ttest               package:genefilter               R Documentation

_A _f_i_l_t_e_r _f_u_n_c_t_i_o_n _f_o_r _a _t._t_e_s_t

_D_e_s_c_r_i_p_t_i_o_n:

     'ttest' returns a function of one argument with bindings for 'cov'
     and 'p'. The function, when evaluated, performs a t-test using
     'cov' as the covariate. It returns 'TRUE' if the p value for a
     difference in means is less than 'p'.

_U_s_a_g_e:

     ttest(m, p=0.05, na.rm=TRUE)

_A_r_g_u_m_e_n_t_s:

       m: If 'm' is of length one then it is assumed that elements one
          through 'm' of 'x' will be one group. Otherwise 'm' is
          presumed to be the same length as 'x' and constitutes the
          groups.

       p: The p-value for the test. 

   na.rm: If set to 'TRUE' any 'NA''s will be removed. 

_D_e_t_a_i_l_s:

     When the data can be split into two groups (diseased and normal
     for example) then we often want to select genes on their ability
     to distinguish those two groups. The t-test is well suited to this
     and can be used as a filter function.

     This helper function creates a t-test (function) for the specified
     covariate and considers a gene to have passed the filter if the
     p-value for the gene is less than the prespecified 'p'.

_V_a_l_u_e:

     'ttest' returns a function with bindings for 'm' and 'p' that will
     perform a t-test

_A_u_t_h_o_r(_s):

     R. Gentleman

_S_e_e _A_l_s_o:

     'kOverA', 'Anova', 't.test'

_E_x_a_m_p_l_e_s:

       dat <- c(rep(1,5),rep(2,5))
       set.seed(5)
       y <- rnorm(10)
       af <- ttest(dat, .01)
       af(y)
       af2 <- ttest(5, .01)
       af2(y)
       y[8] <- NA
       af(y)
       af2(y)
       y[1:5] <- y[1:5]+10
       af(y)