twowayTable           package:CoCiteStats           R Documentation

_C_o_m_p_u_t_e _a _t_w_o _w_a_y _c_o-_c_i_t_a_t_i_o_n _t_a_b_l_e _f_o_r _2 _g_e_n_e_s.

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

     This function computes a two way table for comparing co-citation,
     in PubMed for the two input genes. The values in the table can be
     adjusted according to either the paper size or the gene size.

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

     twowayTable(g1, g2, weights = TRUE, paperLens=paperLen())

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

      g1: The EntrezGene identifier for gene 1.

      g2: The EntrezGene identifier for gene 2.

 weights: 'TRUE' or 'FALSE' indicating whether paper size weights
          should be used. 

paperLens: A vector containing the  number of genes each paper refers
          to, or cites.

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

     To determine the association between two genes one can use
     co-citation in the medical literature. When 'weights' is  'FALSE'
     this function computes the number of papers that cite only gene 1,
     only gene 2, both and neither. 

     By default, we use the 'org.Hs.eg.db' package to define the set of
     papers that are used in the computations.  For other organisms, or
     for more restricted sets of papers the user will need to supply
     the vector 'paperLens' explicitly.

     One can consider papers which cite many genes to be less
     informative than those that cite only a few genes.  If 'weights'
     is 'TRUE' (the default) then papers are weighted by the inverse of
     the number  of citations.

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

     A vector of length four, with entries 'n11', 'n12', 'n21' and
     'n22'. These correspond to the number of papers that cite both
     genes, the number that cite only gene 1, the number that cite only
     gene 2, and the total number of papers minus those counted in
     'n11', 'n21', 'n12', or in the default case the weighted versions
     of these quantities.

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

     R. Gentleman

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

     'paperLen', 'twTStats'

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

       pL = paperLen()
       twowayTable("10", "100", paperLens=pL)
       twowayTable("10", "100", FALSE, paperLens=pL)

