logitTAffy              package:logitT              R Documentation

_T_e_s_t_i_n_g _f_o_r _d_i_f_f_e_r_e_n_t_i_a_l _g_e_n_e _e_x_p_r_e_s_s_i_o_n _u_s_i_n_g _t_h_e _L_o_g_i_t-_t _a_l_g_o_r_i_t_h_m

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

     This function takes an instance of AffyBatch and calculates
     t-statistics  for tests of differential gene expression for
     oligonucleotide arrays using the Logit-t algorithm.

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

     logitTAffy(object, group)

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

  object: an instance of 'AffyBatch' 

   group: a vector specifying the group label for each array 

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

     For more details see the package vignette.

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

     A named vector containing the t-statistics for each probe set for
     each array.

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

     Tobias Guennel tguennel@vcu.edu

_R_e_f_e_r_e_n_c_e_s:

     William J Lemon, Sandya Liyanarachchi and Ming You (2003).  A high
     performance test of differential gene expression for
     oligonucleotide arrays.  Genome Biology 2003, 4:R67.
     http://genomebiology.com/2003/4/10/R67.

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

     'AffyBatch'

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

     if(require(SpikeInSubset)){
     library(SpikeInSubset)
     data(spikein95)
     logitTex<-logitTAffy(spikein95, group=c("A","A","A","B","B","B"))
     logitTex[1:10]                                                              # extract t-statistics for first ten probe sets
     logitTex[grep("AFFX-BioB-5_at",names(logitTex))]                         # extract t-statistics for specific probe set
     pvals<-(1-pt(abs(logitTex),df=4))*2                                         # calculate two-sided p-values
     signifgenes<-names(logitTex)[pvals<0.01]                                    # find significant probe sets at 0.01 significance level
     }else{
     stop("Please install the SpikeInSubset package to run the example.")
     }

