norm2c                 package:nudge                 R Documentation

_F_u_n_c_t_i_o_n _f_o_r _n_o_r_m_a_l_i_z_i_n_g _t_h_e _m_e_a_n _o_f _a_v_e_r_a_g_e-_a_c_r_o_s_s-_r_e_p_l_i_c_a_t_e_s _l_o_g _r_a_t_i_o _d_i_f_f_e_r_e_n_c_e_s

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

     This normalization is used when the two samples (control and
     treatment, say) are not being directly compared on the slides but
     instead are being compared to a common reference sample. The
     quantity of interest for each gene is thus the average difference
     between control and treatment log ratios. The normalization is
     done for each gene by subtracting from its
     average-across-replicates log ratio difference the loess estimated
     mean for average-across-replicates log ratio difference based on
     the loess regression of average-across-replicates log ratio
     differences on average-across-replicates log total intensities.

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

     norm2c(control.logratio, txt.logratio, control.logintensity, txt.logintensity,
     span = 0.6)

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

control.logratio: A multiple-column matrix of replicates of log (base
          2) ratios of gene expressions for the control versus
          reference slides.

txt.logratio: A multiple-column matrix of replicates of log (base 2)
          ratios of gene expressions for the treatment versus reference
          slides.

control.logintensity: A multiple-column matrix of replicates of log
          (base 2) total intensities (defined as the product) of gene
          expressions for the control versus reference slides.

txt.logintensity: A multiple-column matrix of replicates of log (base
          2) total intensities (defined as the product) of gene
          expressions for the treatment versus reference slides.

    span: Proportion of data used to fit the loess regression of the
          average-across-replicates log ratio differences on the
          average-across-replicates log total intensities.

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

     A vector of mean normalized average-across-replicates log ratio
     differences.

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

     N. Dean and A. E. Raftery

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

     N. Dean and A. E. Raftery (2005). Normal uniform mixture
     differential gene expression detection for cDNA microarrays.  BMC
     Bioinformatics. 6, 173-186.

     <URL: http://www.biomedcentral.com/1471-2105/6/173> 

     S. Dudoit, Y. H. Yang, M. Callow and T. Speed (2002). Statistical
     methods for identifying differentially expressed genes in
     replicated cDNA microarray experiments. Stat. Sin. 12, 111-139.

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

     'norm2d','norm1a','norm1b','norm1c','norm1d'

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

     apo<-read.csv("http://www.stat.berkeley.edu/users/terry/zarray/Data/ApoA1/rg_a1ko_morph.txt",
     header=TRUE)
     rownames(apo)<-apo[,1]
     apo<-apo[,-1]
     apo<-apo+1

     lRctl<-log(apo[,c(seq(2,16,2))],2)-log(apo[,c(seq(1,15,2))],2)
     lRtxt<-log(apo[,c(seq(18,32,2))],2)-log(apo[,c(seq(17,31,2))],2)
     lIctl<-log(apo[,c(seq(2,16,2))],2)+log(apo[,c(seq(1,15,2))],2)
     lItxt<-log(apo[,c(seq(18,32,2))],2)+log(apo[,c(seq(17,31,2))],2)

     lRnorm<-norm2c(lRctl,lRtxt,lIctl,lItxt)

