\name{doLPE} \alias{doLPE} %- Also NEED an '\alias' for EACH other topic documented here. \title{Perform LPE analysis} \description{ The local pooled error test attempts to reduce dependence on the within-gene estimates in tests for differential expression, by pooling error estimates within regions of similar intensity. Note that with the large number of genes there will be genes with low within-gene error estimates by chance, so that some signal-to-noise ratios will be large regardless of mean expression intensities and fold-change. The local pooled error attempts to avert this by combining within-gene error estimates with those of genes with similar expression intensity. } \usage{ doLPE(eset, group, member, name = "", snThresh = 3, detectSample = 0.5) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{eset}{an \code{ExpressionSet} object} \item{group}{which group should LPE be performed} \item{member}{optional. The member names in the group specified above} \item{name}{a prefix name for use when writing output to file} \item{snThresh}{S/N ratio threshold to use to define gene detectability} \item{detectSample}{percentage of samples detectable above snThresh to include in LPE test. The default is 50\%. If the probe is detected in 50\% or more samples in one of the subgroup, it is considered in LPE analysis} } \details{ The LPE test statistic numerator is the difference in medians between the two experimental conditions. The test statistic denominator is the combined pooled standard error for the two experimental conditions obtained by looking up the var.M from each baseOlig.error variance function. The conversion to p-values is based on the Gaussian distribution for difference if order statistics (medians). The user may select both the smoother degrees of freedom (smaller is smoother) and the trim percent to obtain a variance function to suit particular issues i.e. variability of genes with low expression intensity. } \value{ Dataframe } \references{Bioconductor LPE package} \author{Y Andrew Sun} \examples{ ##---- Some example usage ---- %-result <- doLPE(eset, "tissue", c("liver", "muscle")) %-result <- doLPE(eset, "tissue", c("liver", "muscle"), detectSample = 0.5) } \keyword{manip}% at least one, from doc/KEYWORDS