# compareREDseq: Compare two RED Sequencing Dataset In REDseq: Analysis of high-throughput sequencing data processed by restriction enzyme digestion

## Description

For early stage experiment without replicates, compareREDseq outputs differentially cut RE sites between two experimental conditions using Fisher's Exact Test.

## Usage

 ```1 2``` ```compareREDseq(REsummary, col.count1 = 2, col.count2 = 3, multiAdj = TRUE, multiAdjMethod = "BH", maxP = 1, minCount = 1) ```

## Arguments

 `REsummary` A matrix with a RE id column, 2 count/weight column, see examples `col.count1` The column where the total count/weight for the 1st experimental condition is `col.count2` The column where the total count/weight for the 2nd experimental condition is `multiAdj` Whether apply multiple hypothesis testing adjustment, TURE or FALSE `multiAdjMethod` Multiple testing procedures, for details, see mt.rawp2adjp in multtest package `maxP` The maximum p-value to be considered to be significant `minCount` For a RE site to be included, the tag count from at least one of the experimental condictions >= minimumCount

## Value

 `p.value` the p-value of the test `*.count` weight/count from the input column col.count1 and col.count2 `*.total` total weight/count from input column col.count1 and col.count2 `REid` the id of the restriction enzyme from the input `odds.ratio` an estimate of the odds ratio for 2nd experimental condition vs. 1st experimental condition `*.adjusted.p.value` applicable if multiAdj=TRUE, adjusted p.value using the method * specified in multiAdjMethod

## Author(s)

Lihua Julie Zhu

 ```1 2 3 4``` ```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) ```
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