intCor               package:MergeMaid               R Documentation

_C_o_r_r_e_l_a_t_i_o_n _o_f _C_o_r_r_e_l_a_t_i_o_n_s

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

     Given a mergeExpressionSet, this function calculates the study
     specific correlation matrices, and, for each gene, the correlation
     of correlations.

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

        intCor(x,method= c("pearson", "spearman"),exact,...)

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

       x: Object of class mergeExpressionSet.

  method: Method used to calculate correlation coefficient. If exact is
          TRUE, the available methods to use is "spearman" and
          "pearson"; If exact is FALSE, the available methods to use is
          "pearson".

   exact: If exact is TRUE, we use the standard method the calculate 
          the integrative correlation; If exact is FALSE, we use the
          approximate method the calculate.

     ...: Not implemented at this time

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

     Integrative correlation coefficients are calcualted as follows. 
     The first step is to identify the n genes common to all studies.
     Within each study, we calculate the correlation coefficient
     between gene g, and every other common gene.  This gives a vector
     of length n-1.  For a pair of studies, S1 and S2, we calculate the
     correlation of correlations for gene g.  When there are more than
     2 studies under consideration, all pairwise correlation of
     correlations are calculated and averaged.

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

     The output is an object of class  mergeCor.

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

     'mergeCor-class','intcorDens'

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

     if(require(Biobase) & require(MASS)){
       data(mergeData)
       merged  <-mergeExprs(sample1,sample2,sample3)
       corcor  <-intCor(merged,method="spearman")
       
       plot(merged)
       hist(corcor)

       corcor  <-intCor(merged,method="pearson",exact=FALSE)
       corcor  <-intCor(merged[1:2])
       corcor  <-intCor(merged,exact=TRUE)

       vv<-c(1,3)
       corcor1  <-intCor(merged[vv])
       plot(merged,xlab="study A",ylab="study B",main="CORRELATION OF CORRELATION",col=3,pch=4)
       hist(corcor1,xlab="CORRELATION OF CORRELATION")
      }  

