getPvalues               package:topGO               R Documentation

_F_u_n_c_t_i_o_n _t_o _c_o_m_p_u_t_e _p-_v_a_l_u_e_s _o_f _a _t-_t_e_s_t _f_o_r _a _g_e_n_e _e_x_p_r_e_s_s_i_o_n _m_a_t_r_i_x.

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

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

        getPvalues(edata, classlabel, test = "t", alternative = c("greater", "two.sided", "less")[1],
        genesID = NULL, correction = c("none", "Bonferroni", "Holm", "Hochberg", "SidakSS", "SidakSD",
        "BH", "BY")[8]) 

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

   edata: Gene expression matrix.

classlabel: The phenotype of the data

    test: Which test statistic to use

alternative: The alternative of the test statistic

 genesID: if a subset of genes is provided

correction: Multiple testing correction procedure

_D_e_t_a_i_l_s:

     ~~ If necessary, more details than the description above ~~

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

     An named vector of p-values is returned.

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

     Adrian Alexa

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

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

     library(ALL)
     data(ALL)

     ## discriminate B-cell from T-cell
     classLabel <- as.integer(sapply(ALL$BT, function(x) return(substr(x, 1, 1) == 'T')))

     ## Differentially expressed genes
     geneList <- getPvalues(exprs(ALL), classlabel = classLabel,
                            alternative = "greater", correction = "BY")

     hist(geneList, 50)

