In a first step FAIRE-seq data are mapped to the reference genome of the model organism used.
Next, the identification of genomic regions with open chromatin, is done by using a peak calling algorithm. Different tools offer packages to do this (e.g. ChIPOTle ZINBA and MACS2). ChIPOTle uses a sliding window of 300bp to identify statistically significant signals. In contrast, MACS2 identifies the enriched signal  by combining the parameter callpeak with other options like broad, broad cutoff, no model or shift. ZINBA is a generic algorithm for detection of enrichment in short read dataset. It thus helps in the accurate detection of signal in complex datasets having low signal-to noise ratio.
BedTools is used to merge the enriched regions residing close to each other to form COREs (Cluster of open regulatory elements). This helps in the identification of chromatin accessible regions and gene regulation patterns which would have been undetectable otherwise, considering the lower resolution FAIRE-seq often brings with it.
Data is typically visualized as tracks (e.g. bigWig) and can be uploaded to the UCSC genome browser.
The major limitation of this method, i.e. the low signal-to-noise ratio compared to other chromatin accessibility assays, makes the computational interpretation of these data very difficult.