IsoGenem               package:IsoGene               R Documentation

_T_h_e _f_i_v_e _t_e_s_t _s_t_a_t_i_s_t_i_c_s _c_a_l_c_u_l_a_t_e_d _f_o_r _b_o_t_h _t_h_e _i_n_c_r_e_a_s_i_n_g _a_n_d
_d_e_c_r_e_a_s_i_n_g _t_r_e_n_d_s

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

     The function calculates the values for the five test statistics
     (the global likelihood test, Williams, Marcus, M, and the modified
     M) for testing increasing and decreasing alternatives.

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

     IsoGenem(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 list with components  

   E2.up: the test statistic of global likelihood test for testing
          increasing alternative.

Williams.up: the test statistic of Williams for testing increasing
          alternative.

Marcus.up : the test statistic of Marcus for testing increasing
          alternative.

   M.up : the M test statistic for testing increasing alternative.

ModM.up : the test statistic of the modified M for testing increasing
          alternative.

  E2.dn : the test statistic of Williams for testing increasing
          alternative.

Williams.dn : the test statistic of global likelihood test for testing
          increasing alternative.

Marcus.dn : the test statistic of Williams for testing increasing
          alternative.

    M.dn: the test statistic of global likelihood test for testing
          increasing alternative.

 ModM.dn: the test statistic of Williams for testing increasing
          alternative.

direction: the direction with the higher likelihood of increasing
          (indicated by "u") or decreasing (indicated by "d") trend.

_N_o_t_e:

     This function calculates the five test statistics for both
     increasing and decreasing ordered alternatives for all the genes
     (rows in the data set).

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

     Lin et al.

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

     Testing for Trend in Dose-Response Microarray Experiments: a
     Comparison of Testing Procedures, Multiplicity, and
     Resampling-Based Inference, Lin et al. 2007, Stat. App. in Gen. &
     Mol. Bio., 6(1), article 26.

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

     'isoreg', 'IsoGene1'

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

     ## Not run: 
       set.seed(1234)
       x <- c(rep(1,3),rep(2,3),rep(3,3))
       y1 <- matrix(rnorm(90, 1,1),10,9)  # 10 genes with no trends
       y2 <- matrix(c(rnorm(30, 1,1), rnorm(30,2,1),
                      rnorm(30,3,1)), 10, 9)  # 10 genes with increasing trends
       y <- data.frame(rbind(y1, y2))  # y needs to be a data frame 
       stat <- IsoGenem(x,y) 
       stat
     ## End(Not run)

