getResults               package:macat               R Documentation

_A_c_c_e_s_s _r_e_s_u_l_t_s _o_f '_e_v_a_l_S_c_o_r_i_n_g'

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

     This function processes the result of the 'evalScoring' function
     and returns a list of probe sets within chromosome regions deemed
     significant by MACAT. Additional annotation for these probe sets
     is provided along with their identifiers.

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

     getResults(MACATevalScoringOBJ)

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

MACATevalScoringOBJ: Object of class 'MACATevalScoring', usually the
          result from 'evalScoring'

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

     The p-values have been computed individually for probe sets
     (genes), not for whole chromosome regions. Thus, regions deemed
     significant by sliding window approach do not have to consist only
     of probe sets with low p-values. These probe-set p-values are not
     used to determine whether a region is considered significant or
     not. Instead the comparison between actual and interpolated scores
     to actual and interpolated boundaries determines whether a region
     is considered significant.

     This function is called within the plot function for the results
     of 'evalScoring', when HTML output is desired.

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

     A list with the following components, describing probe sets within
     chromosome regions deemed significant: 

 probeID: IDs of probe sets within these chromosome regions

cytoband: chromosomal bands these probe sets have been annotated to

 geneSYM: gene symbols these probe sets have been annotated to

  pvalue: p-values for probe sets; see details

 locusid: EntrezGene-(formerly LocusLink) IDs of these probe sets

genedescription: Description of genes the probe sets have been
          annotated to

probeScore: the differential expression scores for the probe sets

chromosome: chromosome, the analysis has been done for

   class: sample class, the analysis has been done for

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

     MACAT development team

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

     'evalScoring'

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

     data(stjd)
     myevalres <- evalScoring(stjd, class="T", chromosome=6, nperms=10,
                              cross.validate=FALSE) 
     results <- getResults(myevalres)
     summary(results)
     results$probeID[1:20]

