norm1d                 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 _a_n_d _v_a_r_i_a_n_c_e _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_s

_D_e_s_c_r_i_p_t_i_o_n:

     This performs a robust normalization of the variance of the (mean
     normalized) average-across-replicates log ratios by scaling the
     (mean normalized) average-across-replicates log ratio for each
     gene either by the standard deviation of the log ratios for that
     gene across replicates (if bigger than its absolute (mean
     normalized) average-across-replicates log ratio) or scaling by a
     constant (a quantile of the distribution of standard deviations of
     log ratios across replicates for all genes whose standard
     deviation was bigger than their absolute (mean normalized)
     average-across-replicates log ratio.

_U_s_a_g_e:

     norm1d(logratio, logintensity, span = 0.6, quant = 0.99, dye.swap = F)

_A_r_g_u_m_e_n_t_s:

logratio: A multiple-column matrix of replicates of log (base 2) ratios
          of gene expressions in two samples.

logintensity: A multiple-column matrix of replicates of log (base 2)
          total intensities (defined as the product) of gene
          expressions in two samples.

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

   quant: Quantile to be used from the distribution of standard
          deviations of log ratios across replicates for all genes
          whose standard deviation was smaller than their absolute
          (mean normalized) average-across-replicates log ratio.

dye.swap: A logical value indicating whether or not the data consists
          of a balanced dye swap (if FALSE a mean normalization will be
          performed prior to the variance normalization rather than a
          simple averaging across replicates).

_D_e_t_a_i_l_s:

     A balanced dye swap is a data set were the data are split into two
     sets of replicates (same number of replicates in each set) where
     one set has the reverse dye assignment of the other set.

_V_a_l_u_e:

     A vector of mean and variance normalized average-across-replicates
     log ratios.

_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_e_e _A_l_s_o:

     'norm1c','norm1a','norm1b','norm2c','norm2d'

_E_x_a_m_p_l_e_s:

     data(hiv)
     lR<-log(hiv[,1:4],2)-log(hiv[,5:8],2)
     lI<-log(hiv[,1:4],2)+log(hiv[,5:8],2)

     lRnorm<-norm1d(lR,lI,dye.swap=TRUE)

