pplr                  package:puma                  R Documentation

_P_r_o_b_a_b_i_l_i_t_y _o_f _p_o_s_i_t_i_v_e _l_o_g-_r_a_t_i_o

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

     WARNING - this function is generally not expected to be used, but
     is intended as an internal function. It is included for backwards
     compatibility with the 'pplr' package, but may be deprecated and
     then hidden in future. Users should generally use 'pumaDE'
     instead.

     This function calculates the probability of positive log-ratio
     (PPLR) between any two specified conditions in the input data,
     mean and standard deviation of gene expression level for each
     condition.

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

     pplr(e, control, experiment, sorted=TRUE)

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

       e: a data frame containing the mean and standard deviation of
          gene expression  levels for each condition. 

 control: an integer denoting the control condition. 

experiment: an integer denoting the experiment condition. 

  sorted: Boolean. Should PPLR values be sorted by value? If FALSE,
          PPLR values are returned in same order as supplied.

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

     The input of 'e' should be a data frame comprising of 2*n
     components, where n is  the number of conditions. The first
     1,2,...,n components include the mean of gene expression  values
     for conditions 1,2,...,n, and the n+1, n+2,...,2*n components
     contain the standard deviation of  expression levels for condition
     1,2,...,n.

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

     The return is a data frame. The description of the components are
     below. 

  index : The original row number of genes.

     cM : The mean expression levels under control condition.

      sM: The mean expression levels under experiment condition.

    cStd: The standard deviation of gene expression levels under
          control condition.

    sStd: The standard deviation of gene expression levels under
          experiment condition.

     LRM: The mean log-ratio between control and experiment genes.

   LRStd: The standard deviation of log-ratio between control and
          experiment genes.

    stat: A statistic value which is -mean/(sqrt(2)*standard
          deviation).

    PPLR: Probability of positive log-ratio.

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

     Xuejun Liu, Marta Milo, Neil D. Lawrence, Magnus Rattray

_R_e_f_e_r_e_n_c_e_s:

     Liu,X., Milo,M., Lawrence,N.D. and Rattray,M. (2005) Probe-level
     variances improve accuracy in detecting differential gene
     expression, technical report available upon request.

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

     Related methods 'pumaDE' and 'bcomb'

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

       data(exampleE)
       data(exampleStd)
       r<-bcomb(exampleE,exampleStd,replicates=c(1,1,1,2,2,2),method="map")
       p<-pplr(r,1,2)

