equivalentGOProfiles       package:goProfiles       R Documentation

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

     Performs an equivalence test based on the squared Euclidean
     distance between the Gene Ontology profiles of two lists of genes.
     Equivalence is declared if the upper limit d.sup of a one-sided
     confidence  interval [0, d.sup] for the distance is lesser than
     the equivalence limit d0.

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

     equivalentGOProfiles(goObject, ...)
     ## S3 method for class 'GOProfileHtest':
     equivalentGOProfiles(goObject, equivEpsilon = 0.05, d0 = NULL, confidence = NULL, ...)
     ## S3 method for class 'list':
     equivalentGOProfiles(goObject, ...)
     ## S3 method for class 'ExpandedGOProfile':
     equivalentGOProfiles(goObject, qm=NULL, pqn0=NULL,
         n = ngenes(goObject), m = ngenes(qm), n0 = ngenes(pqn0),
         confidence = 0.95,
         equivEpsilon = 0.05, d0 = NULL,
         simplify = FALSE, ...)
     ## Default S3 method:
     equivalentGOProfiles(goObject, ...)

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

goObject: an object related to GO profiles or comparisons between them 

      qm: an expanded GO profile, i.e. and object of class
          'ExpandedGOProfile' 

    pqn0: an expanded GO profile, i.e. and object of class
          'ExpandedGOProfile' 

       n: a numeric vector with the number of genes profiled in each
          column of goObject. This parameter is included to allow the
          possibility of exploring the consequences of varying sample
          sizes, other than the true sample size in goObject.

       m: a numeric vector with the number of genes profiled in each
          column of qm.

      n0: a numeric vector with the number of genes profiled in each
          column of pqn0.

confidence: the nominal confidence level of the one-sided confidence
          interval on the distance 

      d0: a positive value specifying the equivalence limit 

equivEpsilon: a positive value used to compute 'd0' if it is not
          directly available 

simplify: should the result be simplified, if possible? See the
          'Details' section 

     ...: further arguments, tipically the same than to
          'compareGOProfiles' 

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

     An object of S3 class "ExpandedGOProfile" is, essentially, a
     "data.frame" object with each column representing the relative
     frequencies in all observed node combinations, resulting from
     profiling a set of genes, for a given and fixed ontology. The
     'row.names' attribute codifies the node combinations and each
     "data.frame" column (say, each profile) has an attribute,
     'ngenes', indicating the number of profiled genes. 

     In the 'ExpandedGOProfile' interface, the arguments 'goObject',
     'qm' and 'pqn0' are compared in a column by column wise, recycling
     columns, if necessary, in order to perform
     max(ncol(goObject),ncol(qm),ncol(pqn0)) equivalence tests (each
     test resulting in an object of class 'htest').   In order to be
     properly tested, these arguments are expanded by row, according to
     their row names. That is, the data arguments can have unequal row
     numbers. Then, they are expanded adding rows with zero
     frequencies, in order to make them comparable. In the i-th
     comparison (i from 1 to max(ncol(goObject),ncol(qm),ncol(pqn0))),
     the parameters n, m and n0 are included to allow the possibility
     of exploring the  consequences of varying sample sizes, other than
     the true sample sizes included as  an attribute in goObject, qm
     and pqn0. When qm = NULL, the genes profiled in goObject are
     compared with a  subsample of them, those profiled in pqn0 (is
     there equivalence between a set of genes and a restricted subset,
     e.g. those overexpressed under a disease, in terms of their
     profiles?). When pqn0 = NULL, an equivalence test between two
     profiles with no genes in common is performed.

     In the 'GOProfileHtest' interface, the one-sided confidence
     interval for the squared Euclidean distance is computed from the
     distance and its standard error stored in the corresponding fields
     of the argument goObject, itself typically an object of class
     'GOProfileHtest' resulting from a call to 'compareGOProfiles' with
      simplify=T.

     In the 'list' interface, the argument goObject is intended to be a
     list of objects of class 'GOProfileHtest' typically resulting from
     a call to 'compareGOProfiles' with simplify=F. The call to the
     method is iterated along the list, and the one-sided confidence
     interval for the squared Euclidean distance is computed from the
     distance and its standard error stored in the corresponding fields
     of all the members  of the list.

     In the default interface, the 'goObject' argument is previously
     converted into an object of class 'ExpandedGOProfile' and then
     this interface is used.

     If the argument 'd0' is not provided it is computed as d0 <- s *
     equivEpsilon^2, where 's' stands for the number of non empty GO
     nodes in any of the GO profiles being compared.

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

     In the 'ExpandedGOProfile' and 'list' interfaces, the result is a
     list of objects of class "htest" or a single "htest" object if
     there is only one object in the list and simplify == T. In the
     other interfaces, the result is a single "htest" object. Each one
     of these "htest" objects has the following fields: 

statistic: test statistic, (distance - d0) / se

parameter: d0 and the sample sizes (number of genes) n and m

 p.value: associated p-value to test the null hypothesis of profiles
          inequivalence

conf.int: asymptotic one-sided confidence interval for the squared
          euclidean distance. Its attribute "conf.level" contains its
          nominal confidence level.

estimate: squared euclidean distance between the contracted profiles.
          Its attribute "se" contains its standard error estimate

data.name: a character string giving the names of the data

alternative: a character string describing the alternative hypothesis
          (always 'Equivalence or similarity, true squared Euclidean
          distance between the contracted profiles is less than d0'

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

     Jordi Ocana

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

     'compareGOProfiles'

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

     data(sampleProfiles)
     comparedMF <-compareGOProfiles (pn=expandedWelsh01[['MF']], 
                               qm  = expandedSingh01[['MF']], 
                               pqn0= commonExpandedWelsh01Singh01[['MF']])
     equivMF<- equivalentGOProfiles(comparedMF)
     print(equivSummary(equivMF, decs=5))

