complexStatus            package:PCpheno            R Documentation

_C_o_m_p_l_e_x _S_t_a_t_u_s

_D_e_s_c_r_i_p_t_i_o_n:

     Categorize the complex whether or not a complex is composed of a
     significant number of genes involved in a particular phenotype
     than expected by chance.

_U_s_a_g_e:

     complexStatus(data, phenotype, interactome, threshold=0.05)

_A_r_g_u_m_e_n_t_s:

    data: Output from CoHyperG test

phenotype: List of gene names inducing an observed phenotype, e.g.,
          list of essential gene names (see package _SLGI_)

interactome: A binary matrix composed of genes (rows) and biological
          complexes (columns) (see package _ScISI_)

threshold: pvalue threshold (default 0.05)

_D_e_t_a_i_l_s:

     We form four distinct categories from A to D to characterize how a
     complex might be involved in a particular phenotype (according to
     the number of genes it contains and that are involved in a
     particular phenotype - see also CoHyperG function)

_V_a_l_u_e:

     The returned value is a list with components: 

       A: "interesting" complexes, complexes with a significant number
          of interesting genes, i.e., genes that participate to a
          particular phenotype (at a given p-values threshold)

       B: complexes with a NON significant number of interesting genes
          BUT that  SHARE genes with complexes from the A status

       C: complexes with a NON significant number of interesting genes
          AND that DON'T SHARE interesting genes with complexes from
          cat A

       D: complexes WITHOUT interesting genes, i.e. the one involved in
          the studied phenotype

_A_u_t_h_o_r(_s):

     N. LeMeur

_E_x_a_m_p_l_e_s:

     data(ScISI)
     data(essglist)
     essential <- names(essglist)

     CoparamsESS <- new("CoHyperGParams",
                        geneIds=essential, 
                        universeGeneIds=rownames(ScISI),
                        annotation="org.Sc.sgd.db",
                        categoryName="ScISI",
                        pvalueCutoff=0.01,
                        testDirection="over")

     sign<- hyperGTest(CoparamsESS)
     test05 <-complexStatus(data=sign, phenotype=essential,
     interactome=ScISI, threshold=0.05)

