RankingWilcoxon         package:GeneSelector         R Documentation

_R_a_n_k_i_n_g _b_a_s_e_d _o_n _t_h_e _W_i_l_c_o_x_o_n _s_t_a_t_i_s_t_i_c

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

     The Wilcoxon statistic is rank-based and 'distribution free'.  It
     is equivalent to the Mann-Whitney statistic and also related to
     the 'Area under the curve' (AUC) in the two sample case. The
     implementation is efficient, but still far slower than that of the
     t-statistic.
      For 'S4' method information, see RankingWilcoxon-methods.

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

     RankingWilcoxon(x, y, type = c("unpaired", "paired", "onesample"), pvalues = FALSE, gene.names = NULL, ...)

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

       x: A 'matrix' of gene expression values with rows corresponding
          to genes and columns corresponding to observations or
          alternatively an object of class 'ExpressionSet'.
           If 'type = paired', the first half of the columns
          corresponds to  the first measurements and the second half to
          the second ones.  For instance, if there are 10 observations,
          each measured twice, stored in an expression matrix 'expr', 
          then 'expr[,1]' is paired with 'expr[,11]', 'expr[,2]' with
          'expr[,12]', and so on.

       y: If 'x' is a matrix, then 'y' may be a 'numeric' vector or a
          factor with at most two levels.
           If 'x' is an 'ExpressionSet', then 'y' is a character
          specifying the phenotype variable in the output from 'pData'.
           If 'type = paired', take care that the coding is analogously
          to the requirement concerning 'x'


          "_u_n_p_a_i_r_e_d": two-sample test, Wilcoxon Rank Sum test is
               performed.

          "_p_a_i_r_e_d": Wilcoxon sign rank test is performed on the
               differences.

          "_o_n_e_s_a_m_p_l_e": 'y' has only one level.  The Wilcxon sign rank
               test for difference from zero is performed.


 pvalues: Should p-values be computed ? Default is 'FALSE'.

gene.names: An optional vector of gene names.

     ...: Currently unused argument.

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

     An object of class GeneRanking.

_N_o_t_e:

     Note that although the Wilcoxon Rank Sum test is
     distribution-free, it is not without assumptions.

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

     Martin Slawski martin.slawski@campus.lmu.de 
      Anne-Laure Boulesteix <URL: http://www.slcmsr.net/boulesteix>

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

     GetRepeatRanking, RankingTstat, RankingFC, RankingWelchT, 
     RankingBaldiLong, RankingFoxDimmic, RankingLimma,  RankingEbam,
     RankingWilcEbam, RankingSam,  RankingBstat, RankingShrinkageT,
     RankingSoftthresholdT,  RankingPermutation, RankingGap,
     wilcox.test

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

     ## Load toy gene expression data
     data(toydata)
     ### class labels
     yy <- toydata[1,]
     ### gene expression
     xx <- toydata[-1,]
     ### run RankingWilcoxon
     wilcox <- RankingWilcoxon(xx, yy, type="unpaired")

