aveProbe                package:pcot2                R Documentation

_T_r_a_n_s_f_o_r_m _A_f_f_y_m_e_t_r_i_x _d_a_t_a _s_o _t_h_a_t _u_n_i_q_u_e _g_e_n_e_s _w_i_t_h _m_u_l_t_i_p_l_e
_p_r_o_b_e_s _a_r_e _r_e_p_r_e_s_e_n_t_e_d _b_y _a _s_i_n_g_l_e _e_x_p_r_e_s_s_i_o_n _v_a_l_u_e _o_n _e_a_c_h _a_r_r_a_y.

_D_e_s_c_r_i_p_t_i_o_n:

     In Affymetrix gene expression data, a unique gene can often link
     to multiple probe sets, with such genes then having a greater
     influence on the analysis (particularly if the gene is
     differentially expressed).  To overcome this problem the median is
     taken across all probes sets which represent a unique gene.

_U_s_a_g_e:

     aveProbe(x, imat = NULL, ids)

_A_r_g_u_m_e_n_t_s:

       x: A matrix with no missing values; Each row represents a gene
          and each column represents a sample. 

    imat: A matrix indicating presence or absence of genes in the gene
          sets. The indicator matrix contains rows representing gene
          identifiers of genes present in the expression data and
          columns representing group (gene set) names. 

     ids: A vector of identifiers (e.g., UniGene or LocusLink
          identifiers) representing unique genes which match to the
          probe ids in the expression data. 

_V_a_l_u_e:

    newx: A data matrix with rows representing the input identifiers
          and columns representing samples.

 newimat: A new imat (indicator matrix) with rows representing the
          unique gene identifiers and columns representing gene sets. 

_A_u_t_h_o_r(_s):

     Sarah Song and Mik Black

_S_e_e _A_l_s_o:

     'pcot2','corplot','corplot2'

_E_x_a_m_p_l_e_s:

     library(multtest)
     library(hu6800)  
     data(golub)
     rownames(golub) <- golub.gnames[,3]
     colnames(golub) <- golub.cl
     KEGG.list <- as.list(hu6800PATH)
     imat <- getImat(golub, KEGG.list, ms=10) 
     colnames(imat) <- paste("KEGG", colnames(imat), sep="")

     pathlist <- as.list(hu6800PATH)
     pathlist <- pathlist[match(rownames(golub), names(pathlist))]
     ids <- unlist(mget(names(pathlist), env=hu6800SYMBOL))
     #### transform data matrix only ####
     newdat <- aveProbe(x=golub, ids=ids)$newx
     #### transform both data and imat ####
     output <- aveProbe(x=golub, imat=imat, ids=ids)
     newdat <- output$newx
     newimat <- output$newimat
     newimat <- newimat[,apply(newimat, 2, sum)>=10]

