An R package for Differential Expression Analysis. Given count data from two experimental conditions, denoiSeq helps one determine which transcripts are differentially expressed across the two conditions using Bayesian inference of the parameters of a bottom-up model for PCR amplification developed in “Chromatin conformation governs T cell receptor J beta gene segment usage”, by Ndifon et al.

To use the package, one needs to create a `readsData`

object and invoke the `denoiseq`

function on it. The results
are obtained from the return value of denoiseq using the
`results`

function which then computes the test statistic
used in differential analysis.

```
RD <- new("readsData", counts = ERCC) #creating the readsData object
steps <- 3000 #steps for MCMC
BI <- denoiseq(RD, steps) #invoking denoiseq on the readsData object
rez <- results(BI,steps) #computing the test statistic
```

This package can be istalled from CRAN using install.packages(“denoiSeq”) or from github using devtools::install_github(“buriom/denoiSeq”).