Chromatin accessibility profiles generated using ATAC-seq or DNase-seq carry functional information of the regulatory genome that control gene expression. Appropriate normalization of ATACseq and DNase-seq data is essential for accurate differential analysis when studying chromatin dynamics. Existing normalization methods usually assume the same distribution of genomic signals across samples; however, this approach may not be appropriate when there are global changes of chromatin accessibility levels between experimental conditions/samples.
We present IGN (Invariable Gene Normalization), a method for ATAC-seq and DNase-seq data normalization. IGN is performed by normalizing the promoter chromatin accessibility signals for a set of genes that are unchanged in expression, usually obtained from accompanying RNA-seq data, and extrapolating to normalize the genome-wide chromatin accessibility profile. We demonstrate that IGN outperforms existing methods. As the first chromatin accessibility normalization method allowing for global difference, IGN can be widely applied for differential ATAC-seq and DNase-seq analysis.
IGN is performed by normalizing the promoter chromatin accessibility signals for a given gene set that is unchanged in expression, usually obtained from accompanying RNA-seq data, and extrapolating to scale the genome-wide chromatin accessibility profile. This function allows users to normalize ATAC/DNase-seq signal matrix based on promoter signal of invariable genes.
- Changelog
v1.0.0 First version of IGN.
v1.1.0 CSBJ revision
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Package requirements
IGN requires Rscript v3+ to run. -
Github installation Simply clone this repo and install the IGN package in R
$ git clone https://github.com/Tarela/IGN.git
$ cd IGN/
$ R CMD INSTALL IGN_1.1.0.tar.gz- Check the R help document in the IGN package for detailed tutorial
Type the following code in an R session after installing it:
> library(IGN)
> ?IGN