fdr.ma                package:fdrame                R Documentation

_f_d_r._m_a

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

     This function takes normalized expression data array, experimental
     design and  computes adjusted p-values. It returns the fdr
     adjusted p-values and plots, according to the methods described in
     (Reiner, Yekutieli and Benjamini 2002)

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

     fdr.ma(exp.arr,design,p.method="resampling",fdr.adj="BH-LSU",plot=c("pvlVSrank","adjVSstat"),perms.num=100)

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

 exp.arr: A data frame or matrix, with m rows corresponding to the gene
          expression level of an observation and n columns to the
          observations. In the case of gene expression data, rows
          correspond to genes and columns to mRNA samples. The data can
          be read using 'read.table'. The matrix is as the X matrix in
          multtest package.

  design: A vector of charachters corresponding to observation (column)
          class labels. For k classes, the labels must be k different
          charachters. The vector is similar to classlabel vector in
          multtest package.

p.method: A character string specifying whether resampling mehtod may
          be used. If 'p.method="resampling"', resampling method is
          used. If 'p.method="t.test"', t.test is computed without
          resampling.

 fdr.adj: A character string specifying which type of p-value
          adjustment method may be used. If 'fdr.adj="BH-LSU"',
          Benjamini-Hochberg Linear Step Up porcedure is used. If
          'fdr.adj="point.est"', point estimation procedure is
          used.(p.method value must be "resampling") If
          'fdr.adj="upper.est"', upper estimation procedure is
          used.(p.method value must be "resampling") If
          'fdr.adj="adaptive"', two-stage adaptive procedure is used.

    plot: A vector of character strings specifying the plots that may
          be drawn.  If the vector contains "pvlVSrank", a plot of
          p-values vs rank is drawn.  If the vector contains
          "adjVSrank", a plot of adjusted p-values vs rank is drawn. If
          the vector contains "adjVSstat", a plot of adjusted p-values
          vs computed statistic (f or t, depends depends on the number
          of groups on the design) is drawn.  

perms.num: An integer specifying the number of permutations that would
          be used.

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

     A data frame with components 

     adj: adjusted p-values.

     dif: When there are only two groups dif contains the differences
          between the means of the two groups. when there are more than
          two groups dif contains the multiple R-Squared values.

res.pvalues: resampling p-values. (in case resampling was requested)

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

     Yoav Benjamini, Effi Kenigsberg, Anat Reiner, Daniel Yekutieli

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

     Reiner A, Yekutieli D, Benjamini Y: Identifying differentially
     expressed genes using false discovery rate controlling procedures.
     Bioinformatics 19:368-375, 2003 Benjamini, Y., Krieger,
     A.M.,Yekutieli, D. (2001) "Two Staged Linear Step Up FDR
     Controlling Procedure", Technical Report Department of Statistics
     and O.R., Tel Aviv University.

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

     data(exp.arr,design)
     output<-fdr.ma(exp.arr,design,p.method="theoretic",fdr.adj="BH-LSU",plot=c("pvlVSrank","adjVSrank","adjVSstat"))

