Isofudge               package:IsoGene               R Documentation

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

     The function calculates the fudge factor for SAM test statistics
     for the five test statistics (the global likelihood test,
     Williams, Marcus, M, and the modified M).

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

       Isofudge(x, y)

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

       x: indicates the dose levels

       y: gene expression for all genes

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

     A vector of five fudge factor values for the five SAM test
     statistics.

_N_o_t_e:

     This function calculates the fudge factor for SAM test statistics
     for the five test statistics.

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

     Lin et al.

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

     'isoreg', 'Isoallfdr', 'IsoGenemSAM', 'Isoqqstat',
     'Isoqval','IsoTestSAM','IsoSAMPlot'

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

       set.seed(1234)
       x <- c(rep(1,3), rep(2,3), rep(3,3))
       y1 <- matrix(rnorm(9000, 1,1), 1000, 9)   # 1000 genes with no trends
       y2 <- matrix(c(rnorm(3000, 1,1), rnorm(3000,2,1), rnorm(3000,3,1)),
                    1000, 9)  # 1000 genes with increasing trends
       y <- data.frame(rbind(y1, y2))  # y needs to be a data frame
       fudge.factor <- Isofudge(x,y)

