\name{pplr} \alias{pplr} \title{ Probability of positive log-ratio } \description{ 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 \pkg{pplr} package, but may be deprecated and then hidden in future. Users should generally use \code{\link{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. } \usage{ pplr(e, control, experiment, sorted=TRUE) } \arguments{ \item{e}{ a data frame containing the mean and standard deviation of gene expression levels for each condition. } \item{control}{ an integer denoting the control condition. } \item{experiment}{ an integer denoting the experiment condition. } \item{sorted}{ Boolean. Should PPLR values be sorted by value? If FALSE, PPLR values are returned in same order as supplied.} } \details{ 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. } \value{ The return is a data frame. The description of the components are below. \item{index }{The original row number of genes.} \item{cM }{The mean expression levels under control condition.} \item{sM}{The mean expression levels under experiment condition.} \item{cStd}{The standard deviation of gene expression levels under control condition.} \item{sStd}{The standard deviation of gene expression levels under experiment condition.} \item{LRM}{The mean log-ratio between control and experiment genes.} \item{LRStd}{The standard deviation of log-ratio between control and experiment genes.} \item{stat}{A statistic value which is -mean/(sqrt(2)*standard deviation).} \item{PPLR}{Probability of positive log-ratio.} } \references{ 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.} \author{ Xuejun Liu, Marta Milo, Neil D. Lawrence, Magnus Rattray } \seealso{ Related methods \code{\link{pumaDE}} and \code{\link{bcomb}} } \examples{ data(exampleE) data(exampleStd) r<-bcomb(exampleE,exampleStd,replicates=c(1,1,1,2,2,2),method="map") p<-pplr(r,1,2) } \keyword{ manip } \keyword{ models }