cset2band                package:reb                R Documentation

_c_s_e_t_2_b_a_n_d

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

     This function will summarize gene expression data by cytogenetic
     band

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

     cset2band(exprs, genome, chr = "ALL", organism = NULL, FUN = isAbnormal, ...)

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

   exprs: matrix of gene expression data or similar. The rownames must
          contain the gene identifiers 

  genome: an associated chromLoc annotation object 

     chr: a character vector specifying the chromosomes to analyze

organism: character, "h" for human, "m" for mouse, and "r" for rat.;
          defaults to NULL - loads from chromLocation object 

     FUN: function by which to aggregate/summarize each cytogenetic
          band 

     ...: extra arguments passed on to the aggregate/summary function 

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

     This function loops through each band for a given organism and
     summarizes the data for genes that lie  within each cytogenetic
     band based upon the input function. For example, a matrix of gene
     expression values could be used and the mean expression of each
     band be determined by passing the 'mean' function. Alternative,
     DNA copy number gains or losses could be predicted using the 'reb'
     function and regions of likely gain or losses be summarized by
     cytogenetic band using the 'isAbnormal' function.

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

     a matrix with rows representing cytogenetic bands, and columns
     representing individual samples.

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

     Karl Dykema

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

        data(mcr.eset)
        data(idiogramExample)

     ## Create a vector with the index of normal samples
        norms <- grep("MNC",colnames(mcr.eset@exprs))

     ## Smooth the data using the default 'movbin' method,
     ## with the normal samples as reference and median centering
        cset <- reb(mcr.eset@exprs,vai.chr,ref=norms,center=TRUE)

     ## Mask the result to remove noise
        exprs <- cset[,-norms]
        exprs[abs(exprs) < 1.96] <- NA

     ## Starting data
        midiogram(exprs,vai.chr,method="i",col=.rwb,dlim=c(-4,4))

     ## Summarize each cytogenetic band
        banded <- cset2band(exprs,vai.chr,FUN=mean,na.rm=TRUE)

     ## Create chromLocation object based on human cytobands
        h.cyto <- buildChromCytoband(organism = "h")

     ## Plot all data using mideogram
        midiogram(banded,h.cyto,method="i",col=.rwb,dlim=c(-4,4))

