iSummary                package:SLGI                R Documentation

_S_u_m_m_a_r_i_z_e _c_e_l_l_u_l_a_r _o_r_g_a_n_i_z_a_t_i_o_n_a_l _u_n_i_t_s _s_h_a_r_i_n_g _g_e_n_e_t_i_c _i_n_t_e_r_a_c_t_i_o_n

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

     Summarize the cellular organizational units sharing genetic
     interactions and display their GO annotation if available

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

     iSummary(iMat, n=10, reverse=FALSE)

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

    iMat: Comembership matrix of genes(proteins) that linked to other
          genes(proteins) by any biological experiment, e.g., output of
          the 'getInteraction' function.

       n: Numeric threshold indicating the minimum number of genetic
          interactions that a pair of cellular organizational unit must
          share.

 reverse: Logical, by default the function return a list of pair of
          cellular organizational units where the name of each element
          is the number of genetic interactions they share. If reverse
          is TRUE, the output is a vector where the values are the
          number of interactions and the names are the combination of
          the 2 cellular organizational units.

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

     The function print the result in the standard output but can also
     save it in variable.

     If 'reverse' is FALSE the output is a list of pairs of cellular
     organizational units where the name of each element is the number
     of genetic interactions they share.

     If 'reverse' is TRUE the output is a vector where the values are
     the number of interactions and the names are the combination of
     the 2 cellular organizational units.

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

     N. LeMeur

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

     data(Atong)
     data(ScISIC)
     data(SGA)
     SLa2 <- gi2Interactome(Atong, ScISIC)
     ## Search for synthetic lethal interaction
     compM <- getInteraction(SLa2, SGA, ScISIC)
     ## Display the tightly interacting pairs
     largeInt <- iSummary(compM$bwMat,n=15)

