper "Alternative
     Transcript Analysis Methods for Exon Arrays".

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

      si(x, genes, group, members, median.gene=FALSE,median.probeset=FALSE,unlogged=TRUE)

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

       x: eSet containing expression data 

   genes: Character vector of Ensembl gene names 

   group: The column name in the ExpressionSet's pData object in which
          to look for 'members' 

 members: The names of the two sets of arrays to compare between as
          defined in the 'group' column

median.gene: Use the median instead of the mean when calculating
          averages across genes

median.probeset: Use the median instead of the mean when calculating
          averages across probesets in each replicate group  

unlogged: Unlog the expression data before calculating the splicing
          index (and then re-log afterwards) 

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

     The splicing index gives a measure of the difference in expression
     level for each probeset in a gene between two sets of arrays,
     relative to the gene-level average in each set. This is calculated
     only for those probesets that are defined as exon targeting and
     non-multitargetted (See 'select.probewise' and 'exclude.probewise'
     for more details of how this filtering is performed.

     The two sets of arrays to compare are specified using the
     annotation in the 'pData' object from 'x' by specifying the name
     of the column in 'pData' in which to look for two sets of arrayds,
     as defined by 'members' (e.g. 'group="treatment",
     members=c("a","b")', will compare between the arrays labelled "a",
     and "b" in the "treatment" column of 'pData(x)').

     The implementation also calculates a 'p.value' and 't.statistic'
     for each probeset; these are returned alongside the splicing
     index.

     By default, the splicing index is calculated using the mean across
     genes and samples. Specifing 'median.gene=TRUE' or
     'median.probeset=TRUE' will use the median instead (for the gene
     or probeset level averages, respectively). It is calculated using
     the unlogged data, unless 'unlogged=FALSE'. This only affects the
     internal calculations; values in 'x' are always assumed to be
     logged, and the splicing index is always returned on the log2
     scale.

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

     A 'list', one element for each gene. Each element contains a
     'data.frame', with the results for a given gene. Each row
     corresponds to a probeset, and there are four columns in the
     'data.frame': '"si","p.value","t.statistic"' and '"gene.av"'.

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

     Crispin J Miller with contributions from Carla Moller Levet and
     Michal J Okoniewski

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

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

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

     'splanova'

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

      
       if(interactive()) {
         xmapConnect()
         data(exonmap)
         gg <- probeset.to.gene(c("2326780","2326822" ))
         spl.idx <-  si(x, gg, "group", c("a","b"))
         spl.idx <-  si(x, gg, gps=list(1:3,4:6))
       }

