\name{compareREDseq} \alias{compareREDseq} %- Also NEED an '\alias' for EACH other topic documented here. \title{ Compare two RED Sequencing Dataset } \description{ For early stage experiment without replicates, compareREDseq outputs differentially cut RE sites between two experimental conditions using Fisher's Exact Test. } \usage{ compareREDseq(REsummary, col.count1 = 2, col.count2 = 3, multiAdj = TRUE, multiAdjMethod = "BH", maxP = 1, minCount = 1) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{REsummary}{ A matrix with a RE id column, 2 count/weight column, see examples } \item{col.count1}{ The column where the total count/weight for the 1st experimental condition is } \item{col.count2}{ The column where the total count/weight for the 2nd experimental condition is } \item{multiAdj}{ Whether apply multiple hypothesis testing adjustment, TURE or FALSE } \item{multiAdjMethod}{ Multiple testing procedures, for details, see mt.rawp2adjp in multtest package } \item{maxP}{The maximum p-value to be considered to be significant} \item{minCount}{For a RE site to be included, the tag count from at least one of the experimental condictions >= minimumCount} } \value{ \item{p.value}{the p-value of the test} \item{*.count}{weight/count from the input column col.count1 and col.count2} \item{*.total}{total weight/count from input column col.count1 and col.count2} \item{REid}{the id of the restriction enzyme from the input} \item{odds.ratio}{an estimate of the odds ratio for 2nd experimental condition vs. 1st experimental condition} \item{*.adjusted.p.value}{applicable if multiAdj=TRUE, adjusted p.value using the method * specified in multiAdjMethod} } \author{ Lihua Julie Zhu } \seealso{ binom.test.REDseq } \examples{ library(REDseq) x= cbind(c("RE1", "RE2", "RE3", "RE4"), c(10,1,100, 0),c(5,5,50, 40)) colnames(x) = c("REid", "control", "treated") compareREDseq(x) } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ Statistics }