plotGene              package:RankProd              R Documentation

_G_r_a_p_h_i_c_a_l _D_i_s_p_l_a_y _o_f _T_h_e _e_x_p_r_e_s_s_i_o_n _l_e_v_e_l_s

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

     Plot the expression values and print statistical results  for each
     individual gene based on a user query

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

          plotGene(gene.to.plot,x,gene.names=NULL, data, cl,origin,
                   logged=TRUE,logbase=2)

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

gene.to.plot: Name of the gene to be plotted

       x: the value returned by function RP,  RPadvance or RSadvance 

gene.names: Names of all genes in the data set. If "NULL", rownames  of
          the data will be used

    data: the same as that used in RP or RPadvance

      cl: the same as that used in RP or RPadvance

  origin: a vector containing the origin labels of the  sample. e.g.
          for  the data sets generated at multiple laboratories, the
          label is the same for samples within one lab and different
          for samples  from different labs. The same as that used in
          RPadvance

  logged: if "TRUE", data has bee logged, otherwise set it  to "FALSE"

 logbase: base used when taking log, used to restore the  fold
          change.The default value is 2, this will be  ignored if
          logged=FALSE

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

     A graphical display of the expression levels of the input gene. 
     The estimated statistics for differential expression will be
     printed  on the plot as well as output in the screen.The
     statistics include:  F.C.:fold-change under each dataset if
     multiple datasets are used AveFC: average fold-change across all
     datasets pfp(pval): estimated percentage of false prediction
     (p-value) for  differential expression under each of the two
     tests: up-regulation  in class 2 compared with classs 1 and
     down-regulation in class 2  compared with class 1

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

     Fangxin Hong fhong@salk.edu

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

     'topGene'   'RP'   'RPadvance' 'RSadvance'

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

          
           # Load the data of Golub et al. (1999). data(golub) 
           #contains a 3051x38 gene expression
           # matrix called golub, a vector of length called golub.cl 
           #that consists of the 38 class labels,
           # and a matrix called golub.gnames whose third column contains the gene names.
           data(golub)
      
           #use a subset of data as example, apply the rank product method
           subset <- c(1:4,28:30)
           #Setting rand=123, to make the results reproducible,

           #identify genes that are up-regulated in class 2 
           #(class label =1)
           RP.out <- RP(golub[,subset],golub.cl[subset], rand=123)
           
           #plot the results
           plotRP(RP.out,cutoff=0.05)
           

