Sort               package:ArrayTools               R Documentation

_S_o_r_t _a _r_e_g_r_e_s_s_i_o_n_R_e_s_u_l_t _o_r _a_n _i_n_t_e_r_a_c_t_i_o_n_R_e_s_u_l_t

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

     Sort a regressionResult or an interactionResult based on p-value,
     fold-change, or F statistics

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

     Sort(x, ...)

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

       x: a regressResult or an interactionResult class

     ...: any other arguments.  See below... 

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

     if sorting a regressResult, returned value is a data frame if
     sorting a interactionResult, returned value is a list of data
     frames

_S_o_r_t _a _r_e_g_r_e_s_s_R_e_s_u_l_t _o_r _a_n _i_n_t_e_r_a_c_t_i_o_n_R_e_s_u_l_t _c_l_a_s_s:

     'Sort(x, sorted.by = c("pValue", "log2Ratio", "F"), top=20)'

     'x' is a regressResult class or an interactionResult class.  
     'sorted.by' can be specified by using "pValue" (p value),
     "log2Ratio" (log2 of fold-change value) or "F" (F statistics).
     'top' is used to specified number of genes being printed

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

     Xiwei Wu, Arthur Li

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

     'regressResult' 'interactionResult'

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

     data(eSetExample)
     design<- new("designMatrix", target=pData(eSetExample), covariates = "Treatment")
     contrast<- new("contrastMatrix", design.matrix = design, 
         compare1 = "Treated", compare2 = "Control")
     result<- regress(eSetExample, contrast)
     Sort(result)

