Current popular nucleosome calling methods are GeneTrack [126], template filtering [58], DANPOS [109], and iNPS [127]. GeneTrack implements a Gaussian smoothing and averaging approach to convert measurements at each genomic coordinate into a continuous probabilistic landscape. Nucleosomes are then detected as the maximal data subset from all local maxima with a user-defined exclusion zone that represents the steric exclusion between neighboring nucleosomes (that is 147 bp) and is centered over each assigned peak. The template filtering algorithm was developed to control for the variable MNase cut patterns observed at different concentrations of MNase digestion. This method uses a set of templates, which match frequently found distributions of sequence tags at MNase-generated nucleosome ends, to extract information about nucleosome positions, sizes and occupancies directly from aligned sequence data. However, the current version of template filtering is only suitable for small genomes (approximately 12 MB) due to memory limitations. iNPS differs from other nucleosome callers in that it uses the wave-like structure of nucleosome datasets as part of its smoothing approach. iNPS detects nucleosomes with various shapes from the first derivative of
